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      Regularized ZF in Cooperative Broadcast Channels under Distributed CSIT: A Large System Analysis

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          Abstract

          Obtaining accurate Channel State Information (CSI) at the transmitters (TX) is critical to many cooperation schemes such as Network MIMO, Interference Alignment etc. Practical CSI feedback and limited backhaul-based sharing inevitably creates degradations of CSI which are specific to each TX, giving rise to a distributed form of CSI. In the Distributed CSI (D-CSI) broadcast channel setting, the various TXs design elements of the precoder based on their individual estimates of the global multiuser channel matrix, which intuitively degrades performance when compared with the commonly used centralized CSI assumption. This paper tackles this challenging scenario and presents a first analysis of the rate performance for the distributed CSI multi-TX broadcast channel setting, in the large number of antenna regime. Using Random Matrix Theory (RMT) tools, we derive deterministic equivalents of the Signal to Interference plus Noise Ratio (SINR) for the popular regularized Zero-Forcing (ZF) precoder, allowing to unveil the price of distributedness for such cooperation methods.

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          Zero-Forcing Methods for Downlink Spatial Multiplexing in Multiuser MIMO Channels

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            Multi-Cell MIMO Cooperative Networks: A New Look at Interference

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              A Vector-Perturbation Technique for Near-Capacity Multiantenna Multiuser Communication—Part I: Channel Inversion and Regularization

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                Author and article information

                Journal
                1502.03654

                Numerical methods,Information systems & theory
                Numerical methods, Information systems & theory

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