Low Overhead Weighted-Graph-Coloring-Based Two-Layer Precoding for FDD Massive MIMO Systems

07/05/2018
by   Abdelrahman A. H. Anis, et al.
0

A massive multiple-input multiple-output (MIMO) system, operating in Frequency Division Duplexing (FDD) mode of operation, suffers from prohibitively high overhead associated with downlink channel state information (CSI) acquisition and downlink precoding, due to the lack of uplink/downlink channel reciprocity. In this paper, a heuristic edge-weighted vertex-coloring based pattern division (EWVC-PD) scheme is proposed to alleviate the overhead of a two-layer precoding approach, in a practical scenario where the user clusters undergo serious angular-spreading-range (ASR) overlapping. Specifically, under a constraint of limited number of subchannels, an undirected edge-weighted graph (EWG) is firstly constructed, to depict the potential ASR overlapping relationship among clusters. Then, inspired by classical graph coloring algorithms, we develop the EWVC-PD scheme which mitigate the ASR by subchannel orthogonalization between clusters possessing serious ASR overlapping, and multiplexing the ones having slight ASR overlapping. Simulation results reveal that our scheme efficiently outperforms the existing pattern division schemes.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/04/2022

Combining Reciprocity and CSI Feedback in MIMO Systems

Reciprocity-based time-division duplex (TDD) Massive MIMO (multiple-inpu...
research
09/22/2022

Deep Learning for Uplink CSI-based Downlink Precoding in FDD massive MIMO Evaluated on Indoor Measurements

When operating massive multiple-input multiple-output (MIMO) systems wit...
research
01/08/2019

Enabling FDD Massive MIMO through Deep Learning-based Channel Prediction

A major obstacle for widespread deployment of frequency division duplex ...
research
11/21/2020

Deep Learning Approach to Channel Sensing and Hybrid Precoding for TDD Massive MIMO Systems

This paper proposes a deep learning approach to channel sensing and down...
research
12/16/2020

User Coordination for Fast Beam Training in FDD Multi-User Massive MIMO

Massive multiple-input multiple-output (mMIMO) communications are one of...
research
10/18/2018

Zero-Forcing Per-Group Precoding (ZF-PGP) for Robust Optimized Downlink Massive MIMO Performance

In this paper, we propose a new, combined Zero-Forcing Per-Group Precodi...
research
04/28/2022

Multicarrier-Division Duplex for Solving the Channel Aging Problem in Massive MIMO Systems

The separation of training and data transmission as well as the frequent...

Please sign up or login with your details

Forgot password? Click here to reset