QoS-Aware Energy-Efficient Downlink Predictive Scheduler for OFDMA-Based Cellular Devices

• Published in: IEEE transactions on vehicular technology Vol. 66; no. 2; pp. 1468 - 1483
• Main Authors: Hammad, Karim, Primak, Serguei L., Kalil, Mohamad, Shami, Abdallah
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cloud computing; Cloud radio access networks (C-RANs); Downlink; Energy consumption; energy-efficient communications; Frequency division multiple access; Multiple objective analysis; Optimization; Orthogonal Frequency Division Multiplexing; orthogonal frequency-division multiple access (OFDMA); Quality of service; ray tracing (RT); Receivers; resource allocation; Resource management; Scheduling
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2016.2555293

We propose a predictive energy-efficient scheduling scheme that optimizes the user equipment (UE)'s bits/joule metric subject to quality-of-service (QoS) constraints in downlink orthogonal frequency-division multiple access (OFDMA) systems. This is achieved by minimizing the number of wake-up transmission time intervals (TTIs), where the UE receiver circuit is on, in a longer time horizon than studied before. The proposed predictive scheduler is supported by a ray-tracing (RT) engine that increases the scheduler's knowledge by long-term information about the users' propagation characteristics. A convex multiobjective binary-integer-programming formulation for the problem is presented to optimize both the UE's energy efficiency (EE) and QoS. The multiobjective formulation is then used for benchmarking of a low-complexity and computationally efficient heuristic scheduler. The results show that the proposed schedulers have significantly improved the UE's EE and the overall capacity of the system, compared with a recently published EE scheduling scheme while maintaining target QoS.