[IEEE 2013 International Symposium on Ocean Electronics (SYMPOL) - Kochi, India (2013.10.23-2013.10.25)] 2013 Ocean Electronics (SYMPOL) - Design aspects of signal waveform for underwater

PROCEEDINGS OF SYMPOL-2013

A.Sambasiva Rao et al.: Design aspect of Signal waveform for underwater acoustic Communication system

DESIGN ASPECTS OF SIGNAL WAVEFORM FOR UNDERWATER ACOUSTIC COMMUNICATION

SYSTEM 1A. Sambasiva Rao, 2M. Srinivasa Rao, 3Dr S. Koteswara Rao, 4Dr A .M. Prasad

1 Scientist-C, NSTL, Visakhapatnam [email protected]

2 Scientist-E, NSTL, Visakapatnam [email protected] 3 Senior Professor&Prinisipal, Vignan Institute o of Engineering for womenen, Visakhapatnam

[email protected]

4 Associate Professor, JNTU, Kakinada [email protected]

Abstract: - The underwater acoustic channel belongs to a complicated class of stochastic communication channels, which are frequency and energy (at long range) limited and time-frequency doubly spread. Underwater acoustic data telemetry is a taxing problem because many unique channel characteristics such as fading, extended multipath, retroactive properties of sound channels preclude direct applications of classical communication techniques. For such channels Channel identification, channel tracking and optimum linear decoding will be the approach in order to solve the problems of communication over a possible doubly spread channel. This paper describes a reliable mechanism and signal design for underwater sensor node.

I. INTRODUCTION:

There is a well established need for

data transmission through underwater. The need for underwater wireless communications exists in a broad range of applications. The possibility to maintain signal transmission enables gathering of data from submerged instruments without human intervention, and unobstructed operation of unmanned or autonomous underwater vehicles (UUV’s , AUV’s) are different types of communications.

The fundamental requirement to use in

dense underwater sensor network is an inexpensive acoustic modem. Commercial under water acoustic modems that do exist were designed for sparse, long range applications rather than for small dense sensor networks.

The design of a robust under water communication system presents several challenges that are unique. The successful design of such a system has to strike a balance /compromise between relatively small bandwidth, low power requirements, error free modulation and demodulation schemes and above all range dependent data rates that the system will have to operate on. The acoustic communication system requirements are tabulated below.

System Requirement

Data rate Bit error rate

Command and control signals

Upto 1kbs Low bit rate

Telemetry data 1~10’s kbps 10-3 to 10-4 Video transmission

10~100’s kbps

10-3 to 10-4



Selection of communication technique for design of acoustic modem can be structured roughly into three levels viz Channel characteristics and modelling, selection of Communication concepts and techniques and application of these concepts in a system context. A wireless communication engineer should have an understanding of the concepts at all three levels as well as the tight interplay between the levels.

This paper reviews modulation signal techniques for underwater acoustic communication. Authors propose usage and definition of communication signals that perform well in all environmental condition and use of good signal processing techniques in the receiving end taking into account the characteristics of the signal and perturbations in the medium. II. Modulation techniques for Underwater Acoustic Communication system: The performance of phase coherent signalling degrades rapidly under severe channel distortion whereas the non-coherent FSK/CSK is more robust. In the current implementation, the parameters of the communication link such as frequency band of operation, modulation scheme, modem output power, and error correction coding types are determined prior to deployment. The apriori choice of signalling parameters tends to be overly conservative and non-optimal. The variations in the properties of the acoustic channel suggests that a more appropriate way to deal with these communication parameters is to be determined dynamically. It is also required to determine the optimal combination of these parameters for a communication

scheme. This means that the signalling parameters can change for each exchange of data between two nodes, depending on the existing characteristics of the channel. As a result, the link would use the communication scheme with the highest possible data rate and the minimum possible probability of error (probably on the order of 10-5). In the same view, the link would use the most appropriate frequency band and transmit the minimum required amount of power. The literature refers to this technique as adaptive modulation.

There are many different types of signals used for underwater acoustic communication. These includes CSK, QPSK, OFDM and DSSS. The adaptive modem can ideally switch between any of these modulation schemes. A major component of an adaptive modem is the ability to change aspects of the modem including selecting a modulation scheme, the data rate, the transmit power and other configurable portions of the design. Many of these depend upon current and future characteristics of the acoustic channel. Therefore channel estimation is an important part of any adaptive modem. The Doppler shift, channel path gains and SNR are some of the important channel state information that must be measured and predicted. III. Signal Processing For acoustic communication:

Digital data can be represented by the slope of chirp signals. In the simplest binary case, an ‘up’ chirp (i.e., a signal with instantaneous frequency that linearly increases with time) represents a ‘1’ and a ‘down’ chirp represents a ‘0’. Higher-dimensional constellations can easily be obtained by using a larger number of up/down slopes. The wide bandwidth should provide immunity from signal degradation in the channel. Chirp signals in digital communication use a pair of linear chirps that have opposite chirp rates for binary signaling. Binary chirp signals, called linear frequency sweeping (LFS), are preferred to frequency-shift-keying (FSK) and phase-shift-keying



(PSK) in coherent channels. In non-coherent channels LFS was considered less appealing because of the requirement for a phase recovery system. At the receiver, the primary task is to achieve time synchronization. This is done by matched filter technique i.e., filtering the received waveform with the frame synchronization pulse. Once the time synchronization is achieved, the received waveform is divided into symbols and is applied to two matched filters, each corresponding to the up chirp and down chirp signals that constitute the symbols transmitted. The outputs of the matched filters are then compared and decision regarding the transmitted bit is taken based on which of the matched filters have a higher output. This decoded message can be suitable for command, control activities of underwater devices.

Another modulation scheme i.e., Direct

Sequence Spread Spectrum (DSSS) is the most common version of spread spectrum in use today, due to its simplicity and ease of implementation. In DSSS, the carrier (data signal) is multiplied by the PN (Pseudo Noise) code sequence, which is of a much higher frequency than the desired data rate. Let “ f “ be the frequency of the data signal, with appropriate pulse time T=1/f. Let the PN sequence be transmitted at a rate fc, so that the increase in the data rate is fc / f. The frequency fc is known as the chipping rate with each individual bit in the modulating sequence known as a chip. Thus the width of each pulse in the modulated sequence is TC , or a chip time. The PN sequence is designed such that it has very good autocorrelation properties. When the signal is correlated with the PN sequence at the receiver, the received signal will be recovered exactly.

The QPSK modulator chooses between the

two symbols. The modulated waveform is appended with a synchronizing pulse which is a chirp signal and then it is transmitted. At the receiver, the primary task is to achieve time synchronization. This is done by matched filtering the received waveform with the frame synchronization pulse. Once the time

synchronization is achieved, the received waveform is divided into symbols and is then applied to QPSK demodulator with adaptive equalizer to estimate transmitted symbols. Underwater acoustic telemetry channels are characterized as under spread i.e. the product of multipath spread and Doppler spread is less than unity. For such channels, adaptive equalization provide means for combating inter symbol interference (ISI) arising from time dispersive characteristics of the channel and allows to make efficient use of available channel bandwidth. An Equalizer within a receiver compensates for the average range of expected channel amplitude and delay characteristics. Equalizers must be adaptive since the channel is generally unknown and time varying.

Another promising solution for underwater

communications is the orthogonal frequency division multiplexing (OFDM), which is particularly efficient when noise is spread over a large portion of the available bandwidth. OFDM is frequently referred to as multicarrier modulation because it transmits signals over multiple sub-carriers simultaneously. In particular, sub-carriers that experience higher SNR are allotted with a higher number of bits, whereas less bits are allotted to sub-carriers experiencing attenuation, according to the concept of bit loading, which requires channel estimation. Since the symbol duration for each individual carrier increases, OFDM systems perform robustly in severe multi-path environments, and achieve a high spectral efficiency.

Channel coding improves the small-scale

link performance by adding redundant data bits in the transmitted message so that if an instantaneous fade occurs in the channel, the data rate may still be recovered at the receiver. At the base band portion of the transmitter, a channel coder maps the user’s digital message sequence into another specific code sequence containing a greater number of bits than originally contained in the message. The coded message is then modulated for transmission in the wireless channel. Channel coding is used by



the receiver to detect or correct some (or all) of the errors introduced by the channel in a particular sequence of message bits. Because decoding is performed after the demodulation, portion of the receiver coding can be considered to be a post detection technique.

Diversity plays a critical role in combating fading in Rayleigh fading channel. Multiple versions of same signal may be transmitted and /or received and combined in receiver. This significantly improves quality of received signal. Diversity implies the receiver is provided with multiple copies of transmitted signal. The multiple signal copies would experience different degree of fading in wireless channel. Signal replicas received would have different delays and phase factors at the receiver. These different replicas are spaced sufficiently apart so that they can be distinguished. They experience independent level of fading and they can be used to exploit multipath diversity. Receiver structures such as rake receiver in CDMA and equalizers such as Maximum likelihood sequence estimators in TDMA system provide multipath diversity.

IV. Design of sensor node For Underwater wireless sensor Network:

The objectives of underwater wireless sensor network are to provide effective reconnaissance of coastal lines, gathering of information about ships, submarines and marine vehicles, effective control / monitoring and decision making capability during war time as well as during peace time and effective control of coastal lines against terrorism. Data from all the sensors in the sensors network is collected at one point (Data Fusion) and after processing of the data decision can be taken by the monitoring station. Total decision making on the data collected will be under the centrally operating point.

The need for underwater wireless

communications exists in applications such as remote control in off-shore oil industry, pollution monitoring in environmental systems,

collection of scientific data recorded at ocean-bottom stations, speech transmission between divers, mapping of the ocean floor for detection of objects, Distributed systems-communication among Unmanned Underwater Vehicle (UUV) platforms and central nodes, Data ex-filtration for remote passive surveillance etc.

The underwater sensor node is basically meant for collecting data from various sensors and digitizing it. The digitized data is transmitted to the on-shore through the acoustic telemetry link. The sensors convert a physical stimulus to be measured into an electrical signal and thus operates as the actual measuring instrument. Sensor nodes form a network to cooperatively monitor large complex physical environment. Sensor nodes reconnaissance can be done by integrating with ad-hock wireless sensor networks using Autonomous underwater vehicle. A robust and intelligent defensive underwater sensor nodes will be required for surveillance. Sensor interfacing circuit should interface sensor to data acquisition system of sensor node. Data acquisition system captures frequencies of interest from the sensor data and would provides enough amplification. The telemetry system has to handle more than one channel of information. These data measurement channels are brought together by multiplexing the channels into one composite signal for transmission over the communications link.

Design of efficient Medium Access Control

(MAC) Protocols are critical for Wireless sensor Networks applications to Connectivity, Reliable monitoring of Sensing region, minimizing the collision and maximizing the Energy efficiency. The key distinguish aspects of the Underwater wireless sensor compared to regular networks is limited power and processing capabilities of sensor node. Multi hop nature of WSN needs to be exploited to improve connectivity.

The link layer provides mechanisms for the reliable transfer of information through a physical link. Even when in an energy-conserving sleep state, nodes are capable of receiving utility packets that perform functions



such as link establishment, automatic repeat request, node-to-node ranging, and return receipts. Future link layer capabilities will support adaptive modulation and network

initialization functions. Mobile nodes have unique issues in maintaining connectivity within sensor network.

Figure 1: Block diagram of sensor node

Lots of sensors are distributed over wide area. Each sensor collects the local information. Total local information is very large. Sending the data to a powerful processor, processing the data and then sending the parameter of the environment to the individual sensor needs much of communication. So, there is need of efficient power in every sensor node. Aim is to design a technique so that they will communicate among themselves and every individual will process their data to get the global solution. V. Discussions on Simulation results:

The channel model can be simulated by providing given channel geometry parameters likes Transmission delays and distances, Attenuation coefficients, Reflection losses, Ambient noise and other physical parameters like temperature, wind speed and salinity of the water etc.

These parameters taken as the inputs to the underwater acoustic channel impulse response

simulator which in turn provides us with the impulse function of the underwater acoustic channel On convolution with the signal generated from the signal generator it gives us the signal which will effect by the artificial channel. Hence the effect of the artificial channel is studied Under water acoustic channel model was developed in matlab and performance of modulation techniques such as FSK, Chirp slope keying, QPSK modem with adaptive equalization techniques has been carried out.



Fig 2: Simulation of CSK Modulation in MATLAB

Figure3:Simulation of Adaptive equalization

VI. CONCLUSION AND FUTURE SCOPE OF WORK:

It was simulated that received signal has been perfectly demodulated can conclude that CSK Modem is useful under low baud rate command and control signals. For high baud rates, DSSS modulation scheme with BPSK technique and QPSK Acoustic Modem with Adaptive equalizer for time varying under water acoustic communication channel, which allows the system to reduce complexity and increase robustness in time-variant underwater environments is studied and is simulated in MATLAB From which it can conclude DSSS and QPSK are useful for high baud rate and high range conditions. To improve transmission quality in future we can use techniques and algorithms such as Orthogonal Frequency Division Multiplexing (OFDM) with Multiple Input-Multiple Output (MIMO) so as to increase the throughput value and reliability of the modem.

VII. ACKNOWLEDGEMENT:



Our sincere thanks to S.V. Ranga Rajan, Director, Naval Science and Technological Laboratory for his encouragement and support in bringing out this paper. Thanks are also due to Shri S.Raja Scientist-G of NSTL for his encouragement in bringing this paper. The authors sincerely acknowledge the contributions made by other team members. VIII. REFERENCES: [1] D.B. Kilfoyle, A.B. Baggeroer, The State of the Art in Underwater Acoustic Telemetry, IEEE

Journal of Oceanic Engineering, vol.25, no. 1, pp. 4-27, Jan 2000. [2] Designing an Adaptive Acoustic Modem for Underwater Sensor Networks Lingjuan Wu,

Jennifer Trezzo. [3] A. Swami, q. Zhao, y-w. Hong, l. Tong “Wireless Sensor Networks: signal Processing And

Communications Perspective”, Willey. [4] Communication Performance Of Under-sea Acoustic Wide Area Network- Hannah A.

Kriewaldt, NAVAL POSTGRADUATE, School Monterey, California. [5] Underwater Acoustic Communications And Networking: Recent Advances And Future

Challenges - Mandar Chitre Shiraz Shahabudeen, Acoustic Research Laboratory, National University Of Singapore & Milica Stojanovic, Massachusetts Institute Of Technology.

Documents

[IEEE 2013 International Symposium on Ocean Electronics (SYMPOL) - Kochi, India (2013.10.23-2013.10.25)] 2013 Ocean Electronics (SYMPOL) - Design aspects of signal waveform for underwater