QoS-Driven Energy-Efficient Resource Allocation in Multiuser Amplify-and-Forward Relay Networks

Keshav Singh, Ankit Gupta, Tharmalingam Ratnarajah

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

In this paper, we investigate energy-efficient joint subcarrier pairing, subcarrier allocation, and power allocation algorithms for improving the network energy efficiency (EE) in multiuser amplify-and-forward (AF) relay networks while ensuring the desired quality-of-service (QoS) requirement for the users through the concept of “network price”. Further, we introduce a network price paid for the consumed power as a penalty for the achievable sum rate and formulate a resource allocation problem subject to limited transmit power budget and QoS constraints. The formulated problem is a nonconvex binary mixed-integer non-linear programming (MINLP) problem and it is hard to solve the problem. We then apply a concave lower bound on the pricing-based network utility to transform the problem into a convex one. The dual decomposition method is adopted to propose a £-price resource allocation algorithm to find the near-optimal solution. Next, we discuss the optimal utility-price from an EE perspective. Moreover, we rigorously analyze the behaviour of the network pricing-based resource allocation in two-user case under different noise operating regimes, and discuss the corresponding strategies for achieving energy-efficient transmission, generating water-filling and channel-reversal approaches. To strike a balance between the computational complexity and the optimality, we propose a low-complexity suboptimal algorithm. Furthermore, we extend the proposed algorithm to maximize the EE of multiuser multi-relay full-duplex (FD) relay networks and the relay networks with an eavesdropper. The performance gain of the proposed algorithms is validated through computer simulations.
Original languageEnglish
JournalIEEE Transactions on Signal and Information Processing Over Networks
Early online date1 Feb 2017
Publication statusE-pub ahead of print - 1 Feb 2017


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