Rate-Splitting for Multi-Antenna Non-Orthogonal Unicast and Multicast Transmission: Spectral and Energy Efficiency Analysis

In a Non-Orthogonal Unicast and Multicast (NOUM) transmission system, a multicast stream intended to all the receivers is superimposed in the power domain on the unicast streams. One layer of Successive Interference Cancellation (SIC) is required at each receiver to remove the multicast stream before decoding its intended unicast stream. In this paper, we first show that a linearly-precoded 1-layer Rate-Splitting (RS) strategy at the transmitter can efficiently exploit this existing SIC receiver architecture. By splitting the unicast messages into common and private parts and encoding the common parts along with the multicast message into a super-common stream decoded by all users, the SIC is better reused for the dual purpose of separating the unicast and multicast streams as well as better managing the multi-user interference among the unicast streams. We further propose multi-layer transmission strategies based on the generalized RS and power-domain Non-Orthogonal Multiple Access (NOMA). Two different objectives are studied for the design of the precoders, namely, maximizing the Weighted Sum Rate (WSR) of the unicast messages and maximizing the system Energy Efficiency (EE), both subject to Quality of Service (QoS) rate requirements of all messages and a sum power constraint. A Weighted Minimum Mean Square Error (WMMSE)-based algorithm and a Successive Convex Approximation (SCA)-based algorithm are proposed to solve the WSR and EE problems, respectively. Numerical results show that the proposed RS-assisted NOUM transmission strategies are more spectrally and energy efficient than the conventional Multi-User Linear-Precoding (MU–LP), Orthogonal Multiple Access (OMA) and power-domain NOMA in a wide range of user deployments (with a diversity of channel directions, channel strengths and qualities of channel state information at the transmitter) and network loads (underloaded and overloaded regimes). It is superior for the downlink multi-antenna NOUM transmission.

[1]  Meixia Tao,et al.  Joint multicast and unicast beamforming for the MISO downlink interference channel , 2017, 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[2]  Lihua Li,et al.  MMSE-Based Precoding for Rate Splitting Systems With Finite Feedback , 2018, IEEE Communications Letters.

[3]  David Gesbert,et al.  Degrees of Freedom of Time Correlated MISO Broadcast Channel With Delayed CSIT , 2012, IEEE Transactions on Information Theory.

[4]  Ana I. Pérez-Neira,et al.  Generalized Multicast Multibeam Precoding for Satellite Communications , 2015, IEEE Transactions on Wireless Communications.

[5]  Bruno Clerckx,et al.  Rate-Splitting for Multi-Antenna Non-Orthogonal Unicast and Multicast Transmission , 2018, 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[6]  Symeon Chatzinotas,et al.  Multigroup Multicast Beamforming and Antenna Selection with Rate-Splitting in Multicell Systems , 2018, 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[7]  Bruno Clerckx,et al.  Rate-Splitting for Max-Min Fair Multigroup Multicast Beamforming in Overloaded Systems , 2017, IEEE Transactions on Wireless Communications.

[8]  Victor O.K. Li,et al.  Rate-Splitting Multiple Access for Coordinated Multi-Point Joint Transmission , 2019, 2019 IEEE International Conference on Communications Workshops (ICC Workshops).

[9]  Bruno Clerckx,et al.  Achievable DoF Regions of MIMO Networks With Imperfect CSIT , 2016, IEEE Transactions on Information Theory.

[10]  Erkai Chen,et al.  Joint Base Station Clustering and Beamforming for Non-Orthogonal Multicast and Unicast Transmission With Backhaul Constraints , 2017, IEEE Transactions on Wireless Communications.

[11]  Tharmalingam Ratnarajah,et al.  Rate-Splitting to Mitigate Residual Transceiver Hardware Impairments in Massive MIMO Systems , 2017, IEEE Transactions on Vehicular Technology.

[12]  Seokhyun Yoon,et al.  Superposition of Broadcast and Unicast in Wireless Cellular Systems , 2008, IEEE Communications Magazine.

[13]  Te Sun Han,et al.  A new achievable rate region for the interference channel , 1981, IEEE Trans. Inf. Theory.

[14]  Mohamed-Slim Alouini,et al.  Interference Mitigation Via Rate-Splitting in Cloud Radio Access Networks , 2018, 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[15]  Bruno Clerckx,et al.  Optimal DoF Region of the $K$ -User MISO BC With Partial CSIT , 2017, IEEE Communications Letters.

[16]  Bruno Clerckx,et al.  Overloaded multiuser MISO transmission with imperfect CSIT , 2016, 2016 50th Asilomar Conference on Signals, Systems and Computers.

[17]  Bruno Clerckx,et al.  Robust Transmission in Downlink Multiuser MISO Systems: A Rate-Splitting Approach , 2016, IEEE Transactions on Signal Processing.

[18]  Anass Benjebbour,et al.  Non-Orthogonal Multiple Access (NOMA) for Cellular Future Radio Access , 2013, 2013 IEEE 77th Vehicular Technology Conference (VTC Spring).

[19]  Timothy N. Davidson,et al.  Robust Downlink Transmission: An Offset-Based Single-Rate-Splitting Approach , 2018, 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[20]  Andrea J. Goldsmith,et al.  On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming , 2006, IEEE Journal on Selected Areas in Communications.

[21]  Bruno Clerckx,et al.  Rate splitting for MIMO wireless networks: a promising PHY-layer strategy for LTE evolution , 2016, IEEE Communications Magazine.

[22]  Bruno Clerckx,et al.  Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems With Partial CSIT: A Rate-Splitting Approach , 2016, IEEE Transactions on Communications.

[23]  Shlomo Shamai,et al.  On the Capacity Region of the Multi-Antenna Broadcast Channel with Common Messages , 2006, 2006 IEEE International Symposium on Information Theory.

[24]  Pinyi Ren,et al.  User Selection Algorithms for Simultaneous Unicast and Multicast Services , 2012, 2012 8th International Conference on Wireless Communications, Networking and Mobile Computing.

[25]  Bruno Clerckx,et al.  Rate-splitting multiple access for downlink communication systems: bridging, generalizing, and outperforming SDMA and NOMA , 2017, EURASIP Journal on Wireless Communications and Networking.

[26]  Yinyu Ye,et al.  Interior point algorithms: theory and analysis , 1997 .

[27]  Sumei Sun,et al.  Sum-rate maximization in the simultaneous unicast and multicast services with two users , 2010, 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[28]  Bruno Clerckx,et al.  Energy Efficiency of Rate-Splitting Multiple Access, and Performance Benefits over SDMA and NOMA , 2018, 2018 15th International Symposium on Wireless Communication Systems (ISWCS).

[29]  Ling Qiu,et al.  Improving energy efficiency through multimode transmission in the downlink MIMO systems , 2011, EURASIP J. Wirel. Commun. Netw..

[30]  Chandra Nair,et al.  The Capacity Region of the Two-Receiver Gaussian Vector Broadcast Channel With Private and Common Messages , 2014, IEEE Transactions on Information Theory.

[31]  Deniz Gündüz,et al.  Non-Orthogonal Unicast and Broadcast Transmission via Joint Beamforming and LDM in Cellular Networks , 2019, 2016 IEEE Global Communications Conference (GLOBECOM).

[32]  Yueping Wu,et al.  Rate Analysis of Two-Receiver MISO Broadcast Channel With Finite Rate Feedback: A Rate-Splitting Approach , 2015, IEEE Transactions on Communications.

[33]  John Riordan,et al.  Introduction to Combinatorial Analysis , 1959 .

[34]  Bruno Clerckx,et al.  Multiuser Millimeter Wave Beamforming Strategies With Quantized and Statistical CSIT , 2017, IEEE Transactions on Wireless Communications.

[35]  Zheng Li,et al.  A Constant-Gap Result on the Multi-Antenna Broadcast Channels with Linearly Precoded Rate Splitting , 2018, 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[36]  Ying Li,et al.  Gaussian Message Passing for Overloaded Massive MIMO-NOMA , 2018, IEEE Transactions on Wireless Communications.

[37]  Giuseppe Caire,et al.  A Rate Splitting Strategy for Massive MIMO With Imperfect CSIT , 2015, IEEE Transactions on Wireless Communications.

[38]  Syed Ali Jafar,et al.  Transmitter Cooperation under Finite Precision CSIT: A GDoF Perspective , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[39]  Bruno Clerckx,et al.  Tomlinson-Harashima Precoded Rate-Splitting for Multiuser Multiple-Antenna Systems , 2018, 2018 15th International Symposium on Wireless Communication Systems (ISWCS).

[40]  Bruno Clerckx,et al.  Sum rate maximization for MU-MISO with partial CSIT using Joint Multicasting and Broadcasting , 2015, 2015 IEEE International Conference on Communications (ICC).

[41]  Symeon Chatzinotas,et al.  Energy-efficient joint unicast and multicast beamforming with multi-antenna user terminals , 2017, 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[42]  Xianbin Wang,et al.  Layered-Division-Multiplexing: Theory and Practice , 2016, IEEE Transactions on Broadcasting.

[43]  Bruno Clerckx,et al.  On coded caching in the overloaded MISO broadcast channel , 2017, 2017 IEEE International Symposium on Information Theory (ISIT).

[44]  Syed Ali Jafar,et al.  GDoF of the MISO BC: Bridging the gap between finite precision CSIT and perfect CSIT , 2016, 2016 IEEE International Symposium on Information Theory (ISIT).

[45]  David Gomez-Barquero,et al.  LDM Versus FDM/TDM for Unequal Error Protection in Terrestrial Broadcasting Systems: An Information-Theoretic View , 2015, IEEE Transactions on Broadcasting.