On Optimal Resource Allocation in Multi-RAT Wireless Networks With Receiver Characteristic Awareness

• Published in: IEEE transactions on cognitive communications and networking Vol. 5; no. 1; pp. 103 - 118
• Main Authors: Nabil, Amr, Padaki, Aditya V., Abdel-Rahman, Mohammad J., ElNainay, Mustafa, MacKenzie, Allen B., Reed, Jeffrey H.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.03.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: adjacent channel interference; Algorithms; Aliasing; Analog to digital conversion; Analog to digital converters; Channel allocation; Decomposition; Digital imaging; Interference; multi-RATs coexistence; Optimization; Particle swarm optimization; Power management; Radio; Radio frequency; Receivers; Receivers & amplifiers; Resource allocation; Resource management; RF receiver characteristics; Solid phases; Wireless communications; Wireless networks
• ISSN: 2332-7731; 2332-7731
• DOI: 10.1109/TCCN.2018.2878005

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.