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On Optimal Resource Allocation in Multi-RAT Wireless Networks With Receiver Characteristic Awareness
Author(s) -
Amr Nabil,
Aditya V. Padaki,
Mohammad J. AbdelRahman,
Mustafa ElNainay,
Allen B. MacKenzie,
Jeffrey H. Reed
Publication year - 2018
Publication title -
ieee transactions on cognitive communications and networking
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 25
eISSN - 2372-2045
pISSN - 2332-7731
DOI - 10.1109/tccn.2018.2878005
Subject(s) - computer science , resource allocation , channel (broadcasting) , mathematical optimization , particle swarm optimization , wireless , optimization problem , channel allocation schemes , frequency allocation , wireless network , transmitter power output , interference (communication) , computer network , algorithm , transmitter , telecommunications , mathematics
Next-generation wireless systems are expected to use multiple coexisting radio access technologies with different receive and transmit characteristics. This will make the radio frequency front-ends susceptible to unprecedented adjacent-channel interference (ACI), which can jeopardize communication performance. In this paper, we propose a novel ACI-aware joint channel and power allocation framework that takes into account the receiver imperfections arising due to: 1) imperfect image frequency rejection and 2) analog-to-digital converter aliasing. The objective is to minimize the number of allocated channels and the aggregate power transmitted while satisfying the rate demands of different links in a multi-radio access technology environment. As the overall problem is NP-hard, we develop an efficient algorithm to solve it through decomposing the problem into two subproblems: channel allocation and power assignment. Then, it solves the decomposed problem by iteration using a two-phase structure. In Phase I, a particle swarm optimization-based algorithm is tailored to obtain good solutions for the channel allocation subproblem. Phase II solves the power allocation subproblem optimally given the channel allocation solution obtained in Phase I. The results demonstrate: 1) the criticality of receiver-characteristic awareness when designing resource allocation schemes and 2) the superiority of the proposed algorithm in solving the overall problem efficiently.

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