Multiplexing Gain of Modulating Phases Through Reconfigurable Intelligent Surface

This paper investigates the information theoretical limit of a reconfigurable intelligent surface (RIS) aided communication scenario in which the RIS and the transmitter jointly send information to the receiver. The RIS is an emerging technology that uses a large number of passive reflective elements with adjustable phases to intelligently reflect the transmit signal to the intended receiver. While most previous studies of the RIS focus on its ability to beamform and to boost the received signal-to-noise ratio (SNR), this paper shows that if the information data stream is available both at the transmitter and the RIS and the phases at the RIS can be used to modulate data, then the multiplexing gain of the overall channel can potentially be significantly enhanced. Specifically, we show that in a multiple-input multiple-output (MIMO) channel with $M$ transmit antennas and $K$ receive antennas, a RIS with $N$ reflective elements can improve the multiplexing gain from min(M, K) to min(M + N/2 - 1/2, $N$, K). This result is obtained by establishing a connection between the RIS system and the MIMO channel with phase noises and using results for characterizing the information dimension under projection.

[1]  Xiaojun Yuan,et al.  Passive Beamforming and Information Transfer Design for Reconfigurable Intelligent Surfaces Aided Multiuser MIMO Systems , 2019, IEEE Journal on Selected Areas in Communications.

[2]  Qiang Cheng,et al.  MIMO Transmission Through Reconfigurable Intelligent Surface: System Design, Analysis, and Implementation , 2020, IEEE Journal on Selected Areas in Communications.

[3]  Jie Chen,et al.  Large Intelligent Surface/Antennas (LISA): Making Reflective Radios Smart , 2019, J. Commun. Inf. Networks.

[4]  Brian R Huntyx,et al.  How projections affect the dimension spectrum of fractal measures , 1997 .

[5]  Shlomo Shamai,et al.  Information Dimension and the Degrees of Freedom of the Interference Channel , 2015, IEEE Transactions on Information Theory.

[6]  Erik G. Larsson,et al.  Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks , 2019, IEEE Transactions on Wireless Communications.

[7]  Shlomo Shamai Shitz,et al.  On the Multiplexing Gain of Discrete-Time MIMO Phase Noise Channels , 2017, IEEE Transactions on Information Theory.

[8]  Mohamed-Slim Alouini,et al.  Smart radio environments empowered by reconfigurable AI meta-surfaces: an idea whose time has come , 2019, EURASIP Journal on Wireless Communications and Networking.

[9]  Shlomo Shamai,et al.  Beyond Max-SNR: Joint Encoding for Reconfigurable Intelligent Surfaces , 2019, 2020 IEEE International Symposium on Information Theory (ISIT).

[10]  Peter J. Winzer,et al.  Calculation of Mutual Information for Partially Coherent Gaussian Channels With Applications to Fiber Optics , 2010, IEEE Transactions on Information Theory.

[11]  Rui Zhang,et al.  Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network , 2019, IEEE Communications Magazine.

[12]  Emil Björnson,et al.  Intelligent Reflecting Surface Versus Decode-and-Forward: How Large Surfaces are Needed to Beat Relaying? , 2019, IEEE Wireless Communications Letters.

[13]  Chau Yuen,et al.  Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication , 2018, IEEE Transactions on Wireless Communications.

[14]  Mohamed-Slim Alouini,et al.  Wireless Communications Through Reconfigurable Intelligent Surfaces , 2019, IEEE Access.

[15]  Wei Yu,et al.  Learning to Reflect and to Beamform for Intelligent Reflecting Surface with Implicit Channel Estimation , 2020 .

[16]  Lajos Hanzo,et al.  Multicell MIMO Communications Relying on Intelligent Reflecting Surfaces , 2019, IEEE Transactions on Wireless Communications.

[17]  Ralf R. Müller,et al.  Load modulated arrays: a low-complexity antenna , 2016, IEEE Communications Magazine.

[18]  Jia Ye,et al.  Reflecting Modulation , 2020, IEEE Journal on Selected Areas in Communications.

[19]  Jun Fang,et al.  Intelligent Reflecting Surface-Assisted Millimeter Wave Communications: Joint Active and Passive Precoding Design , 2019, IEEE Transactions on Vehicular Technology.

[20]  Ying-Chang Liang,et al.  Channel Estimation for Reconfigurable Intelligent Surface Aided Multi-User MIMO Systems , 2019 .

[21]  George C. Alexandropoulos,et al.  A Hardware Architecture For Reconfigurable Intelligent Surfaces with Minimal Active Elements for Explicit Channel Estimation , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[22]  Shlomo Shamai,et al.  Reconfigurable Intelligent Surfaces vs. Relaying: Differences, Similarities, and Performance Comparison , 2019, IEEE Open Journal of the Communications Society.

[23]  Helmut Bölcskei,et al.  Degrees of Freedom in Vector Interference Channels , 2012, IEEE Transactions on Information Theory.

[24]  Amir K. Khandani,et al.  Media-based modulation: A new approach to wireless transmission , 2013, 2013 IEEE International Symposium on Information Theory.

[25]  Shi-Wei Qu,et al.  Terahertz Reflecting and Transmitting Metasurfaces , 2017, Proceedings of the IEEE.

[26]  Qingqing Wu,et al.  Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming , 2018, IEEE Transactions on Wireless Communications.