A Distributed Resource Allocation Scheme for Self-Backhauled Full-Duplex Small Cell Networks

Nafiseh Forouzan, Amir Masoud Rabiei, Mikko Vehkapera, Risto Wichman

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Full-duplex (FD) radio with wireless backhauling, is a key technology for dense small cell deployments in fifth generation (5G) cellular networks. In this paper, the problem of joint user scheduling, operation mode selection and power allocation in a two-tier cellular network with FDcapable small basestations is considered. The objective is to maximize the network sum rate under quality-of-service requirements and backhaul capacity constraints. In order to solve the problem, a distributed algorithm is developed which divides the original problem into two subproblems, viz., (i) user scheduling and mode selection; and (ii) power allocation. For the first subproblem, a low-complexity search method is proposed for opportunistically finding the best user scheduling and operation modes. In the second subproblem, an iterative successive convex approximation method is proposed to transform the nonconvex power allocation problem into a sequence of convex subproblems. The proposed solution provides a hybrid strategy which opportunistically selects FD or half-duplex (HD) operation modes for access and backhaul links. It is observed that the proposed algorithm converges in few iterations and mitigates the interferences by properly adjusting the transmission powers. Numerical results demonstrate the superiority of the proposed scheme over other possible scenarios. In particular, the proposed algorithm can achieve up to 44% gain in overall sum rate compared to a network that solely uses HD.

Original languageEnglish
JournalIEEE Transactions on Vehicular Technology
DOIs
Publication statusE-pub ahead of print - 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • Full-duplex radio
  • resource allocation
  • self-backhauling
  • small cell networks
  • successive convex approximation

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