Title
Symbol-Level Precoding for Low Complexity Transmitter Architectures in Large-Scale Antenna Array Systems
Abstract
In this paper, we consider three transmitter designs for symbol-level-precoding (SLP), a technique that mitigates multiuser interference (MUI) in multiuser systems by designing the transmitted signals using the channel state information and the information-bearing symbols. The considered systems tackle the high hardware complexity and power consumption of existing SLP techniques by reducing or completely eliminating fully digital radio frequency (RF) chains. The first proposed architecture referred to as, Antenna Selection SLP, minimizes the MUI by activating a subset of the available antennas and thus, reducing the number of required RF chains to the number of active antennas. In the other two architectures, which we refer to as RF domain SLP, the processing happens entirely in the RF domain, thus eliminating the need for multiple fully digital RF chains altogether. Instead, the analog phase shifters directly modulate the signals on the transmit antennas. The precoding design for all the considered cases is formulated as a constrained least squares problem and efficient algorithmic solutions are developed via the Coordinate Descent method. Simulations provide insights into the power efficiency of the proposed schemes and the improvements over the fully digital counterparts.
Year
DOI
Venue
2019
10.1109/TWC.2018.2885525
IEEE Transactions on Wireless Communications
Keywords
Field
DocType
Radio frequency,Transmitting antennas,Antenna arrays,Precoding,Computer architecture
Electrical efficiency,Digital radio,Transmitter,Antenna array,Electronic engineering,Radio frequency,Real-time computing,Interference (wave propagation),Precoding,Mathematics,Channel state information
Journal
Volume
Issue
ISSN
18
2
1536-1276
Citations 
PageRank 
References 
7
0.46
0
Authors
4
Name
Order
Citations
PageRank
Stavros G. Domouchtsidis1242.40
Christos G. Tsinos211618.30
Symeon Chatzinotas31849192.76
Björn E. Ottersten46418575.28