Main Research Areas

Our research interests lie in the area of Communication and Information Theory for Wireless Networks, Signal Processing, Optimization and Machine Learning for Wireless Communications and Wireless Power, and prototyping of wireless systems.

Signal Design and Processing for Wireless Power Transfer

Far-field Wireless Power Transfer (WPT) has attracted significant attention in recent years. Despite the rapid progress, the emphasis of the research community in the last decade has remained largely concentrated on improving the design of energy harvester (so-called rectenna) and has left aside the effect of transmitter design. We study the design of signals dedicated for WPT so as to enhance the range of WPT and the dc power at the output of the rectenna. Topics include energy harvester modeling, energy beamforming for WPT, channel acquisition, power region characterization in multi-user WPT, waveform design with linear and non-linear energy receiver model, safety and health issues of WPT, massive MIMO.

• B. Clerckx and E. Bayguzina, “Waveform Design for Wireless Power Transfer”, IEEE Trans on Sig Proc, Vol. 64, No. 23, pp. 6313-6328, Dec 2016.
• Y. Zeng, B. Clerckx and R. Zhang, “Communications and Signals Design for Wireless Power Transmission” IEEE Trans. on Comm, invited paper, Vol 65, No 5, pp 2264 – 2290, May 2017.
• B. Clerckx and E. Bayguzina, “A Low-Complexity Adaptive Multisine Waveform Design for Wireless Power Transfer,” IEEE Antennas and Wireless Propagation Letters, vol 16, pp 2207 – 2210, 2017.
• Y. Huang and B. Clerckx, “Large-Scale Multi-Antenna Multi-Sine Wireless Power Transfer”, IEEE Trans. on Sig Proc., vol. 65, no. 21, pp 5812-5827, Nov 2017.
• Y. Huang and B. Clerckx, “Waveform Design for Wireless Power Transfer with Limited Feedback” IEEE Trans. on Wireless Commun., vol 17, no 1, pp 415 – 429, Jan. 2018.
• B. Clerckx, A. Costanzo, A. Georgiadis, and N.B. Carvalho, “Toward 1G Mobile Power Networks: RF, Signal, and System Designs to Make Smart Objects Autonomous” IEEE Microwave Magazine, vol. 19, no. 6, pp. 69 – 82, Sept./Oct. 2018.
• B. Clerckx and J. Kim, “On the Beneficial Roles of Fading and Transmit Diversity in Wireless Power Transfer with Nonlinear Energy Harvesting,” IEEE Trans. on Wireless Commun, vol. 17, no. 11, pp. 7731 – 7743, Nov. 2018

Prototyping and Experimentation of Wireless Power Transfer

We develop and experiment the first prototype of a closed-loop WPT architecture based on channel adaptive waveform optimization and dynamic channel acquisition. The prototype consists of three important blocks as channel estimator, waveform optimizer, and energy harvester. Software Defined Radio (SDR) prototyping tools are used to implement a wireless power transmitter and a channel estimator, and a voltage doubler rectenna is designed to work as an energy harvester. We conduct experiments in real-world over-the-air conditions and highlight the benefits of such closed-loop and adaptive architecture over the traditional open-loop non-adaptive design.

• J. Kim, B. Clerckx, and P.D. Mitcheson, “Prototyping and Experimentation of a Closed-Loop Wireless Power Transmission with Channel Acquisition and Waveform Optimization” IEEE WPTC 2017.
• B. Clerckx and J. Kim, “On the Beneficial Roles of Fading and Transmit Diversity in Wireless Power Transfer with Nonlinear Energy Harvesting,” IEEE Trans. on Wireless Commun, vol. 17, no. 11, pp. 7731 – 7743, Nov. 2018.
• J. Kim, B. Clerckx, and P.D. Mitcheson, “Experimental Analysis of Harvested Energy and Throughput Trade-off in a Realistic SWIPT System,” IEEE WPTC 2019.


Wireless Information and Power Transfer/Wireless Powered Communication Network

Radio waves carry both energy and information. Nevertheless, traditionally, energy and information have been treated separately and have evolved as two independent fields in academia and industry, namely wireless power and wireless communication, respectively. This separation has for consequences that 1) current wireless networks pump RF energy into the free space (for communication purposes) but do not make use of it for energizing devices and 2) providing ubiquitous mobile power would require the deployment of a separate network of dedicated energy transmitters. Imagine instead a wireless network where information and energy flow together through the wireless medium. Wireless communication, or Wireless Information Transfer (WIT), and WPT would refer to two extreme strategies respectively targeting communication-only and power-only. A unified Wireless Information and Power Transfer (WIPT) design would have the ability to softly evolve in between those two extremes to make the best use of the RF spectrum/radiations and network infrastructure to communicate and energize, and hence outperform traditional systems relying on a separation of communications and power.

• J. Park and B. Clerckx, “Joint Wireless Information and Energy Transfer in a Two-User MIMO Interference Channel,” IEEE Trans. On Wireless Comm., vol. 12, no. 8, pp. 4210-4221, Aug. 2013.
• J. Park and B. Clerckx, “Joint Wireless Information and Energy Transfer in a K-User MIMO Interference Channel,” IEEE Trans. On Wireless Comm, vol. 13, no. 10, pp. 5781-5796, Oct 2014.
• H. Son and B. Clerckx, “Joint Beamforming Design for Multi-User Wireless Information and Power Transfer,” IEEE Trans. On Wireless Comm., vol. 13, no. 11, pp. 6397-6409, Nov 2014.
• J. Park and B. Clerckx, “Joint wireless information and energy transfer with reduced feedback in MIMO interference channels,” IEEE Journal on Selected Areas in Commun., vol. 33, no. 8, pp. 1563-1577, Aug 2015.
• Y. Huang and B. Clerckx, “Joint Wireless Information and Power Transfer for an Autonomous Multiple-Antenna Relay System,” IEEE Comm. Letters, vol.19, no.7, pp.1113-1116, July 2015.
• H. Lee, K.-J. Lee, H. Kim, B. Clerckx, and I. Lee, “Resource Allocation Techniques for Wireless Powered Communication Networks with Energy Storage Constraint,” IEEE Transactions on Wireless Communications, Vol.15 No.4, pp.2619-2628, April 2016.
• Y. Huang and B. Clerckx, “Relaying Strategies for Wireless-Powered MIMO Relay Networks” IEEE Trans. on Wireless Comm, vol 15, no 9, pp 6033-6047, Sept 2016.
• B. Clerckx, Z. Bayani Zawawi and K. Huang “Wirelessly Powered Backscatter Communications: Waveform Design and SNR-Energy Tradeoff” IEEE Communication Letters, vol 21, no 10, pp 2234-2237, Oct 2017.
• B. Clerckx, “Wireless Information and Power Transfer: Nonlinearity, Waveform Design and Rate-Energy Tradeoff”, IEEE Trans. on Sig Proc, vol 66, no 4, pp 847-862, Feb 2018.
•  J. Park, B. Clerckx, C. Song and Y. Wu, “An Analysis of the Optimum Node Density for Simultaneous Wireless Information and Power Transfer in Ad Hoc Networks” IEEE Trans. on Veh. Techn., vol. 67, no. 3, pp. 2713-2726, Mar. 2018.
• Z. B. Zawawi, Y. Huang and B. Clerckx, “Multiuser Wirelessly Powered Backscatter Communications: Nonlinearity, Waveform Design and SINR-Energy Tradeoff,” IEEE Trans. on Wireless Commun, vol. 18, no. 1, pp. 241 – 253, Jan 2019.
• M. Varasteh, B. Rassouli, and B. Clerckx, “On Capacity-Achieving Distributions for Complex AWGN Channels under Nonlinear Power Constraints and their Applications to SWIPT,” submitted to IEEE Trans. on Inf. Theory.
• B. Clerckx, R. Zhang, R. Schober, D. W. K. Ng, D. I. Kim, and H. V. Poor, “Fundamentals of Wireless Information and Power Transfer: From RF Energy Harvester Models to Signal and System Designs,” IEEE Journal on Selected Areas in Communications, vol. 37, no. 1, pp. 4-33, Jan 2019.
• Z. B. Zawawi, Y. Huang and B. Clerckx, “Multiuser Wirelessly Powered Backscatter Communications: Nonlinearity, Waveform Design and SINR-Energy Tradeoff,” IEEE Trans. on Wireless Commun, vol. 18, no. 1, pp. 241 – 253, Jan 2019.
• M. Varasteh, B. Rassouli, and B. Clerckx, “SWIPT Signalling over Frequency-Selective Channels with a Nonlinear Energy Harvester: Non-Zero Mean and Asymmetric Inputs” accepted to IEEE Trans. on Commun.   
• E. Bayguzina and B. Clerckx, “Asymmetric Modulation Design for Wireless Information and Power Transfer with Nonlinear Energy Harvesting,” accepted to IEEE Trans. on Wireless Comm.

Machine Learning for Wireless Communications and Power Transfer

We study the use of machine learning, as an alternative and complementary approach to communication theory and optimization, to design wireless communications and wireless power transfer systems.

• M. Varasteh, E. Piovano and B. Clerckx, “A Learning Approach to Wireless Information and Power Transfer Signal and System Design,” IEEE ICASSP 2019.
• M. Varasteh, B. Clerckx and J. Hoydis, "Learning Modulation Design for SWIPT with Nonlinear Energy Harvester: Large and Small Signal Power Regimes," IEEE SPAWC 2019.
• M. Varasteh, B. Clerckx and J. Hoydis, "Learning to Communicate and Energize: Modulation, Coding and Multiple Access Designs for Wireless Information-Power Transmission," in submission

Information/Communication-Theoretic Limits of MIMO Wireless Networks

We study the fundamental limits of Robust Interference Management for MIMO wireless networks. A particular interest is the characterization of rate/DoF/Generalized DoF region of networks with imperfect and/or delayed Channel State Information at the Transmitter (CSIT) and the role played by CSIT on the performance of MIMO wireless networks.

• B. Rassouli, C. Hao and B. Clerckx, “A New Proof for the DoF Region of the MIMO Networks with No CSIT,” IEEE Comm. Letters, vol. 19, no. 5, pp. 763–766, May 2015.
• B. Clerckx and D. Gesbert, “Space-Time Encoded MISO Broadcast Channel with Outdated CSIT: An Error Rate and Diversity Performance Analysis,” IEEE Trans. On Comm., vol. 63, no. 5, pp. 1661–1675, May 2015.
• B. Rassouli, C. Hao and B. Clerckx, “DoF Analysis of the MIMO Broadcast Channel with Alternating/Hybrid CSIT,” IEEE Trans. on Info Theory, vol. 62, no. 3, pp. 1312-1325, March 2016.
• C. Hao and B. Clerckx, “Achievable Sum DoF of the K-User MIMO Interference Channel with Delayed CSIT,” IEEE Trans. on Comm, vol 64, no 10, pp. 4165-4180, Oct 2016.
• B. Rassouli and B. Clerckx, "On the Capacity of Vector Gaussian Channels With Bounded Inputs," IEEE Trans. on Info Theory, Vol 62, No 12, pp 6884-6903, Dec 2016.
• C. Hao and B. Clerckx, “MISO Networks with Imperfect CSIT: A Topological Rate-Splitting Approach,” IEEE Trans. on Comm., Vol 65, No 5, pp. 2164 – 2179, May 2017.
• C. Hao, B. Rassouli, and B. Clerckx, “Achievable DoF Regions of MIMO Networks with Imperfect CSIT,” IEEE Trans. on Info Theory, vol. 63, no. 10, pp. 6587-6606, Oct 2017.
• E. Piovano and B. Clerckx, “Optimal DoF region of the K-User MISO BC with Partial CSIT,” IEEE Commun. Letters, vol 21, no 11, pp 2368-2371, Nov 2017.
• E. Piovano, H. Joudeh, and B. Clerckx “Generalized Degrees of Freedom of the Symmetric Cache-Aided MISO Broadcast Channel with Partial CSIT,” IEEE Trans. on Inf. Theory, vol. 65, no. 9, pp. 5799-5815, Sept 2019.
• H. Joudeh and B. Clerckx, “On the Optimality of Treating Inter-Cell Interference as Noise in Uplink Cellular Networks,” accepted to IEEE Trans. on Inf. Theory.

Rate-Splitting for MIMO Wireless Networks

Rate splitting relies on the transmission of common (degraded) messages decoded by multiple users, and private (nondegraded) messages decoded by their corresponding users. This bridges two transmission strategies that deal with the extremes of unknown and perfectly known multiuser interference. As a result, multiuser transmission moves away from conventional unicast-only transmission to superimposed unicast multicast transmission. Through information and communication theoretic analysis, rate splitting is shown to provide significant benefits in terms of spectral efficiencies, reliability and CSI feedback overhead reduction over conventional strategies used in 4G and 5G and exclusively relying on private (unicast) messages. Moreover, the gains of rate splitting are demonstrated in a wide range of scenarios: multi-user MIMO, massive MIMO, multi-cell MIMO, overloaded systems, Non-Orthogonal Multiple Access (NOMA), multigroup multicasting, mmwave communications, communications in the presence of RF impairments and coded caching.

• C. Hao, Y. Wu and B. Clerckx, “Rate Analysis of Two-Receiver MISO Broadcast Channel with Finite Rate Feedback: A Rate-Splitting Approach,” IEEE Trans. on Comm., vol. 63, no. 9, pp. 3232-3246, Sept 2015.
• B. Clerckx, H. Joudeh, C. Hao, M. Dai, and B. Rassouli, “Rate Splitting for MIMO Wireless Networks: A Promising PHY-Layer Strategy for LTE Evolution,” IEEE Comm. Mag, pp 98-105, May 2016.
• M. Dai, B. Clerckx, D. Gesbert and G. Caire, “A Rate Splitting Strategy for Massive MIMO with Imperfect CSIT,” IEEE Trans. on Wireless Comm., vol 15, no 7, pp 4611-4624, July 2016.
• H. Joudeh and B. Clerckx, “Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems with Partial CSIT: A Rate-Splitting Approach,” IEEE Trans. on Comm. vol. 64, no. 11, pp. 4847-4861, Nov 2016.
• H. Joudeh and B. Clerckx “Robust Transmission in Downlink Multiuser MISO Systems: A Rate-Splitting Approach,” IEEE Trans. on Sig. Proc. Vol. 64, No. 23, pp. 6227-6242 , Dec 2016.
• C. Hao and B. Clerckx, “MISO Networks with Imperfect CSIT: A Topological Rate-Splitting Approach,” IEEE Trans. on Comm., Vol 65, No 5, pp. 2164 – 2179, May 2017.
• A. Papazafeiropoulos, B. Clerckx, and T. Ratnarajah, “Rate-Splitting to Mitigate Residual Transceiver Hardware Impairments in Massive MIMO Systems,” IEEE Trans. on Veh. Tech., vol 66, no 9, pp 8196-8211, Sept 2017.
• C. Hao, B. Rassouli, and B. Clerckx, “Achievable DoF Regions of MIMO Networks with Imperfect CSIT,” IEEE Trans. on Info Theory, vol. 63, no. 10, pp. 6587-6606, Oct 2017.
• E. Piovano and B. Clerckx, “Optimal DoF region of the K-User MISO BC with Partial CSIT,” IEEE Commun. Letters, vol 21, no 11, pp 2368-2371, Nov 2017.
• M. Dai and B. Clerckx, “Multiuser Millimeter Wave Beamforming Strategies with Quantized and Statistical CSIT,” IEEE Trans. on Wireless Comm., vol 16, no 11, pp 7025-7038, Nov 2017.
• H. Joudeh and B. Clerckx, “Rate-Splitting for Max-Min Fair Multigroup Multicast Beamforming in Overloaded Systems”, IEEE Trans. on Wireless Commun., vol 16, no 11, pp 7276-7289, Nov 2017.
• Y. Mao, B. Clerckx and V.O.K. Li, “Rate-Splitting Multiple Access for Downlink Communication Systems: Bridging, Generalizing and Outperforming SDMA and NOMA,” EURASIP Journal on Wireless Communications and Networking, May 2018.
• Y. Mao, B. Clerckx and V.O.K. Li, “Rate-Splitting for Multi-Antenna Non-Orthogonal Unicast and Multicast Transmission: Spectral and Energy Efficiency Analysis,” submitted to IEEE Trans. on Commun.
• B. Clerckx, Y. Mao, R. Schober, and H. V. Poor, “Rate-Splitting Unifying SDMA, OMA, NOMA, and Multicasting in MISO Broadcast Channel: A Simple Two-User Rate Analysis,” submitted to IEEE Wireless Communications Letters
• J. Zhang, B. Clerckx, J. Ge, and Y. Mao, “Cooperative Rate-Splitting for MISO Broadcast Channel with User Relaying, and Performance Benefits over Cooperative NOMA,” submitted to IEEE Signal Processing Letters

Interference Management, Multi-Point Coordination and Large Network Analysis

• B. Clerckx, H. Lee, J.Y. Hong and G. Kim “A Practical Cooperative Multicell MIMO-OFDMA Network based on Rank Coordination,” IEEE Trans. on Wireless Comm. vol. 12, no. 4, pp. 1481-1491, April 2013.
• Y. Wu, Y. Cui and B. Clerckx, “Analysis and Optimization of Inter-tier Interference Coordination in Downlink Multi-Antenna HetNets with Offloading” IEEE Trans. on Wireless Comm., Vol 14, no 12, Dec 2015.
• Y. Cui, Y. Wu, D. Jiang, and B. Clerckx, “User-Centric Interference Nulling in Downlink Multi-Antenna Heterogeneous Networks,” IEEE Trans. on Wireless Comm., Vol. 15, No. 11, pp 7484-7500 , Nov 2016.
• M. Bacha, Y. Wu, and B. Clerckx, “Downlink and Uplink Decoupling in Two-Tier Heterogeneous Networks with Multi-Antenna Base Stations,” IEEE Trans. on Wireless Comm, Vol 16, No 5, pp 2760 - 2775, May 2017.
• M. Bacha, M. Di Renzo, and B. Clerckx, “Treating Interference as Noise in Cellular Networks: A Stochastic Geometry Approach,” submitted to IEEE Trans. on Wireless Commun.


Some Matlab Codes

Matlab Code for Capacity of Vector Gaussian Channels With Bounded Inputs

Matlab code for the paper B. Rassouli and B. Clerckx, "On the Capacity of Vector Gaussian Channels With Bounded Inputs," IEEE Trans. on Info Theory, Vol 62, No 12, pp 6884-6903, Dec 2016.

Matlab Codes for rate-splitting

Matlab code for the paper Y. Mao, B. Clerckx and V.O.K. Li, “Rate-Splitting Multiple Access for Downlink Communication Systems: Bridging, Generalizing and Outperforming SDMA and NOMA,” EURASIP Journal on Wireless Communications and Networking, May 2018.
Matlab code for the paper Y. Mao, B. Clerckx and V.O.K. Li, “Energy Efficiency of Rate-Splitting Multiple Access, and Performance Benefits over SDMA and NOMA” IEEE ISWCS 2018.
Matlab code for the paper Y. Mao, B. Clerckx and V.O.K. Li, “Rate-Splitting for Multi-Antenna Non-Orthogonal Unicast and Multicast Transmission” IEEE SPAWC 2018.
Matlab code for the paper E. Piovano, H. Joudeh and B. Clerckx, “Overloaded MU-MISO transmission with imperfect CSIT,” Asilomar 2016.



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