Linearly Precoded Rate-Splitting Techniques with Block Diagonalization for Multiuser MIMO Systems

Abstract

In this work, we investigate Block Diagonalization (BD) techniques for multiuser multiple-antenna systems using rate-splitting (RS) multiple access. In RS multiple access the messages of the users are split into a common part and a private part in order to mitigate multiuser interference. We present the system model for a RS multiple access system operating in a broadcast channel scenario where the receivers are equipped with multiple antennas. We also develop linear precoders based on BD for the RS multiple access systems along with combining techniques, such as the min-max criterion and the maximum ratio combining criterion, to enhance the common rate. Closed-form expressions to describe the sum rate performance of the proposed scheme are also derived. The performance of the system is evaluated via simulations considering imperfect channel state information at the transmitter. The results show that the proposed schemes outperform conventional linear precoding methods. Index TermsMultiple-antenna systems, ergodic sum-rate, rate-splitting, block diagonalization .

Linear Precoding and Stream Combining for Rate Splitting in Multiuser MIMO Systems

“…(10) The structure of the kth receiver is shown in Fig. 2, which is different from [11], where the combiner and the private receiver are implemented sequentially. In what follows, we propose combining strategies to set up w k and enhance the common rate performance.…”

“…MMSE-RS and RBD-RS denote the RS scheme without the common combiner. The best strategy from [11] is represented by BD-RS-MRC. For this simulation we set the SNR to 20 dB.…”

Successive Null-Space Precoder Design for Downlink MU-MIMO with Rate Splitting and Single-Stage SIC

“…However, the achievable rate for BD has a large gap to DPC. Thus, RSMA-based extensions to BD were studied in [14], [15], and improvements in performance and resilience to imperfect CSI were demonstrated. However, the schemes in [14], [15] utilized scalar common messages, xed BD or regularized BD precoder matrices, and performed power allocation based on exhaustive search.…”

“…• We compare the obtained lower bound with the performance of DPC, MIMO-RSMA [14], and BD. Our simulation results show that the proposed design outperforms MIMO-RSMA [14] and BD, and has a relatively small gap to DPC, especially at low to medium signal to noise ratios (SNRs).…”

“…The sum rate is averaged over multiple MIMO channel realizations so as to obtain a 99% con dence interval of ±1 bit per channel use (BPCU) for the average sum rate. The obtained average sum rate is compared with the average sum rates of DPC, obtained by exploiting the BC-MAC duality [21], MIMO-RSMA [14], and BD [13]. Furthermore, in Algorithm 1, the numerical tolerance is set to = 10 −5 .…”