Abstract
Energy efficiency (EE) optimization is investigated for a multi-user cognitive radio network (CRN) over multiple-input-multiple-output (MIMO) interference channels (ICs). To reduce the system overhead due to information exchange among the secondary CR uses (SUs), the EE optimization problem is formulated as a non-cooperative game, where each SU transmitter competes against the other SU pairs by optimizing its transmit covariance matrix. Specifically, each multi-antenna SU maximizes locally its energy efficiency in terms of the number of bits transmitted per unit energy consumption, subject to the per-SU transmit power constraint and the primary user (PU) perceived total interference constraint. It is proved that the formulated non-cooperative game admits at least one Nash equilibrium (NE), and the sufficient condition for a unique NE is derived subsequently. Primal decomposition is employed in the local EE optimization problem to relax the coupling PU perceived interference constraint such that fully distributed operation is allowed. A distributed iterative EE optimization algorithm (DIEEOA) is then proposed to obtain the unique NE, which is shown to converge to the global optimum. Linear precoding techniques are employed to mitigate the impacts of multi-user interference and imperfect channel state information (CSI). Through numerical simulations, effectiveness of the proposed scheme is validated and the system setting parameters’ impacts on the performance are studied.
Highlights
The number of connected wireless devices is increasing at an unprecedented speed
NUMERICAL RESULTS performance of the proposed game-based distributed EE optimization scheme for multi-user cognitive radio network (CRN) over MIMO interference channels (ICs) is examined through simulation
We consider in the numerical examples a multi-users CRN with K secondary Cognitive radio (CR) uses (SUs) pairs and 1 primary user (PU) pair
Summary
The number of connected wireless devices is increasing at an unprecedented speed. According to the statistical studies in [1], it is forecasted that by 2022, there will be 5.7 billion mobile users and over 12 billion mobile-ready devices and connections globally. N. Wang et al.: Distributed Energy Efficiency Optimization for Multi-User CRNs Over MIMO ICs: A Non-Cooperative Game Approach latency communication (uRLCC), both of which are more focused on MTC applications. While the data rates must be significantly increased in order to meet the ever increasing demand for enhanced wireless broadband, the per-bit energy consumption must be dramatically decreased, say by a factor of 1,000 or more, to maintain or improve the battery lifetime on mobile devices [3] This is especially important to Internet-of-things (IoT) applications and small devices where complexity and resources are highly constrained. We study energy efficiency optimization for multi-user underlay CRN over MIMO interference channels. Both the perfect channel state information (CSI) scenario and the imperfect CSI scenario are considered. The multi-user MIMO interference channel model is presented, followed by a non-cooperation game formulation of the optimization problem.
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