Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems
arXiv:1509.08309 · doi:10.1109/TSP.2016.2626249
Abstract
This paper addresses the problem of resource allocation for systems in which a primary and a secondary link share the available spectrum by an underlay or overlay approach. After observing that such a scenario models both cognitive radio and D2D communications, we formulate the problem as the maximization of the secondary energy efficiency subject to a minimum rate requirement for the primary user. This leads to challenging non-convex, fractional problems. In the underlay scenario, we obtain the global solution by means of a suitable reformulation. In the overlay scenario, two algorithms are proposed. The first one yields a resource allocation fulfilling the first-order optimality conditions of the resource allocation problem, by solving a sequence of easier fractional problems. The second one enjoys a weaker optimality claim, but an even lower computational complexity. Numerical results demonstrate the merits of the proposed algorithms both in terms of energy-efficient performance and complexity, also showing that the two proposed algorithms for the overlay scenario perform very similarly, despite the different complexity.
to appear in IEEE Transactions on Signal Processing
References in corpus (7)
- Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks
- Energy-Efficient Power Control: A Look at 5G Wireless Technologies
- A Tutorial on the Optimization of Amplify-and-Forward MIMO Relay Systems
- Energy-Efficient Resource Allocation for Device-to-Device Underlay Communication
- Dynamic Power Control for Delay-Aware Device-to-Device Communications
- Energy Efficiency and Sum Rate when Massive MIMO meets Device-to-Device Communication
- An Energy-Efficient Framework for the Analysis of MIMO Slow Fading Channels
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- Energy Efficiency of Rate-Splitting Multiple Access, and Performance Benefits over SDMA and NOMA
- Rate-Splitting to Mitigate Residual Transceiver Hardware Impairments in Massive MIMO Systems
- Autonomous Power Allocation based on Distributed Deep Learning for Device-to-Device Communication Underlaying Cellular Network