QoS Aware Power Allocation and User Selection in Massive MIMO Underlay Cognitive Radio Networks

We address the problem of power allocation and secondary user (SU) selection in the downlink from a secondary base station (SBS) equipped with a large number of antennas in an underlay cognitive radio network. A new optimization framework is proposed in order to select the maximum number of SUs and...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on cognitive communications and networking Vol. 4; no. 2; pp. 220 - 231
Main Authors: Chaudhari, Shailesh, Cabric, Danijela
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.06.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Allocations
Antennas
Array signal processing
Base stations
Cognitive radio
Computer simulation
Imperfect CSI
Interference
massive MIMO
Maximum power
Optimization
power allocation
Power management
Radio networks
underlay cognitive radio
user selection
zero-forcing beamforming
ISSN:2332-7731, 2332-7731
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We address the problem of power allocation and secondary user (SU) selection in the downlink from a secondary base station (SBS) equipped with a large number of antennas in an underlay cognitive radio network. A new optimization framework is proposed in order to select the maximum number of SUs and compute power allocations in order to satisfy instantaneous rate or QoS requirements of SUs. The optimization framework also aims to restrict the interference to primary users (PUs) below a predefined threshold using available imperfect CSI at the SBS. In order to obtain a feasible solution for power allocation and user selection, we propose a low-complexity algorithm called DeleteSU-with-Maximum-Power-allocation (DMP). Theoretical analysis is provided to compute the interference to PUs and the number of SUs exceeding the required rate. The analysis and simulations show that the proposed DMP algorithm outperforms the stateof-the art selection algorithm in terms of serving more users with minimum rate constraints, and it approaches the optimal solution if the number of antennas is an order of magnitude greater than the number of users.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2332-7731
2332-7731
DOI:10.1109/TCCN.2018.2794392