Rate-Splitting Unifying SDMA, OMA, NOMA, and Multicasting in MISO Broadcast Channel: A Simple Two-User Rate Analysis

Considering a two-user multi-antenna Broadcast Channel, this letter shows that linearly precoded Rate-Splitting (RS) with Successive Interference Cancellation (SIC) receivers is a flexible framework for non-orthogonal transmission that generalizes, and subsumes as special cases, four seemingly different strategies, namely Space Division Multiple Access (SDMA) based on linear precoding, Orthogonal Multiple Access (OMA), Non-Orthogonal Multiple Access (NOMA) based on linearly precoded superposition coding with SIC, and physical-layer multicasting. This letter studies the sum-rate and shows analytically how RS unifies, outperforms, and specializes to SDMA, OMA, NOMA, and multicasting as a function of the disparity of the channel strengths and the angle between the user channel directions.

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

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

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

[4]  Rangeet Mitra,et al.  Non-orthogonal Multiple Access as an Enabler for Massive Connectivity for 5G and Beyond Networks , 2019 .

[5]  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.

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

[7]  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).

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

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

[10]  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.

[11]  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.

[12]  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).

[13]  Lajos Hanzo,et al.  Nonorthogonal Multiple Access for 5G and Beyond , 2017, Proceedings of the IEEE.

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

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

[17]  Wern-Ho Sheen,et al.  A two-user approximation-based transmit beamforming for physical-layer multicasting in mobile cellular downlink systems , 2015 .

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