An Optimization Framework for General Rate Splitting for General Multicast
Lingzhi Zhao, Ying Cui, Sheng Yang, and Shlomo Shamai (Shitz)

TL;DR
This paper develops an optimization framework for general rate splitting in multicast wireless networks, addressing both slow and fast fading scenarios, and demonstrates significant performance improvements over existing methods.
Contribution
It introduces a unified optimization framework for rate splitting in general multicast, with novel algorithms for slow and fast fading scenarios that improve computational efficiency and performance.
Findings
Substantial rate gains over existing schemes.
Effective algorithms for slow fading channel optimization.
Promising low-complexity algorithms for fast fading scenarios.
Abstract
Immersive video, such as virtual reality (VR) and multi-view videos, is growing in popularity. Its wireless streaming is an instance of general multicast, extending conventional unicast and multicast, whose effective design is still open. This paper investigates general rate splitting for general multicast. Specifically, we consider a multi-carrier single-cell wireless network where a multi-antenna base station (BS) communicates to multiple single-antenna users via general multicast. We consider linear beamforming at the BS and joint decoding at each user in the slow fading and fast fading scenarios. In the slow fading scenario, we consider the maximization of the weighted sum average rate, which is a challenging nonconvex stochastic problem with numerous variables. To reduce computational complexity, we decouple the original nonconvex stochastic problem into multiple nonconvex…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Advanced Wireless Network Optimization · Cooperative Communication and Network Coding
