Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
156 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

On Rate-Splitting With Non-unique Decoding In Multi-cell Massive MIMO Systems (2208.03532v1)

Published 6 Aug 2022 in cs.IT, eess.SP, and math.IT

Abstract: We consider the downlink of a multi-cell massive MIMO system suffering from asymptotic rate saturation due to pilot contamination. As opposed to treating pilot contamination interference as noise (TIN), we study the performance of decoding the pilot contamination interference. We model pilot-sharing users as an interference channel (IC) and study the performance of schemes that decode this interference partially based on rate-splitting (RS), and compare the performance to schemes that decode the interference in its entirety based on simultaneous unique decoding (SD) or non-unique decoding (SND). For RS, we non-uniquely decode each layer of the pilot contamination interference and use one common power splitting coefficient per IC. Additionally, we establish an achievable region for this RS scheme. Solving a maximum symmetric rate allocation problem based on linear programming (LP), we show that for zero-forcing (ZF) with spatially correlated/uncorrelated channels and with a practical number of BS antennas, RS achieves significantly higher spectral efficiencies than TIN, SD and SND. Furthermore, we numerically examine the impact of increasing the correlation of the channel across antennas, the number of users as well as the degree of shadow fading. In all cases, we show that RS maintains significant gain over TIN, SD and SND.

Citations (1)

Summary

We haven't generated a summary for this paper yet.