An Adaptive Power Allocation and Coding Scheme for Improving Achievable Rate of the Gaussian Interference Channel

Zhonglong Wang, Liyuan Zhang, Meng Ma

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The best coding scheme for Gaussian interference channel (GIC) is still an open problem so far, and has attracted much attention in the field of wireless communication due to it plays an important role in combating co-channel interference. In this paper, an adaptive power allocation and coding scheme based on time sharing (TS) strategy is proposed for the twouser GIC to coordinate the interference and achieve a higher sum-rate. In the proposed scheme, the codewords are divided into some segments, and the power of each segment is jointly optimized for the two users to maximize the sum-rate. To solve the power allocation problem, a heuristic search algorithm based on the optimal path planning algorithm is proposed. Simulation results show that the proposed scheme can achieve a higher sum-rate compared with the conventional coding schemes.

Original languageEnglish
Title of host publication2020 IEEE 8th International Conference on Information, Communication and Networks, ICICN 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages8-13
Number of pages6
ISBN (Electronic)9781728189758
DOIs
StatePublished - Aug 2020
Externally publishedYes
Event8th IEEE International Conference on Information, Communication and Networks, ICICN 2020 - Xi'an, China
Duration: 22 Aug 202025 Aug 2020

Publication series

Name2020 IEEE 8th International Conference on Information, Communication and Networks, ICICN 2020

Conference

Conference8th IEEE International Conference on Information, Communication and Networks, ICICN 2020
Country/TerritoryChina
CityXi'an
Period22/08/2025/08/20

Keywords

  • Gaussian interference channel
  • Power allocation
  • capacity
  • time sharing

Fingerprint

Dive into the research topics of 'An Adaptive Power Allocation and Coding Scheme for Improving Achievable Rate of the Gaussian Interference Channel'. Together they form a unique fingerprint.

Cite this