Abstract
In this paper, the energy-efficient resource scheduling is investigated considering quality of service (QoS) constraints for OFDMA based heterogeneous network (HetNet). The energy efficiency (EE) is measured as “throughput (bits) per Joule”, while the power consumption model includes RF transmit and circuit power (i.e. feeder loss, cite cooling, signal processing). Compared to existing literature on QoS aware method which mainly consider sum throughput or total transmission power as objective function for optimization, we investigate and model an optimization problem to maximize the EE subject to users' QoS requirements. Given QoS (data rate) requirement for maximizing EE, a constrained based optimization problem is devised. Since the optimization problem is non-convex in nature, we reconstruct the optimization problem as a convex one and devise a pragmatically efficient novel resource assignment algorithm for maximizing achievable EE with quick convergence. The considered optimization problem is transformed into a convex optimization problem by redefining the constraint using the cubic inequality satisfying certain conditions to prove non-negativity, which leads to the problem to be solve as a convex optimization method and results in an efficient iterative resource allocation algorithm. In each iteration, the transformed problem is solved by using Lagrangian dual decomposition with a projected gradient method. Analytical insights and numerical results exhibit the potency of the devised scheme for the targeted complex wireless systems. Our analysis also provides design guidelines for the future design and deployment of green wireless networks as approach the 5G era.
Original language | English |
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Title of host publication | 2015 IEEE International Conference on Communications (ICC) |
Place of Publication | London, UK |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 5954-5960 |
Number of pages | 7 |
ISBN (Electronic) | 978-1-4673-6432-4 |
ISBN (Print) | 978-1-4673-6431-7 |
DOIs | |
Publication status | Published - 10 Sept 2015 |