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Wireless Cooperative Video Coding Using a HybridDigital-Analog Scheme
Lei Yu, Houqiang Li, Senior Member, IEEE, and Weiping Li, Fellow, IEEE
Abstract—Wireless video broadcast/multicast and mobile videocommunication pose a challenge to the conventional video trans-mission strategy (which applies separate digital source coding anddigital channel coding in a point-to-point communication system),and therefore cooperative communication has been proposed toimprove the received quality of the receivers with bad channelsand the robustness to fading (mobility). In this paper, we proposea novel wireless cooperative video coding (WCVC) framework.Specifically, we present a cooperative joint source-channel coding(JSCC) scheme which is based on hybrid digital-analog (HDA)coding, and integrates the advantages of digital coding and analogcoding. Compared to most state-of-the-art cooperative videodelivery methods, no matter for cooperation scenario or nonco-operation scenario, the proposed scheme can avoid the “staircaseeffect” and realize Continuous Quality Scalability (CQS) on con-dition that the channel quality is within the expected range, andit has strong adaptability to channel variation with higher codingefficiency and better fairness among all receivers. Therefore,it is very suitable for wireless cooperative/noncooperative videobroadcast/multicast transmission and cooperative/noncooperativemobile video applications. The experimental results show thatthe proposed WCVC outperforms SoftCast (which is a newanalog scheme) and SVC+HM (which combines H.264/SVCcodec and hierarchical modulation technique) no matter fornoncooperative scenario or for cooperative scenario, which verifythe effectiveness of our proposed WCVC framework.
Index Terms—Wireless cooperative video coding (WCVC),wireless cooperative scalable video coding (WCSVC), wirelessvideo broadcast/multicast, hybrid digital-analog (HDA), jointsource-channel coding (JSCC), robust video communication, con-tinuous quality scalability (CQS), fading channel, relay channel.
I. INTRODUCTION
W IRELESS video services are becoming increasinglyimportant and popular with the rapid development
of wireless network and mobile terminals, which involvea diversity of real-time applications, such as mobile TV,mobile video conference, wireless video surveillance, etc. Andmost of them belong to wireless video broadcast/multicastand/or mobile video communication. This poses a challenge
Manuscript received March 21, 2014; revised July 27, 2014. This paper wasrecommended by Associate Editor Jie Liang. This work was supported in partby 973 Program under Contract 2013CB329004, Natural Science Foundationof China (NSFC) under Contract 61390510 and Contract 61325009, andthe Fundamental Research Funds for the Central Universities under ContractWK2100060011.
The authors are with the Chinese Academy of Sciences Key Laboratory ofTechnology in Geo-Spatial Information Processing and Application System,University of Science and Technology of China, Hefei 230027, China (e-mail:[email protected], [email protected], [email protected]).
Copyright (c) 2014 IEEE. Personal use of this material is permitted.However, permission to use this material for any other purposes must beobtained from the IEEE by sending an email to [email protected].
to the conventional video transmission strategy, which appliesseparate digital source coding and digital channel coding ina point-to-point communication system. The problems resultfrom two main reasons. The first reason is that for mobilevideo communication the unreliability characteristic (mainlythe fading) of wireless links causes the conventional systemto suffer from cliff effect [21] (also named as threshold effect)which refers to the fact that when the channel signal-to-noise ratio (SNR) falls beneath a certain threshold then thereceived video quality degrades drastically, and when thechannel SNR increases above the threshold, the received videoquality cannot improve any more This problem, which iswell known in the literature, is due to the entropy coding’ssensitivity to bit errors the total breakdown of most pow-erful error-correcting codes at low channel SNRs, and theunrecoverable quantizing distortion. The second reason is thatfor video broadcast/multicast services, the bitrate selected byconventional wireless video delivery scheme cannot match allreceivers at the same time. If the video is transmitted at a highbitrate, it can be decoded only by those receivers with betterquality channels, but it is unfair to those receivers with worsequality channels; on the contrary, if it is transmitted at a lowbitrate supported by all receivers, it reduces the performanceof the receivers with better quality channels, and it is unfairto them.
Diversity plays an important role in improving robustnessto fading, which is the main unreliability characteristic ofwireless links for mobile video communication. Forward errorcorrection (FEC) combined with interleaving technology hasbrought improvements in robustness to fading by providingdiversity in the time domain. Another technology to improverobustness to fading is orthogonal frequency-division mul-tiplexing (OFDM) technology, which can provide frequen-cy diversity. Besides, multiple-input multiple-output (MIMO)technology is also able to improve robustness to fading byproviding spatial diversity (also named antenna diversity). Asan alternative to multiple antenna systems when the devicesare limited to a single antenna (because of the limitations onthe device size and resources), user cooperation or wirelessrelaying is now being vigorously researched to provide spatialdiversity (or cooperative diversity).
As shown in Fig. 1, in cooperative communication systems,wireless signal transmitted from a source node is receivedby multiple terminals. Some of them (called relays, whichmay be also the destination terminals intending the transmittedinformation at the same time) process and forward the signal toother intended terminals, who combine different copies of thesignal to improve the end-to-end performance. Such a spatial
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Fig. 1. A typical wireless cooperative video communication scenario.
diversity scheme provides the adaptability to the time-varyingchannel by exploiting the network resources instead of limitingitself to the bottlenecks of the point-to-point channel.
The basic idea of cooperative communication system wasproposed by Cover and EI Gamal [1], which is a three-nodenetwork consisting of the source, the destination, and a relay.Furthermore, two major coding schemes are proposed for therelay channel in [1], which are widely known as Decode-and-Forward (DF) and Compress-and-Forward (CF) today. InDF, the relay decodes the source message in one block andtransmits the re-encoded message in the following block; whilein CF the relay quantizes the received signal in one block andtransmits the encoded version of the quantized received signalin the following block. Sendonaris et al. [2], [3] introduced theconcept of cooperation among wireless terminals for spatialdiversity. They showed that user cooperation is able to effec-tively achieve robustness against fading. Besides DF and CF,another simpler relaying scheme called Amplify-and-Forward(AF) has been discussed in the literature [4]-[6], which allowsthe relay to receive the signal transmitted from the sender, andthen amplify and retransmit it to the destination. Furthermore,some mixed strategies have been proposed [7], [9], [10], e.g., amixed strategy which combines CF with DF strategy has beenintroduced in [7]. In addition, several generalizations of relaychannels have been comprehensively studied in [7], [8], suchas relay channels combined with broadcast (called broadcastrelay channels) or relay channels combined with multiaccess(called multiaccess relay channels).
Besides diversity technologies such as MIMO, user coop-eration, etc., another approach to improve robustness is jointsource and channel coding (JSCC). Separate source-channelcoding consists of separate digital source compression codingpart and digital channel coding part; while for any othersource-channel coding scheme, it can be seen as a joint source-channel coding scheme, such as analog coding where onlylinear coding operation, rather than digital coding techniques(e.g., entropy-coding or digital channel-coding), is adopted,or hybrid digital-analog (HDA) coding where both linearcoding operation and digital coding techniques are adopted.It deserves to note that JSCC is not only able to improverobustness, but also able to improve Quality Scalability (whichmeasures how gracefully one receiver’s reconstructed videoquality varies with its channel variation over time, and re-flects the robustness and adaptability of one scheme to thereceiver’s channel variation) and fairness among all receiversfor broadcast/multicast scenario. In [11]-[16], Erkip et al.introduced the problem of joint source-channel coding incooperative relay systems. They considered layered digital
coding scheme, analog coding (uncoded) scheme and HDAcoding scheme; and through simulation studies, they comparedthe achievable minimal distortions by different schemes forthe i.i.d. Gaussian source [11]-[15]. However, for a real videosource, they only proposed several digital coding schemes forcooperative scenario [16], [16], such as layered video compres-sion combined with progressive transmission. Besides, thereare some other studies on digital-coding-based cooperativescalable video streaming in the literature. Most of them focuson unicast scheduling of scalable video streams, and moreoveradopt scalable (layered) source coding and dynamic resourceallocation, such as [18]-[20]. Cooperative relaying in uplinkmulti-user wireless video transmissions is considered in [18].By jointly optimizing the packet scheduling and physical layer,the proposed scheme maximizes the long-term sum of videoquality across the video terminals. In [19], the authors inves-tigate relay-assisted downlink multi-user video streaming in acognitive radio (CR) cellular network. They incorporate zero-forcing precoding to eliminate interference among differentencoded signals, and further by jointly optimizing spectrumsensing, power allocation, and channel selection they achievethe optimal reconstructed video quality at all users. In [20], theauthors propose a cooperative MIMO architecture, and basedon this architecture, they design an unequal-error-protection-based JSCC algorithm to minimize the expectation distortionof video.
Recently, some analog (or near-analog) and HDA jointsource-channel coding schemes for video communication havebeen proposed, such as SoftCast [24], [25], DCast [26],[27], ParCast [28], and WSVC [30], [31]. However, they arealmost all designed for noncooperative video communicationscenario; and to the best of our knowledge, so far there ishardly any analog scheme or HDA scheme for cooperativevideo communication. SoftCast is an analog video broadcastscheme which transmits the linear transform of the videosignal directly in analog channel without quantization, entropycoding and FEC. Therefore, it is able to provide better QualityScalability (realizing Continuous Quality Scalability (CQS))than digital scheme owing to the nature of analog coding.However, in theory, such analog scheme with linear mapping(from source signals to channel signals) is relatively inefficientfor most of the signal sources with large memory such as video[22], [23]. The follow-up works after SoftCast include DCast[26], [27], ParCast [28], both of which share the same coremodules as SoftCast. DCast adds coset coding and syndromecoding [which are two typical techniques used in distributedsource coding (DSC)] into SoftCast to further remove orutilize the source redundancy. ParCast extends SoftCast to thevideo transmission over MIMO-OFDM channel by scaling thesource data to match the source components and subchannels.However, unlike SoftCast and DCast, ParCast is designed foronly one given MIMO-OFDM channel, so it only appliesto video unicast communication scenario. Besides, FlexCast[29] is another video coding and transmission scheme usinga soft-reconstruction-based digital coding approach. Similarly,FlexCast is also designed for noncooperative video unicastcommunication scenario and can hardly multicast or broadcastvideo to the users with different SNRs simultaneously because
3
of applying motion compensation (the error propagation prob-ably occurs when channel SNR is low). In addition, generally,for video source, separate digital coding is able to achieve thehigh coding efficiency, and analog coding is able to achievethe desirable Quality Scalability; while hybrid digital-analogscheme is able to make an optimal trade-off between codingefficiency and Quality Scalability. One of HDA-based videocoding schemes, named WSVC [30], [31], has been proposedby us recently, which is a state-of-the-art HDA scheme andachieves higher coding efficiency and better Quality Scala-bility. Owing to lack of analog scheme or HDA scheme forcooperative video communication, it is extremely meaningfulto propose one HDA-based cooperative video coding scheme.Moreover, although cooperation-based single-layered or multi-layered digital coding is able to improve robustness to fading,it also unavoidably causes cliff effect or staircase effect. Atthe same time, HDA-based coding scheme is able to providegraceful quality variation with channel quality varying overtime, i.e., it has better Quality Scalability. Besides, it isalso able to provide better fairness among all receivers forbroadcast/multicast scenario. Therefore, applying HDA codingin cooperative video communication may probably achievebetter overall performance than most of the existing schemes.
In this paper, we consider the problem of JSCC on the co-operative communication system and propose a novel wirelesscooperative video coding (WCVC) framework. In particular,we present a hybrid digital-analog joint source-channel codingscheme for cooperative communication system (where thedigital coding part codes base layer and the analog codingpart codes enhancement layer) that integrates the advantagesof digital coding and analog coding—high coding efficiencyand high Quality Scalability. This scheme is based on ourprior work, wireless scalable video coding (WSVC) [30],[31], which is a HDA scheme for noncooperative communica-tion scenario. Relative to most state-of-the-art video deliverymethods, our WCVC has remarkable performance in QualityScalability and coding efficiency. Furthermore, it is compatiblewith WSVC, and consequently it can be easily extendedto realize full scalability (quality, temporal and spatial s-calability). Therefore, it is very suitable for wireless videobroadcast/multicast and mobile video scenarios no matter forcooperative communication or for noncooperative communi-cation.
The rest of the paper is organized as follows. The systemmodel is described in Section II. The proposed WCVC iselaborated on in Section III. Next, Section IV extends theability of our proposed WCVC to support compatibility withH.264/SVC, bandwidth adaptation and full scalability; besides,Section IV also includes the complexity and delay analysisof WCVC. Then, the evaluation environment and the experi-mental results are presented in Section V. Finally, Section VIconcludes the paper.
II. SYSTEM MODEL
We consider the wireless video transmission system depict-ed in Fig. 2, where a sender S broadcasts one video sequenceto a cooperative group with two destination receivers T1 and
Fig. 2. Communication system model.
T2. They can forward the information they achieved to eachother. We assume time-division transmission is considered here(which means that the transmission from the sender to thereceivers and the transmissions between the receivers occupydifferent time slots, and moreover the transmissions betweenthe receivers in different directions also occupy differenttime slots), and furthermore, we assume that all channels arefrequency-flat Rayleigh fading and the phase shift informationof each channel is perfectly known by the receiver. Thereforethe broadcast channel from the sender to all receivers can bemodeled as
y1 = h1x+ n1,y2 = h2x+ n2,
(1)
where y1 and y2 are the complex signals received by thereceivers T1 and T2 directly from the sender, x is the complexsignal transmitted by the sender S and is achieved by encodingoriginal video sequence, h1 and h2 are the channel coefficients(channel gains) which are mutually independent and subjectedto unidimensional Rayleigh distribution with unit variance, n1
and n2 are complex white Gaussian noises with variancesN1 and N2 respectively. In addition, the average transmittingpower for the sender is constrained by the average availablepower Pt, i.e.,
E{|x|2
}≤ Pt. (2)
In the case of cooperation, a receiver can share its informationwith the partner. The receivers T1 and T2 receive signals y21and y12 from each other respectively that can be expressed as
y12 = h12x1 + n12,y21 = h21x2 + n21,
(3)
where x1 and x2 are the complex signal retransmitted byT1 and T2 respectively and are generated from the receivedsignals y1 and y2 respectively, h12 and h21 are the channelcoefficients which are independent and subjected to unidimen-sional Rayleigh distribution with unit variance, n12 and n21 arecomplex white Gaussian noises with variances N12 and N21
respectively. In addition, the average transmitting power forthe relays T1 and T2 are constrained by the average availablepower P1,t and P2,t respectively, i.e.,
E{|x1|2
}≤ P1,t,
E{|x2|2
}≤ P2,t.
(4)
In addition, throughout this paper, we use the symbol withoutarrowhead to denote each component of the correspondingcomplex signal, e.g., x denotes each component of x.
4
Considering the performance improvement for the relayfrom the worse receiver (the receiver with smaller instanta-neous channel SNR from sender) to the better receiver (thereceiver with larger instantaneous channel SNR from sender)is very limited, so it is resonable to assume that at any timethe relay signal is always transmitted from the better to theworse (it means that at the same time there is no relay signaltransmitted in the opposite direction). Therefore, based on thisassumption, we allocate the same number of time slots for thetransmission from the sender and the receivers as that for thetransmission between the receivers. This means that for AFscheme, the better receiver can relay all received signals to theworse receiver. In addition, we assume that for each channel,its average SNR (channel distribution information (CDI)) isknown by the transmitter and the receiver, and meanwhile, theinstantaneous channel coefficient (channel state information(CSI)) is only known at the receiver at current time. Certainly,the all past CSIs can be available at all terminals by commu-nicating them to each other.
By cooperation, T1 and T2 receive the extra informationy21 and y12 from each other, therefore each of them canreconstruct a better video from all its own received signals. Ifthere is no cooperation, only the signal y1 and y2 can be usedto reconstruct video sequences for T1 and T2 respectively.
III. PROPOSED WCVC FRAMEWORK
As shown in Fig. 3, the proposed WCVC consists of HDA-Cast encoder part, HDA-Relay part, and HDA-Decoder part.To focus on cooperative coding in this paper, we adopt HDA-Cast in WCVC, which is one realization of WSVC [30],[31] with only quality scalability. However, the proposedWCVC is able to be extended to support spatial scalabilityand temporal scalability by replacing HDA-Cast encoder withWSVC encoder (The detailed process will be presented inSection IV). Next, we will introduce each part of our WCVCin detail.
A. HDA-Cast
In order to take advantages of both digital and analogschemes, our HDA-Cast adopts a hybrid scheme which com-bines the low bitrate digital coding (as base layer coding) withthe linear analog coding (as enhancement layer coding), i.e.,MSoftCast (a modified version of SoftCast), by superposingdigital modulation signal and analog modulation signal. Sucha hybrid scheme can provide desirable Quality Scalability aswell as make full use of the channel capacity on condition thatthe channel quality is within the expected range.
As shown in Fig. 4, HDA-Cast consists of the codingpart, which includes both the digital and analog codecs,and the denoising part. At the sender side, original videoframes are firstly encoded using H.264/AVC [35] as baselayer; next, the output bitstream is channel-coded, interleaved,BPSK-modulated and power-allocated by the sender; then, theresidual after coding base layer (i.e., the difference betweenthe original video and the reconstruction of base layer), as thesource of enhancement layer, are processed sequentially by3D-DCT, power allocation and mapping (analog modulation);
Fig. 3. Framework of our proposed WCVC.
finally, the output signals of digital encoder (as coded signalsof base layer) and the output signals of the analog encoder(as coded signals of enhancement layer) are superposed andthen transmitted. At the receiver side, the decoder first decodesthe digital signal “correctly” (with high probability); next,it obtains the analog signal by subtracting the digital signalfrom the received signal; finally, it reconstructs the videoby adding the digital part (decoded by H.264/AVC) and thereconstructed residual part (decoded by the analog decoder).However, due to the effect of analog coding, it is unavoidablethat the reconstructed video using digital and analog codecsmay contain analog noise. Therefore, it is desired to denoisethe reconstructed video to achieve better visual quality atthe receivers, especially for the receivers with bad qualitychannels. Therefore the linear minimum mean square error(LMMSE) filter is adopted in video denoising part of HDA-Cast. The details about HDA-Cast or WSVC can be seen in[30], [31].
For the integrity of the paper, power allocation and LMMSEestimator in HDA-Cast are briefly described below Assumingthat s (k) is the output coefficient of 3D-DCT in k-th PAU(power allocation unit), then the power allocation that mini-mizes the mean square reconstruction error for s (k) is givenby
xa0 (k) = g (k) s (k) ,
g (k) =
√NPPa/2
σs(k)∑NP
i=1 σs(i),
(5)
where xa0 (k) is the output of power allocation for s (k), g (k)is the power allocation scaling factor for s (k), NP is thenumber of the PAUs in each GOP (group of pictures), σs(k) isthe rounded-off standard deviation of s (k), and Pa is averagepower allocated to the analog modulated signal (the outputof MSoftCast) xa. The LMMSE estimator provides a high-quality estimate of the DCT components by leveraging theknowledge of the statistics of the DCT components as wellas the statistics of the channel noise, which is represented asfollows:
ya0 (k) = h (k)xa0 (k) + n (k) ,
s (k) =g(k)h(k)σ2
s(k)g2(k)h2(k)σ2
s(k)+N/2ya0 (k) ,(6)
where ya0 (k) is the received signal for xa0 (k), h (k) is thecorresponding channel coefficient, n (k) is the channel noise
5
Analog (MSoftCast) Encoder
Digital Encoder
H264/AVC
Encoder
-
FEC
&Interleaving
&Modulation
OFDM
Channel3D-DCT
Power
Allocation
2+Mapping
Received
Signal
Residual
Error
H264 Reconstructed Video
-+
Power
Allocation
1
Side Information
H264 Bitstream
Original
Video
s ax0ax
dx
x y
0dx
(a) The encoder of HDA-Cast
Analog (MSoftCast) Decoder
Digital Decoder Video Denoising
Demodulation
&Deinterleaving
&Decoder
H264/AVC
Decoder +Recons-
tructed
Video
- 3D-IDCTLMMSE
EstimatorDemapping
Received
Signal
H264
Reconstructed
Video
Reconstructed
Residual Error
-+
FEC
&Interleaving
&Modulation
H264 Bitstream
Side Infomation
s
Video
Denoising
Denoised
Video
Auxiliary Information
0ayayˆdx
Scaling
y
(b) The decoder of HDA-Cast
Fig. 4. Framework of HDA-Cast.
Fig. 5. Mapping output of the digital and analog encoders to I/Q componentsof transmitted signal.
and N/2 is its variance, and s(k) is the output of LMMSEestimator for s (k)
Superposition based HDA modulation is used in our HDA-Cast. As shown in Fig. 5, the transmitted signal x is thesuperposition of BPSK-modulated signal xd and the outputof MSoftCast xa, i.e.,
x = xd + xa. (7)
For the integrity of the paper, the overall power allocation(i.e., dividing the average available power Pt into the averagepower of digital signals Pd and the average power of analogsignals Pa) in HDA-Cast are briefly described below Assumethat Γ
(PTE
)is the lowest average SNR of base layer (i.e., the
ratio of the power of BPSK-modulated signals and the totalpower of analog and noise signals in the I component) neededfor the adopted FEC to guarantee that the decoding bit errorrate (BER) is not larger than the target BER PT
E . Then, toguarantee that the decoding BER is not larger than PT
E , thefollowing inequality should be satisfied,
Pd
Pa2 +N/2≥ Γ
(PTE
), (8)
where Pd and Pa2 are the allocated average power to xd
and xa2 respectively Combine it with the following averagetransmitting power constraint, and power equality,
Pd + Pa ≤ Pt,Pa = Pa1 + Pa2,
(9)
then we have the optimal overall power allocation,
Pa =(1+µ)
(1−
Γ(PTE )
2γm
)1+µ+Γ(PT
E )Pt,
Pd = Pt − Pa.
(10)
where Pa is the allocated average power to xa, γm denotesminimum of target average channel SNR range, i.e. γm =Pt/Nm, where Nm is the maximum power of channel noise,µ is given by
µ , Pa1
Pa2=
∑NP /2i=1 σs(ki)∑NP
i=NP /2+1 σs(ki), (11)
where ki, 1 ≤ i ≤ NP are the indices achieved by sortingσs(k), 1 ≤ k ≤ NP in descending order σs(k1) ≥ σs(k2) ≥· · · ≥ σs(kNP
), Pa1 is the allocated average power to xa1,and
Pa1 = µPa/(1 + µ),Pa2 = Pa/(1 + µ).
(12)
Although all formulas above are derived in [30] based onassumption of communication over Gaussian channel withoutfading, it is also appropriate for communication over fadingchannel whose CSI is not available at sender by replacing thechannel SNR with average channel SNR.
B. HDA-Relay
As shown in Fig. 2, we first consider the simplest case wherethe cooperative group has only two receivers. In WCVC, oneof HDA relay coding schemes, HDA-Relay, is adopted. HDA-Relay consists of four forwarding modes and at each time itchooses one of them according to γ1 and γ2 which are theSNRs of base layer (i.e., the ratio of the power of BPSK-modulated signals and the total power of analog and noise
6
Fig. 6. Relay mode selection region.
signals in the I component) of the blocks to be retransmittedfor T1 and T2 respectively and can be expressed as
γ1 =h21Pd
h21Pa2+N1/2
,
γ2 =h22Pd
h22Pa2+N2/2
.(13)
Without loss of generality, here we assume γ1 ≥ γ2 (i.e., theSNR of channel S-T1 is higher than the one of channel S-T2)and therefore T1 relays information to T2.
1) Amplify-and-Forward (AF): This mode is the same asthe general AF, which linearly maps the received signalto transmitted signal directly. If γ1 < ΓB
(PTE
), the
relay adopts AF mode, where ΓB
(PTE
)is defined as,
for a block the least SNR needed for T1 (without relayinformation) to guarantee that the decoding BER of thebase layer is not larger than the target BER PT
E . Thedifference between ΓB
(PTE
)and Γ
(PTE
), which is de-
fined in previous subsection, is that ΓB
(PTE
)denotes the
least SNR for a block, while Γ(PTE
)denotes the least
average SNR for averaging all blocks. The detailed relaymode selection region is shown in Fig. 6. Accordingly,if (γ1, γ2) is located in the “AF” region, the relay adoptsAF mode.
2) Digital-Code-and-Forward (DCF): In this mode, T1 de-codes the base layer information and then recodes andretransmits it to T2 by digital coding. Therefore DCF isa special decode-and-forward which only forwards baselayer information. If (γ1, γ2) is located in the “DCF”region of Fig. 6, the relay adopts this mode.
3) HDA-Code-and-Forward (HDACF): In this mode, T1decodes the base layer information and noisy enhance-ment layer, and then recodes and retransmits them to T2by HDA coding. If (γ1, γ2) is located in the “HDACF”region of Fig. 6, the relay adopts this mode.
4) Analog-Code-and-Forward (ACF): In this mode, T1decodes the base layer information and noisy enhance-ment layer, and then recodes and retransmits the noisyenhancement layer to T2 by linear analog coding. If(γ1, γ2) is located in the “ACF” region of Fig. 6, therelay adopts this mode.
From the brief introduction above, we can see that bothDCF and ACF are the special HDACF with only one layerretransmitted; in AF and HDACF modes the relay informationcontains all received information, however in DCF and ACFmodes the relay information only contains part of received
information. Next we will introduce four relay modes in detailand explain how to determine relay mode selection region.
1) Amplify-and-Forward: In this mode, the relay T1 re-ceives the signal transmitted from the sender S, and thenamplifies and retransmits it to its partner T2. Therefore, theretransmitted signal can be represented as
x1 = αy1. (14)
In addition, by the average transmitting power constraintformula (4), we have
α ≤
√P1,t
h21Pt +N1
. (15)
In order to achieve the best video quality, the power shouldbe in full use. Therefore,
α =
√P1,t
h21Pt +N1
. (16)
2) HDA-Code-and-Forward, Digital-Code-and-Forward,and Analog-Code-and-Forward: Similar to the operations ofHDA-Cast, in HDACF mode, the relay first decodes the digitalsignal “correctly”; next, it obtains the noisy analog signalby subtracting the digital signal from the received signal;finally, it recodes the digital signal and then maps it plusanalog signal into transmitted signal by HDA modulation.We assume that the FEC used in relay coding is the same asthe one used in HDA-Cast.
The similar HDA modulation as in HDA-Cast is usedin HDA-Relay part. The transmitted signal x1 is the linearsuperposition of BPSK modulated signal x1,d and the obtainednoisy analog signal x1,a, i.e.
x1 = x1,d + αax1,a,x1,a = y1 − h1xd = h1xa + n1,
(17)
where x1,d =(√
P1,dxd0, 0)
with high probability whenγ1 ≥ ΓB
(PTE
), xd0 is the normalized BPSK-modulated signal
(before power allocation is performed) at the sender S asshown in Fig. 4, and P1,d is the allocated average power tox1,d.
In order to decode the digital information correctly for T2,the power allocation at relay T1 (i.e., dividing the averageavailable power P1,t into the average power of digital signalsP1,d and the average power of analog signals P1,a) is needed.Assume that for a block, ΓB1
(PTE , γ2
)is the lowest SNR of
base layer of the relay signal needed for T2 to guarantee thatthe decoding BER of base layer is not larger than the targetBER PT
E , when the SNR of base layer of the correspondingblock at T2 is γ2. How to determine ΓB1
(PTE , γ2
)will be
explained in next subsection. Then, to guarantee that thedecoding BER is not larger than PT
E , the SNR of base layerof the relay signal γ12 should satisfy the following inequality,
γ12 =P1,d
P1,a2 +N12/2/h212
≥ ΓB1
(PTE , γ2
), (18)
where P1,a2 is the allocated average power to x1,a2, x1,a2 is Icomponent of x1,a, N12 is the average power of channel noise
7
n12, and h12 is the inter-partner channel coefficient. Obviously,it satisfies that
P1,a = P1,a1 + P1,a2,
P1,a = α2a
(h1
2Pa +N1
),
P1,a2=α2a
(h1
2Pa2 +N1/2),
(19)
where P1,a1 are the allocated average power to x1,a1, andx1,a1 is Q component of x1,a.
In addition, by the average transmitting power constraint,we have
P1,d + P1,a ≤ P1,t. (20)
By combining expressions (18)-(20), it can be deduced that
α2a ≤
P1,t − ΓB1
(PTE , γ2
)N12/
(2h2
12
)h1
2Pa +N1 + ΓB1
(PTE , γ2
) (h1
2Pa2 +N1/2) . (21)
However, α2a ≥ 0 should hold. Therefore, if the right
term of this formula is negative or zero, i.e. P1,t ≤Γ1
(PTE , γ2
)N12/
(2h2
12
), then we should set
α2a = 0,
P1,a = 0,P1,d = P1,t,
(22)
i.e., HDACF degenerates to DCF. It means that when therelay power is not sufficient, we should allocate all powerto base layer to guarantee its transmission. Otherwise, ifP1,t > ΓB1
(PTE , γ2
)N12/
(2h2
12
)> 0, in order to achieve the
best video quality, the power should be in full use. Therefore,it is reasonable to set P1,a to be the maximum.
α2a =
P1,t−Γ1(PTE ,γ2)N12/(2h2
12)h1
2Pa+N1+Γ1(PTE ,γ2)(h1
2Pa2+N1/2),
P1,a = α2a
(h1
2Pa +N1
),
P1,d = P1,t − P1,a.
(23)
If T2 can decode the base layer correctly without the help ofT1, i.e., γ2 ≥ ΓB
(PTE
), then ΓB1
(PTE , γ2
)should be zero.
In this case, HDACF degenerates to ACF. Therefore, powerallocation (23) is modified as
α2a =
P1,t
h21Pa+N1
,
P1,a = P1,t,P1,d = 0.
(24)
In the derivation above, the current inter-partner channelcoefficient h12 is an input parameter of relay coding. However,it is unknown by the relay T1 at current time, therefore,we should estimate it by its previous realization, and thenreplace h12 with it. For the slow fading case, h12 has highcorrelation among its adjacent block realization, therefore itcan be achieved by taking its previous realization as currentestimate; for the fast fading case, h12 has high randomnessamong its adjacent realization in block, therefore it can beapproximated by the root mean square of h12; as for the middlefading case, combining the above two estimation methods canbe applied.
As for multiple receivers case, similarly, the receiver withthe best sender-receiver channel acts as the relay and forwardsits received information to all the other receivers of its cooper-ative group. It can optimize the relay coding scheme according
to all its partners to guarantee as much as possible that theycan decode the base layer correctly. The corresponding HDA-Relay scheme described above is still valid by setting the relayas T1 and the worst receiver (which needs the most power forbase layer among all T1’s partners) as T2. Although by thisway the HDA-Relay scheme can be extended to the case ofmultiple receivers, it probably leads to a limited gain incurredby the cooperation, when the relay T1 is far from its partners.Therefore, to make all receivers in the group achieve the bestperformance, the selection of relay node and the correspondingrelay scheme should be well studied and designed carefully
C. HDA-Decoder
For the receivers without cooperation, it is reasonable thatthey apply HDA-Cast decoder directly. While for the receiverswith cooperation, they apply a modified version of HDA-Cast decoder, named HDA-Decoder, which adds one LMMSEestimator operation into the digital decoder and adds thereceived relay signal as another input into the analog decoder(as shown in Fig. 7). Before decoding digital information,the LMMSE estimator [33] is needed, which herein realizesnot only diversity combining (combing the multiple receivedsignals of a diversity reception device into a single improvedsignal) but also signal equalization. For different relay modes,these two LMMSE estimators in HDA-Decoder have differentparameters.
1) Amplify-and-Forward: LMMSE estimator 1: For AFmode, T2 receives signals y2 and y12, which are from thesender and the relay respectively and whose I componentscan be expressed as
y2,I = h2
{√Pdxd0 + xa2
}+ n2,I ,
y12,I = αh12
{h1
(√Pdxd0 + xa2
)+ n1,I
}+ n12,I ,
(25)
where n1,I , n2,I and n12,I denote the I components of n1, n2
and n12, respectively. Normalizing the coefficient of digitalinformation, we have
z2∆=
y2,I
h2
√Pd
= xd0 + w2,
z12∆=
y12,I
αh12h1
√Pd
= xd0 + w12,(26)
wherew2 =
n2,I
h2
√Pd
,
w12 =αh12(h1xa2+n1,I)+n12,I
αh12h1
√Pd
.(27)
The variances of w2 and w12 are
σ2w2
=h22Pa2+N2/2
h22Pd
,
σ2w12
=α2h2
12{h21Pa2+N1/2}+N12/2
α2h212h
21Pd
.(28)
According to LMMSE estimator [33], the LMMSE estimator1 can be expressed as
xd0 = β2z2 + β12z12, (29)
whereβ2=
1/σ2w2
1/σ2w2
+1/σ2w12
+1 ,
β12=1/σ2
w12
1/σ2w2
+1/σ2w12
+1 .(30)
8
Analog (MSoftCast) Decoder
Digital DecoderVideo Denoising
Demodulation
&Deinterleaving
&Decoder
H264/AVC
Decoder +Recons-
tructed
Video
- 3D-IDCT
LMMSE
Estimator
2
DemappingReceived
Signal
H264
Reconstructed
Video
Reconstructed
Residual Error
-+
FEC
&Interleaving
&Modulation
H264 Bitstream
Side Infomation
s
Video
Denoising
Denoised
Video
Auxiliary Information
( )2, 12,,a ay y
( )1,ˆ ˆ,d dx x
LMMSE
Estimator
1
( )2 12,y y
( )2, 0 12, 0,a ay y
Scaling
0ˆdx
Fig. 7. The decoder of WCVC with cooperation.
Since LMMSE estimator is also the Maximum-Ratio-Combining (MRC) [32], the corresponding SNR is
γ′2 = γ2 + γ12
=h22Pd
h22Pa2+N2/2
+α2h2
12h21Pd
α2h212{h2
1Pa2+N1/2}+N12/2.
(31)
Assume that for a block, ΓB2
(PTE
)is the lowest SNR of
base layer of the combined signal needed for T2 to guaranteethat the decoding BER of base layer is not larger than thetarget BER PT
E . Since the signal distribution and the noisedistribution of the combined signal are different from thesingle received from sender, ΓB2
(PTE
)may be unequal to
ΓB
(PTE
). To guarantee γ′
2 ≥ ΓB2
(PTE
), we have
γ12 ≥ ΓB1
(PTE , γ2
) ∆= max
(ΓB2
(PTE
)− γ2, 0
). (32)
LMMSE estimator 2: T2 subtracts the reconstructed digitalinformation from the received signals y2 and y12 to achievethe noisy analog information ya0 and y12,a0 which can beexpressed as (for k-th PAU)
y2,a0 (k) = h2 (k) g (k) s (k) + n2 (k) ,y12,a0 (k) = αh12 (k) {h1 (k) g (k) s (k) + n1 (k)}+ n12 (k) .
(33)And then similar to LMMSE estimator 1, LMMSE estimator2 can be represented as follows
s (k) = βa,2 (k) z2 (k) + βa,12 (k) z12 (k) , (34)
where
z2 (k)∆=
y2,a0(k)h2(k)g(k)
= s (k) + w2 (k) ,
z12 (k)∆=
y12,a0(k)αh12(k)h1(k)g(k)
= s (k) + w12 (k) ,(35)
w2 (k) =n2(k)
h2(k)g(k),
w12 (k) =αh12(k)n1(k)+n12(k)
αh12(k)h1(k)g(k),
(36)
with variances
σ2w2
(k) = N2/2h22(k)g
2(k),
σ2w12
(k) =α2h2
12(k)N1/2+N12/2
α2h212(k)h
21(k)g
2(k),
(37)
andβa,2 (k)=
1/σ2w2
(k)
1/σ2w2
(k)+1/σ2w12
(k)+1/σ2s(k)
,
βa,12 (k)=1/σ2
w12(k)
1/σ2w2
(k)+1/σ2w12
(k)+1/σ2s(k)
.(38)
The resulting distortion is approximately expressed as
D (k) ≈ 1
1/σ2w2
(k) + 1/σ2w12
(k) + 1/σ2s (k)
. (39)
2) HDA-Code-and-Forward, Digital-Code-and-Forward,and Analog-Code-and-Forward: LMMSE estimator 1: Thereceived signals y2 and y12, which are from the sender andthe relay respectively, can be expressed as
y2,I = h2 (k){√
Pdxd0 + xa2
}+ n2,I ,
y12,I (k) = h12
{√P1,dxd0+α (h1xa2 + n1,I)
}+ n12,I .
(40)Therefore similar to LMMSE estimator 1 for AF mode,LMMSE estimator 1 for HDACF mode can be representedas follows. Normalizing the coefficient of digital information,we have
z2∆=
y2,I
h2
√Pd
= xd0 + w2,
z12∆=
y12,I
h12
√P1,d
= xd0 + w12,(41)
wherew2 =
n2,I
h2
√Pd
,
w12 =αh12(h1xa2+n1,I)+n12,I
h12
√P1,d
.(42)
The variances of w2 (k) and w12 (k) are
σ2w2
(k) =h22(k)Pa2+N2/2
h22(k)Pd
,
σ2w12
(k) =α2h2
12(k){h21(k)Pa2+N1/2}+N12/2
h212(k)P1,d
.(43)
The LMMSE estimator 1 can be expressed as
xd0 = β2z2+β12z12, (44)
whereβ2=
1/σ2w2
1/σ2w2
+1/σ2w12
+1 ,
β12=1/σ2
w12
1/σ2w2
+1/σ2w12
+1 .(45)
And the corresponding SNR is
γ′2 = γ2 + γ12
=h22Pd
h22Pa2+N2/2
+h212P1,d
α2h212{h2
1Pa2+N1/2}+N12/2.
(46)
The formula (32) still holds in HDACF, DCF or ACF case.LMMSE estimator 2: For LMMSE estimator 2 in HDACF,
DCF or ACF case, the formulas (33)∼(39) still hold byreplacing all α with αa.
IV. WCVC PERFORMANCE ANALYSIS
A. Bandwidth Adaptation
Like SoftCast, our WCVC can accommodate to differentbandwidths by either discarding the transform coefficients inthe PAUs with the smaller variances for the channel bandwidth
9
WCVC- Enhancement Layer
Non-video
Data Layer
WCVC- Base
Layer
(a)
WCVC- Enhancement Layer
Non-video Data Layer
WCVC- Base Layer
(b)
Fig. 8. Cooperation within different services.
lower than source bandwidth case, or retransmitting the trans-form coefficients in the PAUs with the larger variances for thechannel bandwidth higher than source bandwidth case.
In addition, a more efficient approach for the channelbandwidth lower than source bandwidth case is cooperationwithin the multiple users intending different data from thesender. Assume there are two receiver groups: one intends avideo service, while the other intends a file service (non-video,which needs lossless transmission). Then in this cooperationscheme, at the sender side, the video data and the file data areencoded into multiple layers by combining WCVC and FEC insuperposition way (the highest layer is the enhancement layerof the WCVC), and then transmitted. At the decoder side, eachdecoder decodes the layer intended by itself through successivedecoding. Moreover, the file layer can be coded into either thesame layer with the base layer of WCVC as shown in Fig. 8(a), or the different layers with the base layer of WCVC asshown in Fig. 8 (b). In addition, in this cooperation scheme, theusers in different groups intending different data can naturallyrelay received information to each other. The superpositioncoding in the proposed hybrid WCVC and file transmissionscheme is just a multiplex way, which works on the data linklayer for digital part (however for analog part, it is a crosslayer design), and it does not have influence on the transportlayer or higher layer protocol. In addition, a practical systemwith superposition-coding multiplexing has been implementedon software-defined radio (SDR) recently [38] which furtherverifies the feasibility of our proposed hybrid scheme.
B. Compatibility with H.264/SVC
H.264/SVC streaming works well on wired network (e.g.,Ethernet), and our WCVC works well on (the last hop) wire-less network. Therefore combining WCVC with H.264/SVCis of considerable interest. Fortunately, both base layers ofH.264/SVC and our WCVC adopt single-layer digital coding,hence H.264/SVC and WCVC can easily be converted intoeach other by transcoding enhancement layers. Besides, a morecompatible digital video coding can be designed by directlyencoding enhancement layer of WCVC into bit-stream.
C. Complexity and Delay Analysis
At sender end, our WCVC adds the MSoftCast and theLMMSE denoising operations besides H.264/AVC Codecwith fixed modulation and LDPC coding. In addition, theLMMSE denoising only uses the linear filter with very lowcomplexity. Therefore, the main additional complexity comesfrom 3D-DCT/ 3D-IDCT operations of MSoftCast. For n-points DCT/IDCT operation, its computation complexity is
O (n log n)[39]. Thus, for WCVC, the additional computationcomplexity of one GOP is O (V log V ), where V is the numberof pixels in one GOP.
At relay end, since the operation on the enhancement layer(analog part) is scaling (computation complexity O (V )), themain complexity comes from the decoding and re-encodingthe base layer video. Furthermore, the encoding operation ofLDPC code can be done through logical operation “XOR”,hence the main complexity comes from the decoding operationof LDPC code. According to [40], the complexity of beliefpropagation (BP) decoding algorithm of LDPC code for oneiteration is O (JL), where L is the block length of theLDPC code, and J is the number of “1”s in each columnof the parity-check matrix. Moreover, if the relay has ahigh SNR channel (this is true in usual situations), the BPalgorithm needs very few the average number of iterationsto converge. In addition, since the relay is also a receiver,the decoding operation is necessary even if it does not relayany information. Therefore, compared with noncooperativecommunication case, the additional computation complexity(coming from the scaling operation on the enhancement layerand the re-encoding operation of LDPC code) is very low.Nevertheless, like DF scheme, the transmission delay incurredby relay is not ignorable, which consists of transmissiondelay and forwarding operation delay. The former is mainlydetermined by the interleaving length, since only when thewhole interleaved block has been received, it is able to startto perform the decoding operation (in our experiments, we setit to 0.27s); while the later mainly comes from the decodingoperation of LDPC code.
In addition, the proposed WCVC is able to realize fullscalability (quality scalability, spatial scalability, and temporalscalability) by replacing the HDA-Cast module with WSVCmodule in Fig.3, which turns into a wireless cooperativescalable video coding (WCSVC) scheme.
V. EVALUATION AND RESULTS
A. Reference Baselines and Testing Setup
To evaluate the performance of our proposed WCVC wecompare it with two baselines with cooperative communica-tion:
1) Layered cooperative digital scheme: H.264/SVC [36],[37] (a layered video coding) with LDPC codes andhierarchical modulation [34] (a layered channel coding),which is denoted as SVC+HM. The relay forwardsthe information it is able to decode successfully whilethe receiver is unable to decode successfully. In detail,adaptive selecting relay mode AF (the relay amplifiesand forwards all the layers that cannot be decoded byits partner) or DF is applied (when the receivers’ averagechannel SNRs are close, AF is applied; otherwise, DFis applied). Here the layered cooperative scheme isbased on superposition transmission and it is moreefficient than the one proposed in [16] which adoptslayered video compression combined with progressivetransmission. This is derived from the comparison results
10
of these two schemes in [16] for Gaussian source in thehigh SNR regime.
2) Typical cooperative analog scheme: Latest version ofSoftCast [24], [25] which uses the 3D-DCT. Sincecooperation is not considered in the original SoftCast[24], [25], therefore we extend it into a cooperative ana-log scheme by combining it with Amplify-and-Forwardscheme. Moreover, the LMMSE estimator is applied atthe receiver.
All the schemes are implemented using MATLAB. All LDPCcodes used in our experiments are constructed by ProgressiveEdge Growth [42], which have the desirable error correctioncapability, and all the decoders of LDPC codes apply soft-decision decoding.
In our experiments, we extract luminance component togenerate monochrome video sequences for test. Some rep-resentative reference video sequences [43] with resolutionCIF (352x288) frame rate 30 fps are used to conduct allthe experiments. Since in practical communication scenario,there might be both noncooperative case and cooperativecase, we realize each scheme with two modes: noncooperativemode and cooperative mode. We use them to test the perfor-mance of all the schemes in three situations: noncooperativecommunication, symmetric cooperation communication andasymmetric cooperation communication. All the schemes sendthe same power, and use the same total wireless bandwidth of1.8 MHz (for noncooperative scenario, the bandwidth of thesender-receiver channels is 1.8 MHz, while for cooperativescenario, the bandwidth of the sender-receiver channels andthe bandwidth of the inter-partner channels are both 0.9 MHz),which guarantees that nearly 3/5 of the coding coefficients canbe sent out and relayed by analog coding part for cooperativeschemes. In addition, we assume that all channels are Rayleighfading with maximum Doppler shift 10 Hz.
For the baselines, we use reference implementation availableonline. Specifically, we generate the H.264/SVC stream usingthe JSVM implementation [44], which allows us to controlthe number of layers, and we also generate H.264/AVC bit-streams by using the JSVM to encode the video with singlelayer. We use Open SVC Decoder [45] with error concealmentto decode SVC bit-streams. The error concealment is realizedin this way: when bit error is detected in enhancement layers,each pixel value of the concealed frame is copied from thecorresponding pixel of the corresponding decoded frame inlower layer. In order to achieve the best performance forH.264/AVC or SVC, both WCVC’s digital part and SVC+HMapply hierarchical B coding structure, with IntraPeriod (whichrepresents the period of I frames) being 32 and GOPsize(which represents the distance between key frames (I or Pframes)) being 8. In addition, to keep the same coding delay,both WCVC’s analog part and SoftCast set GOP size to 8.
In the implementation of our WCVC, the size of each PAUin WCVC is set to 44× 36. This means each GOP is dividedinto 512 PAUs. We realize WCVC with noncooperative mode(i.e., HDA-Cast) and cooperative mode. In noncooperativemode, we apply LDPC code with rate 0.1, and set γm = 0dBand Γ
(PTE
)= 2dB in expression (10) (this set of parameters is
obtained from our test) to guarantee PTE is less than 5.5×10−7.
This target BER further guarantees that for the test sequence(with 300 frames), the average bit error number of its bit-stream encoded by H.264/AVC (total size 1.8Mbits) is lessthan 1 on condition that the channel average SNR is 0 dB.Moreover, the higher the channel average SNR is, the smallerthe BER is However, in cooperative mode, we apply LDPCcode with rate 0.2, and set γm = 5dB, Γ
(PTE
)= 6.2dB,
ΓB
(PTE
)= 0dB and ΓB2
(PTE
)= 0dB (this set of parameters
is also obtained from our test) to guarantee PTE is less than
5.5× 10−7.We realize SVC+HM and SoftCast with noncooperative
mode and cooperative mode, respectively. For both noncooper-ative and cooperative modes of SVC+HM, we run SVC+HMwith different layer number and different modulations andLDPC code rates for each layer. For 2-layers SVC case, weencode the video with quality scalability and different coderates: in noncooperative mode base layer with BPSK and coderate 0.1, and enhancement layer with BPSK and code rate0.1 0.2 and 0.4 respectively; while in cooperative mode baselayer with BPSK and code rate 0.2, and enhancement layerwith BPSK and code rate 0.2, 0.4 and 0.8 respectively. For 3-layers SVC case, we encode the video with quality scalability:in noncooperative mode, base layer with BPSK and code rate0.1, first enhancement layer with BPSK and code rate 0.1, andsecond enhancement layer with BPSK and code rate 0.2; whilein cooperative mode, base layer with BPSK and code rate 0.2,first enhancement layer with BPSK and code rate 0.2, andsecond enhancement layer with BPSK and code rate 0.4. ForSoftCast, its side information is also needed to be transmittedlossless. However, we assume that no power is consumed forthe transmission of this part, since the data amount of theside information is very small (but this maybe lead to the testresults seems unreasonable when the channel SNR is low).We fix these parameters of SVC+HM schemes and then testthese schemes together with SoftCast and our WCVC in all thefollowing experiments. In addition, we compare the schemesin terms of the Peak Signal-to-Noise Ratio (PSNR) [41] andsubjective quality.
B. Quality Evaluation for NoncooperationAs a special case of cooperative communication, nonco-
operative communication scenario is considered here in thatthe receiver has no cooperative partners, i.e., the cooperativegroup has only one receiver. Since it is a communicationscenario that might arise, the performance for noncooperativecommunication is also an important evaluation indicator.Method: For noncooperative video quality comparison, werun a group of simple noncooperative unicast experimentswith a receiver, whose channel is Rayleigh fading with fixedaverage SNR, for different schemes: SVC+HM, SoftCast andour WCVC. For each experiment, all the schemes are testedat same average SNR, and we conduct a group of suchexperiments under different average SNR. We set the workingSNR range of all schemes is 0∼ 25 dB, and to exhibit thecliff effect, we set the measurement of SNR with a span from-2 to 25 dB.Results: The PSNR curves of the reconstructed videos withdifferent schemes for the Foreman sequence are shown in
11
(a)
Fig. 9. Video PSNR comparison of different schemes for noncooperationscenario, test sequence: Foreman.
Fig. 9. In addition, the 5-th frame of reconstructed Foremansequence by each scheme at average SNR 5 dB is shown inFig. 12 From Fig. 9, it can be concluded:
1) It shows that WCVC is average 0.6 ∼ 8.7 dB and 1.1∼ 4.6 dB better than SoftCast and the SVC+HM with3-layers respectively within the working SNR range 0 ∼25 dB. For SVC+HM schemes with 2-layers as well aswith different modulations and channel code rates, theconclusion similar to that for SVC+HM with 3-layerscan be drawn. In a word, WCVC has higher codingefficiency than SoftCast and SVC+HM;
2) It shows that within the working SNR range 0 ∼ 25dB the PSNR of WCVC varies gracefully with channelSNR varying, whereas the PSNR curve of SVC+HMsuffers from staircase effect; therefore WCVC providesbetter fairness among all the receivers in video broadcastscenario and possesses better Quality Scalability thanSVC+HM.
Fig. 12 shows that compared with SVC+HM the recon-structed video by WCVC has less blocking artifacts, andcompared with SoftCast, it has less analog noise. Therefore,among these three schemes, WCVC has the best visual quality.
C. Quality Evaluation for Cooperation: Symmetric Case
Method: For cooperative video quality comparison, we set thecommunication scenario as shown in Fig. 2 where all channelsare Rayleigh fading with fixed average SNR Moreover we setSNR1 = SNR2 = γ and SNR12 = 15dB. Then we run agroup of cooperative communication experiments for differentschemes: SVC+HM (AF is adopted), SoftCast and our WCVCFor each experiment, all schemes are tested at same γ, and weconduct a group of such experiments under different γ.Results: The PSNR curves of the reconstructed videos withdifferent schemes for the Foreman sequence are shown in Fig.10 (a) and the video PSNR comparison of noncooperativemodes and cooperative modes of different schemes for sym-metric communication scenario is shown in Fig. 10 (b). Inaddition, the 5-th frame of reconstructed Foreman sequenceby each scheme at average SNR 5 dB is shown in Fig. 13From Fig. 10, it can be concluded:
1) Fig. 10 (a) shows that for symmetric cooperation,WCVC is average 0.8∼ 9.0 dB and 0.8 ∼ 4.6 dB better
than SoftCast and the SVC+HM with 3-layers respec-tively within the SNR range -1∼ 25 dB. For SVC+HMschemes with 2-layers as well as with different modu-lations and channel code rates, the conclusion similarto that for SVC+HM with 3-layers can be drawn. In aword, WCVC has higher coding efficiency than SoftCastand SVC+HM for symmetric cooperation scenario;
2) Fig. 10 (a) also shows that similar to the noncooperationcase, within the SNR range -1∼ 25 dB the PSNR ofWCVC varies gracefully with channel SNR varying,whereas the PSNR curve of SVC+HM suffers fromstaircase effect; therefore WCVC provides better fairnessamong all the receivers and possesses better QualityScalability than SVC+HM in symmetric cooperationscenario;
3) Fig. 10 (b) shows that compared with the noncooperationcase, cooperative SoftCast almost achieves the sameperformance, and cooperative WCVC and cooperativeSVC+HM are more robust (at channel SNR below 15dB) Therefore it seems that in symmetric communi-cation case, when the inter-partner channel is goodenough, cooperation does not have influence on thereconstructed video PSNR for analog coding schemes;while it makes the digital coding schemes more reliable.This is true, because in cooperative communication, itreceives and combines two independent fading signals(which is cooperative diversity), while in noncoopera-tive communication, it receives a double-length time-dependent fading signal (which can be seen as timediversity); on the other hand, in SoftCast or analogpart of WCVC, it does not utilize knowledge of thechannel fading, but independently processes (scales andestimates) each transform coefficient, while in SVC+HMor digital part of WCVC, the cooperative diversitycan mitigate channel fading more effectively than timediversity when inter-partner channel is good enough.In addition, although for all schemes the cooperativeperformance is similar to the noncooperative one, incooperative communication, the sender saves half of thetotal power consumed in the noncooperative case sinceit sends data only for half of the time slots occupied inthe noncooperative case (of course, the relay consumesmore power than the one of the noncooperative case).Therefore, if the total power of the sender is constrained,then the cooperative performance will outperform thenoncooperative one.
Fig. 13 shows that similar to the noncooperation case, insymmetric cooperation scenario, compared with SVC+HM thereconstructed video by WCVC has less blocking artifacts, andcompared with SoftCast, it has less analog noise. Therefore,among these three schemes, WCVC has the best visual quality.
D. Quality Evaluation for Cooperation: Asymmetric Case
Method: For cooperative video quality comparison, we set thecommunication scenario as shown in Fig. 2 where all channelsare Rayleigh fading with fixed average SNR. Moreover weset SNR1 = SNR2+10dB and SNR12 = 15dB. Then we
12
(a)
(b)
Fig. 10. (a) Video PSNR comparison of different schemes for symmetriccooperation, and (b) video PSNR comparison of noncooperative modesand cooperative modes of different schemes for symmetric communicationscenario, test sequence: Foreman.
run a group of cooperative communication experiments fordifferent schemes: SVC+HM (DF is adopted), SoftCast andour WCVC. For each experiment, all schemes are tested atthe same SNR2, and we conduct a group of such experimentsunder different SNR2.Results: The PSNR curves of the reconstructed videos withdifferent schemes for the Foreman sequence are shown in Fig.11 (a) and the video PSNR comparison of noncooperativemodes and cooperative modes of different schemes for asym-metric communication scenario is shown in Fig. 11 (b). Toshow the robustness incurred by cooperation, we set SNR2from -10 to 25 dB, although the very low channel SNR seemssomewhat unreasonable in practice In addition, the 5-th frameof the reconstructed Foreman sequence by each scheme ataverage SNR 5 dB is shown in Fig. 14 From Fig. 11, it canbe concluded:
1) Fig. 11 (a) shows that for asymmetric cooperation,WCVC is average .9∼ 8.3 dB and 0.7 ∼ 5.4 dB betterthan SoftCast and the SVC+HM with 3-layers respec-tively within the SNR range 8∼ 25 dB. For SVC+HMschemes with 2-layers as well as with different modu-lations and channel code rates, the conclusion similarto that for SVC+HM with 3-layers can be drawn. In aword, WCVC has higher coding efficiency than SoftCastand SVC+HM for asymmetric cooperation scenario;
2) Fig. 11 (a) also shows that similar to the noncooperationand symmetric cooperation cases within the SNR range8∼ 25 dB the PSNR of WCVC varies gracefully withchannel SNR varying, whereas the PSNR curve ofSVC+HM suffers from staircase effect; therefore WCVC
(a)
(b)
Fig. 11. (a) Video PSNR comparison of different schemes for asymmetriccooperation communication, and (b) video PSNR comparison of noncoopera-tive modes and cooperative modes of different schemes for asymmetriccommunication scenario, test sequence: Foreman.
provides better fairness among all the receivers andpossesses better Quality Scalability than SVC+HM inasymmetric cooperation scenario;
3) Fig. 11 (b) shows that compared with the noncooperationcase, all cooperative schemes achieve remarkably superi-or performance. In asymmetric communication case thecooperation gain (denotes how much the transmissionpower can be reduced when a cooperative scheme isintroduced, without a performance loss) of SoftCast islarger than the ones of WCVC and SVC+HM, whenchannel has a low average SNR; while it is smaller thanthe ones of WCVC and SVC+HM, when channel has ahigh average SNR.
Fig. 14 shows that similar to the previous conclusions, inasymmetric cooperation scenario, compared with SVC+HMthe reconstructed video by WCVC has less blocking artifacts,and compared with SoftCast, it has less analog noise. There-fore, among these three schemes, WCVC has the best visualquality.
VI. CONCLUSION
In this paper, we propose a novel HDA-based wireless co-operative video coding (WCVC) framework. Specifically, wepresent a HDA cooperative joint source-channel coding (JSC-C) scheme that integrates the advantages of digital coding andanalog coding—high coding efficiency and graceful qualityvariation with channel variation. The performance evaluationshows that (1) for noncooperation scenario, our WCVC hasaverage 0.6 ∼ 8.7 dB and 1.1 ∼ 4.6 dB performance gainover SoftCast and SVC+HM respectively; (2) for symmetric
13
(a) SoftCast (b) SVC+HM
(c) WCVC (d) Original
Fig. 12. The 5-th frame of the reconstructed video comparison for noncoop-eration with average SNR 5 dB, test sequence: Foreman.
(a) SoftCast (b) SVC+HM
(c) WCVC (d) Original
Fig. 13. The 5-th frame of the reconstructed video comparison for symmetriccooperation with average SNR 5 dB, test sequence: Foreman.
cooperation scenario, our WCVC has average 0.8∼ 9.0 dB and0.8 ∼ 4.6 dB performance gain over SoftCast and SVC+HMrespectively; (3) for asymmetric cooperation scenario, ourWCVC has average 0.9∼ 8.3 dB and 0.7 ∼ 5.4 dB per-formance gain over SoftCast and SVC+HM respectively; (4)our WCVC avoids the staircase effect and realizes CQS oncondition that the channel quality is within the expected rangeTherefore, the proposed WCVC is very suitable for wirelesscooperative video broadcast/multicast and cooperative mobilevideo applications.
(a) SoftCast (b) SVC+HM
(c) WCVC (d) Original
Fig. 14. The 5-th frame of the reconstructed video comparison for asymmetriccooperation with average SNR 5 dB, test sequence: Foreman.
ACKNOWLEDGMENT
The authors would like to thank Intel Collaborative Re-search Institute for Mobile Networking and Computing (ICRI-MNC) for providing funding to partially support this work.
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Lei Yu received the B.E. degree in electronic infor-mation engineering from the University of Scienceand Technology of China, Hefei, China, in 2010. Heis now pursuing the Ph.D. degree at the Universityof Science and Technology of China.
His research interests include image/video codingand communication, and theory and practice of jointsource-channel coding (JSCC).
Houqiang Li (S’12) received the B.S., M.Eng., andPh.D. degrees in electronic engineering from the U-niversity of Science and Technology of China, Hefei,China, in 1992, 1997, and 2000, respectively, wherehe is currently a Professor with the Department ofElectronic Engineering and Information Science.
His research interests include video coding andcommunication, multimedia search, image/videoanalysis. He has authored and co-authored over 100papers in journals and conferences. He served as anAssociate Editor of the IEEE TRANSACTIONS ON
CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY from 2010 to2013, and has been with the Editorial Board of the Journal of Multimedia since2009. He was a recipient of the Best Paper Award for Visual Communicationsand Image Processing Conference in 2012.
Weiping Li (F’00) received his B.S. degree fromUniversity of Science and Technology of China(USTC) in 1982, and his M.S. and Ph.D. degreesfrom Stanford University in 1983 and 1988 respec-tively, all in electrical engineering. He was an As-sistant Professor, Associate Professor with Tenure,and Professor of Lehigh University from 1987 to2001. He worked in several high-tech companies inthe Silicon Valley with technical and managementresponsibilities from 1998 to 2010. He has been aProfessor in USTC since 2010. He served as the
Editor-in-Chief of IEEE Transactions on Circuits and Systems for VideoTechnology, a founding member of the Board of Directors of MPEG-4Industry Forum, and several other positions in IEEE and SPIE. He is anIEEE Fellow.
