Wireless Communications and Signal Processing Lab

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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, wireless sensing 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.
• S. Shen and B. Clerckx, “Beamforming Optimization for MIMO Wireless Power Transfer with Nonlinear Energy Harvesting: RF Combining versus DC Combining,” IEEE Trans. on Wireless Comm., vol. 20, no. 1, pp. 199-213, Jan. 2021.
• S. Shen and B. Clerckx, “Joint Waveform and Beamforming Optimization for MIMO Wireless Power Transfer,” accepted to IEEE Trans. on Commun.

Prototyping and Experimentation of Wireless Power and Radio Systems

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. We have also extended the prototype to demonstrate the feasibility of wireless information and power transfer.

• 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.
• J. Kim, B. Clerckx, and P.D. Mitcheson “Signal and System Design for Wireless Power Transfer: Prototype, Experiment and Validation” IEEE Trans. on Wireless Comm., vol. 19, no. 11, pp. 7453-7469, Nov. 2020.
• S. Shen, J. Kim, C. Song, and B. Clerckx, “Wireless Power Transfer with Distributed Antennas: System Design, Prototype, and Experiments,” accepted to IEEE Trans. on Industrial Electronics.
• J. Kim and B. Clerckx, “Range Expansion for Wireless Power Transfer using Joint Beamforming and Waveform Architecture: An Experimental Study in Indoor Environment,” accepted to IEEE Wireless Commun. Letters.
• J. Kim and B. Clerckx, “Wireless Information and Power Transfer for IoT: Pulse Position Modulation, Integrated Receiver, and Experimental Validation,” submitted to IEEE Internet of Things Journal.

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,” IEEE Trans. on Inf. Theory, vol. 66, no. 10, pp. 6488-6508, Oct. 2020.
• 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” IEEE Trans. on Commun., vol. 67, no. 10, pp. 7195-7210, Oct 2019.  
• E. Bayguzina and B. Clerckx, “Asymmetric Modulation Design for Wireless Information and Power Transfer with Nonlinear Energy Harvesting,” IEEE Trans. on Wireless Comm., vol 18, no 12, Dec 2019.
• B. Clerckx, K. Huang, L. R. Varshney, S. Ulukus, and M.-S. Alouini, “Wireless Power Transfer for Future Networks: Signal Processing, Machine Learning, Computing, and Sensing,” submitted to IEEE Journal of Selected Topics in Signal Processing.

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," IEEE Trans. on Commun., vol. 68, no. 11, pp. 6822-6839, Nov. 2020.

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,” IEEE Trans. on Inf. Theory, vol. 65, no. 11, pp. 7208-7232, Nov 2019.
• H. Joudeh and B. Clerckx, “On the Separability of Parallel MISO Broadcast Channels under Partial CSIT: A Degrees of Freedom Region Perspective,” IEEE Trans. on Inf. Theory, vol. 66, no. 7, pp. 4513-4529, July 2020.

Rate-Splitting Multiple Access and Next Generation Multiple Access

Rate Splitting Multiple Access (RSMA), based on (linearly or nonlinearly) precoded Rate-Splitting (RS) at the transmitter and Successive Interference Cancellation (SIC) at the receivers, has emerged as a novel, general and powerful framework for the design and optimization of non-orthogonal transmission, multiple access, and interference management strategies in future MIMO wireless networks. RSMA relies on the split of messages and the non-orthogonal transmission of common messages decoded by multiple users, and private messages decoded by their corresponding users. This enables RSMA to softly bridge and therefore reconcile the two extreme strategies of fully decode interference and treat interference as noise. RSMA has been shown to generalize, and subsume as special cases, four seemingly different strategies, namely Space Division Multiple Access (SDMA) based on linear precoding (currently used in 5G), Orthogonal Multiple Access (OMA), Non-Orthogonal Multiple Access (NOMA) based on linearly precoded superposition coding with SIC, and physical-layer multicasting. RSMA boils down to those strategies in some specific conditions, but outperforms them all in general. Through information and communication theoretic analysis, RSMA is shown to be optimal (from a Degrees-of-Freedom region perspective) in a number of scenarios and provides significant room for spectral efficiency, energy efficiency, fairness, reliability, QoS enhancements in a wide range of network loads and user deployments, robustness against imperfect Channel State Information at the Transmitter (CSIT), as well as feedback overhead and complexity reduction over conventional strategies used in 5G. The benefits of RSMA have been demonstrated in a wide range of scenarios (MU-MIMO, massive MIMO, multi-cell MIMO/CoMP, overloaded systems, NOMA, multigroup multicasting, mmwave communications, communications in the presence of RF impairments and superimposed unicast and multicast transmission, relay,…) and systems (terrestrial, cellular, satellite, …). Thanks to its versatility, RSMA has the potential to tackle challenges of modern communication systems and is a gold mine of research problems for academia and industry, spanning fundamental limits, optimization, PHY and MAC layers, and standardization..

We are leading the Special Interest Group (SIG) on RSMA in IEEE Communications Society. Check the link for a detailed list of papers and tutorials. In this SIG on RSMA, we provide a platform to bring together PhD students, researchers and engineers in academia and industry interested in the lower layers of wireless communication systems and in particular the design of 6G physical layer to share their ideas and discuss the major technical challenges, recent breakthroughs, new applications, open problems and challenges related to RSMA.

• 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,” IEEE Trans. on Commun., vol 67, no 12, pp. 8754-8770, Dec 2019.
• 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,” IEEE Signal Processing Letters, vol. 26, no. 11, pp. 1678-1682, Nov 2019. 
• 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,” IEEE Wireless Communications Letters, vol. 9, no 3, March 2020.
• Y. Mao, B. Clerckx, J. Zhang, V.O.K. Li, and M. Arafah, “Max-min Fairness of K-user Cooperative Rate-Splitting in MISO Broadcast Channel with User Relaying” IEEE Trans. on Wireless Comm., col. 19, no. 10, pp. 6362-6376, Oct. 2020.
• Y. Mao and B. Clerckx, “Beyond Dirty Paper Coding for Multi-Antenna Broadcast Channel with Partial CSIT: A Rate-Splitting Approach,” IEEE Trans. on Commun., vol 68, no. 11, pp. 6775-6791, Nov. 2020.
• Y. Mao, E. Piovano, and B. Clerckx, “Rate-Splitting Multiple Access for Overloaded Cellular Internet of Things,” accepted to IEEE Trans. on Commun.
• O. Dizdar, Y. Mao, W. Han, and B. Clerckx, “Rate-Splitting Multiple Access for Downlink Multi-Antenna Communications: Physical Layer Design and Link-level Simulations”, IEEE PIMRC 2020.
• O. Dizdar, Y. Mao, B. Clerckx, “Rate-Splitting Multiple Access to Mitigate the Curse of Mobility in (Massive) MIMO Networks” submitted to IEEE Trans. on Commun.
• B. Clerckx, Y. Mao, R. Schober, E. Jorswieck, D.J. Love, J. Yuan, L. Hanzo, G.Y. Li, E.G. Larsson, and G. Caire, “Is NOMA Efficient in Multi-Antenna Networks? A Critical Look at Next Generation Multiple Access Techniques,” submitted to IEEE Open Journal of the Communications Society.

6G

We study 6G multiple access designs.

• O. Dizdar, Y. Mao, W. Han, and B. Clerckx, “Rate-Splitting Multiple Access: A New Frontier for the PHY Layer of 6G”, IEEE VTC Fall 2020.
• O. Dizdar, Y. Mao, Y. Xu, P. Zhu, and B. Clerckx, “Rate-Splitting Multiple Access for Enhanced URLLC and eMBB in 6G,” in IEEE ISWCS 2021.

Reconfigurable Intelligent Surfaces/Intelligent Reflecting Surfaces

We study the modeling, design and optimization of reconfigurable intelligent surfaces for next generation wireless communications and wireless power transfer.

• S. Shen, B. Clerckx, and R. Murch, “Modeling and Architecture Design of Intelligent Reflecting Surfaces using Scattering Parameter Network Analysis,” submitted to IEEE Trans. on Wireless Commun.
• Y. Zhao, B. Clerckx, and Z. Feng, “IRS-Aided SWIPT: Joint Waveform, Active and Passive Beamforming Design Under Nonlinear Harvester Model,” in submission
• Z. Feng, B. Clerckx, and Y. Zhao, “Waveform and Beamforming Design for Intelligent Reflecting Surface Aided Wireless Power Transfer: Single-User and Multi-User Solutions,” in submission

Integrated Radar Sensing and Communications

We study the integration of sensing and communications in future wireless networks and aim at understanding how to make the best use of the spectrum joint sensing and communications.

• C. Xu, B. Clerckx, and J. Zhang, “Multi-Antenna Joint Radar and Communications: Precoder Optimization and Weighted Sum-Rate vs Probing Power Tradeoff,” IEEE Access, vol. 8, pp. 173974-173982, 2020.
• C. Xu, B. Clerckx, S. Chen, Y. Mao, and J. Zhang, “Rate-Splitting Multiple Access for Multi-Antenna Joint Radar and Communications,” in submission
• O. Dizdar, A. Kaushik, B. Clerckx, C. Masouros, “Rate-Splitting Multiple Access for Joint Radar-Communications with Low-Resolution DACs,” IEEE ICC 2021.
• R. Cerna-Loli, O. Dizdar, and B. Clerckx “A Rate-Splitting Strategy to Enable Joint Radar Sensing and Communication with Partial CSIT,” submitted to IEEE SPAWC 2021.

Satellite Communications

We study multi-antenna processing, multiple access, and interference maangement for future multibeam satellite communications.

• L. Yin and B. Clerckx, “Rate-Splitting Multiple Access for Multigroup Multicast and Multibeam Satellite Systems,” IEEE Trans. on Commun., vol. 69, no. 2, pp. 976-990, Feb. 2021.
• Z. W. Si, L. Yin, and B. Clerckx, “Rate-Splitting Multiple Access for Multigateway Multibeam Satellite Systems with Feeder Link Interference” in submission
• L. Yin, O. Dizdar, and B. Clerckx, “Rate-Splitting Multiple Access for Multigroup Multicast Cellular and Satellite Communications: PHY Layer Design and Link-Level Simulations” IEEE ICC 2021.

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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