Interference analysis and power allocation in the presence of mixed numerologies

Mao, J., Zhang, L. , Xiao, P. and Nikitopoulos, K. (2020) Interference analysis and power allocation in the presence of mixed numerologies. IEEE Transactions on Wireless Communications, 19(8), pp. 5188-5203. (doi: 10.1109/TWC.2020.2990717)

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Abstract

The flexibility in supporting heterogeneous services with vastly different technical requirements is one of the distinguishing characteristics of the fifth generation (5G) communication systems and beyond. One viable solution is to divide the system bandwidth into several bandwidth parts (BWPs), each having a distinct numerology optimized for a particular service. However, multiplexing of mixed numerologies over a unified physical infrastructure comes at the cost of induced interference. In this paper, we develop an analytical system model for inter-numerology interference (InterNI) analysis in orthogonal frequency-division multiplexing (OFDM) systems with and without filter processing in the presence of mixed numerologies. With the analytical model, the level of InterNI is quantified by the developed analytical metric, which is expressed as a function of several system parameters. This leads to an analysis and evaluation of these parameters for meeting a given distortion target. Moreover, a case study on power allocation utilizing the derived analysis is presented, where an optimization problem of maximizing the sum rate is formulated, and a solution is also provided. It is also demonstrated that a filtered-OFDM system better accommodates the coexistence of mixed numerologies. The proposed model provides an accurate analytical guidance for the multi-service design in 5G and beyond systems.

Item Type:Articles
Additional Information:This work of J. Mao and P. Xiao was supported by the U.K. Engineering and Physical Sciences Research Council under Grant EP/R001588/1 and EP/S02476X/1.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Zhang, Dr Lei
Authors: Mao, J., Zhang, L., Xiao, P., and Nikitopoulos, K.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:IEEE Transactions on Wireless Communications
Publisher:IEEE
ISSN:1536-1276
ISSN (Online):1558-2248
Published Online:07 May 2020
Copyright Holders:Copyright © 2020 IEEE
First Published:First published in IEEE Transactions on Wireless Communications 19(8): 5188-5203
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
304481Resource Orchestration for Diverse Radio SystemsLei ZhangEngineering and Physical Sciences Research Council (EPSRC)EP/S02476X/1ENG - Systems Power & Energy