Optimization of Weighted Individual Energy Efficiencies in Interference Network
arXiv:1804.08926 · doi:10.1109/WCNC.2018.8377255
Abstract
This paper studies the maximization of the weighted sum energy efficiency (WSEE). We derive a first-order optimal algorithm applicable to a wide class of communication scenarios exhibiting very fast convergence. We also discuss how to leverage monotonic optimization and fractional programming to obtain a global optimal solution at the cost of higher computational complexity. The WSEE of interference networks is studied in detail with an application to relay-assisted multi-cell communication. This scenario is modeled as a non-regenerative multi-way relay channel and the achievable rate region is derived. We apply the proposed algorithm to this scenario and compare its performance to the global optimal algorithm. The results indicate that the proposed algorithm often achieves the global optimal solution and is close to it otherwise. Convergence is achieved within 10 iterations, while the global optimal solution may require more than iterations.
arXiv commentPresented at IEEE Wireless Communications and Networking Conference (WCNC) Barcelona, Spain
References in corpus (7)
- Practical Non-linear Energy Harvesting Model and Resource Allocation for SWIPT Systems
- Energy-Efficient Power Control: A Look at 5G Wireless Technologies
- Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks
- Energy-Efficient Scheduling and Power Allocation in Downlink OFDMA Networks with Base Station Coordination
- A Unified Successive Pseudo-Convex Approximation Framework
- Energy-Efficient Beam Coordination Strategies with Rate Dependent Processing Power
- Instantaneous Relaying for the 3-Way Relay Channel with Circular Message Exchanges
Cited by in corpus (5)
- A Globally Optimal Energy-Efficient Power Control Framework and its Efficient Implementation in Wireless Interference Networks
- Mixed Monotonic Programming for Fast Global Optimization
- Graph-based Algorithm Unfolding for Energy-aware Power Allocation in Wireless Networks
- Efficient Global Optimal Resource Allocation in Non-Orthogonal Interference Networks
- Learning to Transmit with Provable Guarantees in Wireless Federated Learning