Title
Novel Detection Scheme for LSAS Using Power Allocation in Multi User Scenario with LTE-A and MMB Channels.
Abstract
Massive MIMO (also known as the “Large-Scale Antenna System”) enables a significant reduction of latency on the air interface with the use of a large excess of service-antennas over active terminals and time division duplex operation. For large-scale MIMO, several technical issues need to be addressed (e.g., pilot pattern design and low-antenna power transmission design) and theoretically addressed (e.g., channel estimation and power allocation schemes). In this paper, we analyze the ergodic spectral efficiency upper bound of a large-scale MIMO, and the key technologies including channel uplink detection. We also present new approaches for detection and power allocation. Assuming arbitrary antenna correlation and user distributions, we derive approximations of achievable rates with linear detection techniques, namely zero forcing, maximum ratio combining, minimum mean squared error (MMSE) and eigen-value decomposition power allocation (EVD-PA). While the approximations are tight in the large system limit with an infinitely large number of antennas and user terminals, they also match our simulations for realistic system dimensions. We further show that a simple EVD-PA detection scheme can achieve the same performance as MMSE with one order of magnitude fewer antennas in both uncorrelated and correlated fading channels. Our simulation results show that our proposal is a better detection scheme than the conventional scheme for LSAS. Also, we used two channel environment channels for further analysis of our algorithm: the Long Term Evolution Advanced channel and the Millimeter wave Mobile Broadband channel.
Year
DOI
Venue
2016
10.1007/s11277-017-4093-7
Wireless Personal Communications
Keywords
Field
DocType
EVD-PA,LSAS,LTE-A,MMB,MMSE,MRC,Power allocation,ZF
Fading,Maximal-ratio combining,Computer science,MIMO,Minimum mean square error,Communication channel,Real-time computing,Spectral efficiency,LTE Advanced,Telecommunications link
Journal
Volume
Issue
ISSN
95
4
0929-6212
Citations 
PageRank 
References 
0
0.34
9
Authors
8
Name
Order
Citations
PageRank
Saransh Malik1116.77
Sangmi Moon21813.35
Bora Kim3116.43
Cheolwoo You415737.11
Huaping Liu58220.94
Jeong Ho Kim63610.48
Jihyung Kim732.49
Intae Hwang84530.80