Rate Splitting for Multi-Antenna Downlink: Precoder Design and Practical Implementation

• Published in: IEEE journal on selected areas in communications Vol. 38; no. 8; pp. 1910 - 1924
• Main Authors: Li, Zheng, Ye, Chencheng, Cui, Ying, Yang, Sheng, Shamai, Shlomo
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Algorithms; Antenna design; Antennas; Approximation algorithms; Complexity; Complexity theory; Computer Science; Decoding; Downlinking; imperfect channel state information at the transmitter’s side (CSIT); Information Theory; Interference; MIMO communication; Multi-antenna downlink transmission; Optimization; precoder design; rate splitting (RS); Receivers; Receivers & amplifiers; Splitting; stream selection; Streams
• ISSN: 0733-8716; 1558-0008
• DOI: 10.1109/JSAC.2020.3000824

Rate splitting (RS) is a potentially powerful and flexible technique for multi-antenna downlink transmission. In this paper, we address several technical challenges towards its practical implementation for beyond 5G systems. To this end, we focus on a single-cell system with a multi-antenna base station (BS) and <inline-formula> <tex-math notation="LaTeX">K </tex-math></inline-formula> single-antenna receivers. We consider RS in its most general form with <inline-formula> <tex-math notation="LaTeX">2^{K}-1 </tex-math></inline-formula> streams, and joint decoding to fully exploit the potential of RS. First, we investigate the achievable rates under joint decoding and formulate the precoder design problems to maximize a general utility function, or to minimize the transmit power under pre-defined rate targets. Building upon the concave-convex procedure (CCCP), we propose precoder design algorithms for an arbitrary number of users. Our proposed algorithms approximate the intractable non-convex problems with a number of successively refined convex problems, and provably converge to stationary points of the original problems. Then, to reduce the decoding complexity, we consider the optimization of the precoder and the decoding order under successive decoding. Further, we propose a stream selection algorithm to reduce the number of precoded signals. With a reduced number of streams and successive decoding at the receivers, our proposed algorithm can even be implemented when the number of users is relatively large, whereas the complexity was previously considered as prohibitively high in the same setting. Finally, we propose a simple adaptation of our algorithms to account for the imperfection of the channel state information at the transmitter. Numerical results demonstrate that the general RS scheme provides a substantial performance gain as compared to state-of-the-art linear precoding schemes, especially with a moderately large number of users.