SCAVENGE NEWSLETTER NO. 2

H2020 SCAVENGE (http://www.scavenge.eu/)

Funded by the EU in the framework of the H2020 Marie Skłodowska Curie Action - Innovative Training Networks.

1. Call: H2020-MSCA-ITN-20152. Acronym: SCAVENGE (project No. 675891)3. Duration: 48 months4. Start date: 2016-02-015. Project Coordinator: Paolo Dini - CTTC6. Project Officer: Nina Poumpalova - REA

scavengesustainable cellular networks harvesting ambient energy

SCAVENGENewsletter No. 2

In This Issue• Getting up to speed• Training schools• Stay in touch with us• News from the students

Our partners

SCAVENGE newsletter no. 2

Getting up to speed

With 2017, SCAVENGE has been getting up to speed. Our ESRs are growingstronger, they have started to publish their first research papers and manymore are on the way. An updated list of papers is available through thefollowing link: SCAVENGE publications.

The students also gave their first talks at international conferences such as ICC,WoWMoM, GLOBECOM, WCNC, PIMRC, etc. and developed some friendshipamong them, they are a team now and we are proud of them.

Training schools

In 2017, three training schools have been organized:

• School 1: 5G cellular networks and Internet of Things (March 27th,30th, 2017, Imperial College, London, UK).

• School 2: Energy Generation and Storage: the case of Energy Har-vesting in Mobile Networks (May 29th, June 2nd, 2017, University ofStrathclyde, Glasgow, UK).

• School 3: New scenarios for 5G Mobile Networks: Smart City, SmartGrid, Public Protection and Disaster Relief (July 2nd - 7th, 2017, Univer-sity of Padova, Bressanone/Brixen, Italy).

We believe the schools have all been very successful, in general featuringthree types of lessons on: 1) mobile communication systems, 2) energy manage-ment and smart grids, 3) fundamental theoretical tools such as optimization,machine learning, convex programming, etc. All the schools have been verywell received by our students, who provided excellent feedback in terms oforganization and usefulness. Being open, and being their participation freeof charge, we have also had the pleasure of teaching to (sometimes many)non-SCAVENGE students. A proof of that is provided by the picture below,which was taken during the school in Brixen :-)

Stay in touch with us

The perhaps easiest and most enter-taining way to see what’s going on isthrough our You Tube channel.

There, you can find the lessons fromour first three schools and much more,including:

• Promo videos,• Video lessons & tutorials,

• News from our students,• Our technical achievements,• Talks to public events, etc.

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Contact Information:SCAVENGE ITNhttp://www.scavenge.euEmail: paolo.dini@cttc.es

News from the students

Ibrahim Fawaz (ESR01)

As the wireless mobile communica-tions are witnessing unprecedentedgrowth, the future 5G networks willhave to satisfy the demands onhigh-volume data traffic and at thesame time strong requirements onthe latency, error rates and energyconsumption. Focusing on resourcescheduling algorithms, I proposed, asa first step, to minimize the consumedenergy while taking into account anew constraint related to the latency.The idea is to introduce a strict de-lay constraint to guarantee that allthe data packets are scheduled beforean application-specific deadline. Inthis context, a power-efficient trans-mission strategy is designed to guar-antee reliable and sustainable com-munications. As an extension to thiswork, I investigated an energy har-vesting communication system meet-ing such strict delay constraint. Inthis case, the optimal policy shouldadapt the transmission rate to the ran-domness of the energy harvested fromthe surrounding environment in a wayto prevent energy shortage. Then,offloading capabilities are added tothe system, where the mobile termi-nal can choose to execute its taskslocally using his own processor, orremotely by offloading a part of thetasks to nearby servers or base sta-tions with more energy and computa-tion resources. Working within CEApremises and being a part of the LSCgroup (Communicating Systems Lab-oratory) offers me a unique opportu-nity to experience a professional re-search environment. It is also a greatopportunity to understand theoreticaland implementation aspects of mobilesystems.

Filipe Conceição (ESR02)

With 5G, cellular connectivity willprovide access to a great variety ofnetwork-enabled things which inter-act with one another. However, 5Gapplications will require much morefrom the network in terms of secu-rity/privacy, coverage availability, re-liability and energy savings. Thiscalls for clever cooperation strategiesamong end devices and my project atCEA aims at investigating approachesto do this. So far, I have proposed anew operating mode for Machine TypeCommunications that is characterizedby human controlled devices connect-ing directly to IoT devices. I also pro-vided a new secure method that canestablish these connections withoutany prior trust relationships and un-der the supervision of the network,meeting all the requirements of cur-rent security and telecom standards. Ithen used the proposed method alongwith the ProSe standard and intro-duced a layout for coverage exten-sion using D2D. This led to a con-ference paper entitled “Security Es-tablishment for IoT Environments in5G: Direct MTC-UE Communications”which was presented at PIMRC 2017,in Montreal, Canada, in October 2017.As direct connections have a great po-tential in energy efficiency, I am cur-rently exploring areas where energycan be saved and energy efficiency canbe improved. My current approachis to look at one IoT object and itsenergy consumption while interactingwith its neighbor nodes. I am trying toquantify this energy and demonstratethat it can be saved if the devices areable to choose wisely with whom tocooperate.

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OutlineOur vision

• Energy sustainability is keyto future mobile networksdue to their foreseen capac-ity upsurge.

• SCAVENGE introduces theconcept of Sustainable 5GMobile Network.

• Environmental energy canbe used to power the mo-bile system elements likebase stations, mobile termi-nals, sensors and machines.

Our mission

• SCAVENGE’s objective isto create a training net-work for early-stage re-searchers (ESRs) who willcontribute to the designand implementation of eco-friendly and sustainablenext-generation 5G nets.

• SCAVENGE encompassestheory along with the op-timisation and proof-of-concept implementation ofbase stations and mobile el-ements as well as their inte-gration with the smart elec-trical grid.

Our team

• The attitude of SCAV-ENGE’s industrial partnerstowards the strong invest-ment in R&D and theirstrategic vision are fullyaligned with the mission ofthis project.

• The ESRs will have aunique opportunity to-wards professional growthin light of dedicatedcross-partner trainingactivities and throughthe interaction with theinternational PartnerOrganisations, which alsoinclude relevant stake-holders in the envisionedmarket.

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Hoang Duy Trinh (ESR03)

Understanding the huge amount ofinformation that is exchanged in themobile network, can help improve thesystem in terms of communicationperformance and energy efficiency.My project aims to deliver mobile net-work solutions studying datasets thatcome from the network and from themobile users. The reason behind thefocus on data analytics is motivated bythe fact that, nowadays, the growth ofmost businesses is data-driven: thus,collection, manipulation and deepanalysis of data are fundamental skillsto be developed. Within the contextof SCAVENGE, in 2017 we collected ahuge amount of traffic datasets frommobile users, using a tool that isable to capture the control channelof LTE networks. We did this uti-lizing a software-defined radio andopen-source algorithms. We analyzedthe measurements, trying to under-stand how much efficiently the re-sources are allocated among the users.We are now able to identify recur-rent patterns, but also unexpectedtraffic upsurges due to exceptional lo-cal events. Working with large chunksof data demands for fast and effi-cient algorithms. Underlying struc-tures and hidden features can be dis-covered using artificial intelligencetechniques and machine learning al-gorithms that show good abilities insolving these problems. Neverthe-less, adapting existing machine learn-ing algorithms, which are mostly ap-plied to images and computer vision,to the telecommunication field, is anon-trivial endeavor. To help us deal-ing with this, the SCAVENGE networkhas organized schools and other train-ing events, which provided me witha good set of skills. Likewise, the sec-ondments are giving me the chanceof growing technically with the helpof other important institutions. In mycase, the hosting period at Universityof Maryland, has given me the unique

opportunity to work with ProfessorUlukus. The scope of the work we car-ried out together is to combine differ-ent datasets and study the problem ofnetwork energy efficiency from a the-oretical standpoint. Much work is stillahead of me, but I am very excited tocontinue and tackle data-driven learn-ing challenges for 5G networks.

Dagnachew Temesgene (ESR04)

In 2017, my first main task hasbeen to carry out a state-of-the-artreview, exploring recent advance-ments in Software Defined Network-ing (SDN), Network Function Virtu-alization (NFV), Machine Learning,Network Slicing and Energy Harvest-ing. The application of these conceptsand tools to the Radio Access Net-work and the resulting architectureswere surveyed. Moreover, the train-ing schools were also very helpful asthey provided lectures and hands onexperience on these topics. The find-ings from the literature survey havebeen published in an IEEE Access ar-ticle entitled “Softwarization and Op-timization for Sustainable Future Mo-bile Networks: A Survey”. This pa-per presents the interplay among soft-warization, optimization and energyharvesting, as the pillars of sustain-able mobile networks, and identifiesopen research challenges that requirefurther investigation. Besides, basedon the identified open issues, thestudy of optimal placement of func-tional split options for the scenario ofenergy harvesting virtual small cellsis being carried out. I am currentlyformulating the related optimizationproblem and solving it by applyingdynamic programming, shortest pathsearch in particular. A paper with thedescription of the approach and sim-ulation results has been submitted toIEEE ICC 2018. These results alsoserved as a basis for our contributionto the WP4 deliverable 4.1. Addition-ally, a contribution on energy harvest-ing technologies, energy storage de-

vices and base station power consump-tion has been made to the WP2 deliv-erable D2.1. In the future, I am plan-ning to extend the current dynamicprogramming based solution to sce-narios involving more energy harvest-ing virtual small cells and to comparethe algorithm’s performance againststatic configurations. Finally, apply-ing approximate optimization toolssuch as reinforcement learning for thesame optimization problem is part ofmy future research plan.

Nicola Piovesan (ESR05)

I have begun my work in SCAVENGEby working on a survey paper aboutarchitectures and paradigms for fu-ture mobile networks. In this paper,we reviewed the literature about en-ergy saving techniques, energy coop-eration between base stations and en-ergy trading with the smart electric-ity grid. This gave me the oppor-tunity to study existent works andidentify open issues. Currently, I aminvestigating the problem of the in-creased power consumption due tothe augmented system capacity re-quired by 5G networks. This require-ment will be meet by deploying morenetwork elements, in particular smallcells, in a scenario that is usually re-ferred to as “ultra-dense”. Specifically,I am focusing on the managementof self-sustainable small cells that areonly powered by renewable energy.The problem of minimizing the con-sumption of grid energy and maximiz-ing the system performance can besolved by optimally switching ON-OFFthe small cells. As a first step, I usedgraph theory and dynamic program-ming to find the performance boundsof this approach and published the al-gorithm and some results in a journalpaper. Then, I have studied the impactof the energy harvesting and trafficprofile on the optimal policies and sub-mitted the results to the IEEE WCNCconference. In 2018, I plan to improvemy knowledge about machine learn-

ing, also through my secondment, inorder to exploit these techniques todesign online algorithms for the loadcontrol of small cells. Furthermore,I plan to investigate energy sharingmethods between network elementsto further save grid energy and to re-duce the carbon footprint of the wholenetwork.

Angel Fernandez Gambin (ESR06)

In 2017, together with ESR05, I haveanalyzed the role of energy in the de-sign of future mobile networks, advo-cating the use of energy harvestinghardware as a means to decrease theenvironmental footprint of 5G tech-nology. A survey journal paper hasbeen accepted, where we review exist-ing energy sustainable paradigms andmethods and identify several open is-sues ranging from the need for ac-curate data traffic and energy con-sumption models to the use of powertransfer, energy cooperation and en-ergy trading techniques. After this,we examined the tradeoffs involvedin the process of wirelessly recharg-ing mobile terminals as they get suf-ficiently close to base stations usingWireless Power Transfer (WPT) tech-nology. Our performance evaluationrevealed that WPT can increase themobile terminal battery life, howevertransfer efficiencies are very low. Thiswork led to a conference paper, thatI presented to IEEE WoWMoM 2017.Then, I focused on small cell deploy-ments where energy harvesting andpacket power networks are combinedto provide energy self-sustainabilitythrough the use of own-stored energyand carefully planned energy trans-fers among network elements. Numer-ical results revealed that my approachis capable of increasing the energysustainability of the network, reduc-ing the amount of energy purchasedfrom the power grid, and preventingbase stations to run out of service dueto energy scarcity. A conference anda journal paper have emerged from

this research. I presented the con-ference contribution to IEEE GLOBE-COM 2017, whereas the journal is cur-rently under review. My next stepsinvolve the implementation of patternrecognition algorithms through ma-chine learning techniques, to improvethe effectiveness of energy coopera-tion and trading strategies. This iscurrently under investigation.

I am currently on leave at CTTC, work-ing on the above topics and establish-ing collaborations with ESR03, in thedesign of data analytic techniques for5G mobile traffic.

Elvina Gindullina (ESR07)

In 2017, I have been working on ana-lyzing and developing a battery man-agement system for mobile devices, inparticular, considering non-idealitiesof batteries, such as leakage, chargerecovery and deep discharge effects,which are caused by diffusion pro-cesses. By analyzing the outage prob-ability, we demonstrated that thesebattery imperfections can have a dra-matic impact on the operation policyof autonomous devices. A heuristicwas devised, which is aimed at reduc-ing events such as battery dischargeand data losses for such systems. Re-sults were published and presented atIEEE WCNC 2017 and IEEE ICC 2017.To analyze the management of mobiledevices with inhomogeneous energystorage and energy harvesting capabil-ities, the system was represented as aBayesian game with asymmetric play-ers. Results were published at IEEEWoWMoM 2017 and demonstrate thatknowledge about asymmetric prop-erties provide more balanced perfor-mance for energy harvesting wirelessnetworks.

I am currently on leave at Wordsens-ing in Barcelona, Spain, where I amstudying orthogonal resource shar-ing in wireless networks. Resourcesharing aims to enable distributedand dynamic discovery, negotiation

and sharing of tasks and resourcesamong nodes in heterogeneous andmulti-tasked IoT-like networks. I amconsidering node-collaboration sce-narios with three levels of knowledgeabout available resources. These ac-tivities encompass comparing the sce-narios and extracting the best strategyas well as its implementation.

Mehmet Emre Ozfatura (ESR08)

In the last decade, on demand videostreaming applications are responsi-ble for most of the Internet traffic andmany surveys predict that their sharewill increase further in the next fewyears. The boost in the size of theInternet video traffic and the densifi-cation process of heterogeneous cellu-lar networks call for a paradigm shiftin the design of future cellular net-works. One of the most promisingapproaches to deal with the exces-sive video traffic is content caching;which entails moving the popular filesto the network edge, closer to the fi-nal user in an attempt to improve thenetwork performance such as reduc-ing the transmission delay. In the lit-erature, many papers deal with thisproblem, particularly focusing on co-operative caching, cooperative codedcaching and coded delivery. How-ever, we realize that there are onlyfew works on mobility-aware contentcaching. Driven by these considera-tions, in 2017 we have started to workon mobility-aware coded storage andcoded delivery techniques. Some ofour results were published in the IEEEcommunication letters and some werepresented at the ITG Workshop onSmart Antennas (WSA 2018). More-over, we observed that user requestsfor the video files do no follow a uni-form distribution. Hence, we steeredour attention towards coded deliv-ery schemes under non-uniform de-mand. Our results will be presented atthe IEEE International Conference onCommunications (ICC) 2018 and soonwe will submit an extended journal pa-

per. At Imperial College of London, be-sides the aforementioned research ac-tivity, I am working as a co-advisor forgraduation projects, to make under-graduate students familiar with therecent research areas on communica-tion, while improving their researchskills and enhancing my supervisionabilities. We recently submitted the re-sults of an ongoing graduation projectto the IEEE International Symposiumon Personal, Indoor and Mobile Ra-dio Communications (PIMRC) 2018.Our current research focuses on fourmain areas; coded distributed compu-tation, decentralized coded cachingschemes, cache replacement strate-gies for energy harvesting cells andsmart transcoding strategies for videostreaming in cellular networks. Weare also seeking collaborations withother researchers to have a more com-plete design for future cellular net-works.

Nitish Mital (ESR09)

In 2017, I have researched literatureon coded multicasting techniques for5G networks, which have the poten-tial to increase the overall efficiencyand to reduce the power consumptionand delivery latency. Coded cachingis a novel method to utilize the mem-ory capacities of devices on a net-work to supplement the spectrum con-straints. There has been a long listof works in this area and industryconsiders it to be a very importanttechnology for future networks. Mywork includes proposing a deliveryscheme and study the performanceof coded caching in a distributedsmall-cell based scenario.

My paper “Coded caching in a multi-server system with random topology”has been recently presented at IEEEWCNC 2018, where it has receivedthe best student paper award. Ifeel that the environment I am get-ting from working in the SCAVENGEnetwork and in Imperial College is op-timal for my professional growth, be-

cause I am in the middle of peopleworking on the best ideas in the area.

Currently, my work is directed to-wards studying and proposing dis-tributed storage codes in a wirelesssetting, where files may be storedamong multiple devices with dynamicmemory management. The goal isto minimize the repair bandwidth(amount of communication amongnodes to repair corrupted data) whenstored data is disturbed during mem-ory management.

Vianney Anis (ESR10)

In 2017, I continued experimentationson filter-bank multi-carrier systems,with further study of Wavelet basedsystems. In parallel, I carried out apreliminary study of heterogeneousnetwork optimization problems forthe reduction of base-station energyconsumption, it included a listing ofthe involved variables, and variousattempts at formulating the problem.This study is a first step towards thedescription of the considered hetero-geneous network scenario as an opti-mization problem that can be solvedusing methods such as Bayesian net-works and Dynamic programming. Ialso contributed to two SCAVENGEdeliverables (within WP2 and WP4)and was amongst the main editors ofone of the deliverables. These docu-ments opened the discussions for fu-ture collaborations with other ESRs.My future research plans include fur-ther study and experimentations withfilter-bank multi-carrier transceiversystems, which should soon lead tothe implementation of a low-powerTV white space base-station proto-type on a software defined radio plat-form. This implementation workwould mostly be carried out duringmy SCAVENGE secondment in ToshibaResearch Europe in Bristol (9 monthsfrom April 2018). Using this radiosystem, we will extract a power con-sumption model which will be reusedin the formulation of a heterogeneous

network optimization problem.

Thembelihle Dlamini (ESR11)

Future cellular networks are requiredto be flexible with minimal infrastruc-ture complexity, unlike current onesthat rely on proprietary network ele-ments to offer their services. More-over, they are expected to make useof renewable energy to decrease theircarbon footprint and of virtualizationtechnologies for improved adaptabil-ity and flexibility, thus resulting ingreen and self-organized systems. Inmy project, I have focused on firstunderstanding the core network man-agement procedures, particularly thecharging gateway function in orderto develop guidelines for softwariz-ing it. From this work, I have ob-served that it is possible to visual-ize the extracted data over a Webdashboard and perform data analyt-ics over the extracted data to iden-tify traffic variation patterns. Thus,I have compared power consump-tion between virtualized computingplatforms and “bare metal” using ex-perimental power datasets and theserver power consumption model,which considered the utilization ofthe CPU and other system compo-nents (memory, disk, network inter-face card). In this work, I have consid-ered container- and hypervisor-basedvirtualized systems to better under-stand their power consumption in re-sponse to different applications. Frommy results, we have identified thateach server will respond differentlyin response to the running applicationon the virtual machine or container, asthe power consumption always varies.This makes it possible for the virtu-alized server to be power-aware, ex-ploiting knowledge of the consumedpower per time slot, and then map-ping server utilization to the availableenergy stored, in renewable-powerednetworks. Also, I have observed theeffects of CPU pinning, i.e., the lack ofscheduling, in the virtualized servers,

and such insights can enable the devel-opment of auto-scaling policies (CPUand Memory utilization rules) sincethey guarantee latency for real timeservices demanded by users. Theperformance per watt ratings for thenetwork function virtualized infras-tructure (NFVI) shows a different re-sponse in relation to the benchmarksused. Lastly, we have worked on de-veloping machine learning algorithmsfor edge workload prediction, usingthe long short term memory (LSTM)network for regression, using opensource mobile traffic datasets, andthen developed energy saving policiesfor virtualized systems for a remotesite, thus enabling network coverageextension. From the obtained results,we have observed that we can usethe past behavior of the network toproject hour-ahead server workloadestimates for a remote site, thus be-ing able to provision edge networkresources. My future work entails thedevelopment of mobility managementprocedures, for ultra-dense networkscoexisting with virtualized computingplatforms. A review journal paper hasbeen accepted on softwarization tech-nology for 5G networks, another jour-nal paper is being prepared and con-ference paper will be submitted.

I am currently on leave at the Depart-ment of Information Engineering ofthe University of Padova.

Pavlos Triantaris (ESR12)

After completing my mandatory ed-ucation (i.e., sixth-form equivalent,with mathematical/engineering foun-dation), I was accepted into theSchool of Engineering of the Aristo-tle University of Thessaloniki, Greece,

in September of 2011, for a full-timeM.Eng. course. Almost six years af-ter initial enrollment, I completed mystudies and acquired an M.Eng. de-gree in Electrical Engineering, with aGPA of 8.72/10, which is a First-ClassHonors equivalent. During the courseof the programme, I was involved intwo projects with outlook towards re-search:

1) “ERPs-based Attention AnalysisUsing Continuous Wavelet Trans-form: The bottom-up and top-downparadigms”. Written by a group of 8students under the supervision of Prof.Leontios Hadjileontiadis and ChrysaPapadaniil. Submitted to the 14thMediterranean Conference on Med-ical and Biological Engineering andComputing, qualified for the competi-tive phase of the conference.

2) “Accelerometer Data Processingfor the Recognition of Hand Move-ments”. Master’s Thesis. Preparedunder the supervision of Prof. Had-jileontiadis. Utilised hardware and de-veloped software subsequently givento the Georgios Papanikolaou GeneralHospital of Thesaloniki for purposesof medical research.

In June, 2017, I was accepted intothe SCAVENGE project as part of theirteam of Early Stage Researchers. Inthat, I also became a student of theImperial College of London and anemployee of Toshiba Research EuropeLtd. Having spent my first months as aPhD student in the facilities of Toshibain Bristol, UK, I can only relay thebest impressions about my employers,and I can state with confidence thatthe facilities and resources to which Ihave access thanks to them are mostsatisfactory in all respects. I believethat, thanks to the format of the SCAV-ENGE project for its ESRs, I shall gaininvaluable experience in research andscientific work, in both academic andworkplace scenarios.

An early-stage study of selected liter-ature suggested that an interestingsub-area open to further research isthe identification of the activity of spe-cific devices within the context of awireless system. As a result, the ideawhich was developed under this con-sideration is the development of anadvanced algorithm which will lever-age understanding of RF imperfec-

tions and Artificial Neural Networksin order to passively extract a finger-print and identify each individual de-vice which is active in the spectrumof a given access point or base station.The next phase of this study shall bea thorough attempt to understand thefunction and use of ANNs, as well asauxiliary signal processing techniques.As such, year 2018, during which mysecondment at the Imperial Collegeshall begin, shall be partly dedicatedto the study of ANNs and partly tothe development of new ANN-basedmodels for device identification.

Ioana Suciu (ESR13)

This past year spent as a ScavengeEarly Stage Researcher has been filledwith opportunities, challenges and ac-complishments: not only regardingthe training but also regarding theway we, the ESRs, learned how to suc-cessfully collaborate inside the SCAV-ENGE project. The training schoolsorganized by Scavenge representedgreat opportunities: not only for theirinvited speakers and the knowledgebrought but also for the opportunitythey gave us to share our trainingbackground experiences and to buildreal research teams. This, as wellas working for the work packagesthought us how to collaborate as re-search teams and it helped us broadenour knowledge outside our individualresearch projects. Regarding the chal-lenges and accomplishments met dur-ing this past year, I significantly im-proved my technical and theoreticalskills by following training activitiesin my host institution, Worldsensing.As Worldsensing is a well-known IoTpioneer company, training activities inembedded firmware development, en-ergy consumption measurements, test-ings of wireless communication relia-

bility, etc, were carried out with the ut-most professionalism. As a result, werecently submitted a paper analyzingthe impact of packet fragmentation inLow Power Wide Area Networks andwe are currently working on a newpaper. Regarding future plans, I couldonly hope that the next year will bringme as many achievements as this one,and that I will be able to continuouslyimprove as a researcher and as a per-son.

Soheil Rostami (ESR14)

Hello, I am Soheil Rostami, I havebeen hired by Huawei Finland towork as an Early Stage Researcher inthe SCAVENGE training network. AtHuawei, I am carrying out researchon 5G networks, focusing on energyefficient transceiver architectures andon designs enabling low-energy oper-ations for uplink and downlink com-munications. I am paying particularattention to energy efficient schedul-ing, which allocates resources in or-

der to maximize the sleeping time forboth mobile terminals and base sta-tions, and to minimize their energyconsumption through discontinuousand adaptive receiving / transmissionscheduling (DRX/DTX). Furthermore,I am currently designing a wake-upscheme and the corresponding signal-ing for mobile devices to reduce theenergy consumption of the deviceswhen in power-saving mode. Differ-ent measurements show that currentDRX techniques are not able to pro-vide major energy savings, thereforea novel wake-up scheme is being in-vestigated to tackle such a problem.For this, I have been designing the sig-nal structure, a maximum-likelihoodreceiver, and have been assessing thecorresponding implementation chal-lenges. At Huawei, we hope to impactcurrent 5G standardization activities,based on the promising results thatwe have recently obtained. Some pa-pers are currently under submissionand others in preparation.

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