This study addresses the energy efficiency (EE) maximisation problem in multi-input multi-output cognitive relay networks, where a secondary transmitter-receiver pair communicates through an amplify-and-forward relay ...
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This study addresses the energy efficiency (EE) maximisation problem in multi-input multi-output cognitive relay networks, where a secondary transmitter-receiver pair communicates through an amplify-and-forward relay using the licenced spectrum of a primary user. The authors aim to maximise the EE of the secondary system by jointly designing the source and relay precoding matrices, subject to transmit power, interference, and quality-of-service constraints. The resultant problem is non-convex in the precodingmatrices;it is converted into a much simpler vector-valued problem using singular value decomposition. A combination of iterative optimisation, fractional programming, and Lagrangian multiplier is used to further tackle the problem. Numerical results are presented to evaluate the EE performance of the proposed scheme. Impact of transmit power, interference threshold, and minimum rate requirement on the EE is analysed.
In this work, the authors investigate a multi-user multi-input multi-output (MIMO) interference relay system, where several transmitter nodes simultaneously communicate with their respective receiver nodes through hal...
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In this work, the authors investigate a multi-user multi-input multi-output (MIMO) interference relay system, where several transmitter nodes simultaneously communicate with their respective receiver nodes through half-duplex MIMO amplify and forward (AF) relay nodes. For this system configuration, they address the problem of linear transceiver-relay design to achieve max-min fairness among all the users' data streams. Assuming perfect channel state information, this problem is formulated as the maximisation of the minimum signal-to-interference-plus-noise ratio (SINR) per stream among all the users subject to transmit power constraints at the transmitter and relay nodes. Since the formulated problem of jointly optimising all the transmitters, relays and receivers is non-convex, a globally optimal solution cannot be easily obtained. Therefore, they propose a quasi-optimal iterative algorithm to jointly optimise the transmitter precoders, relay precoding matrices and receiver filters for all the users and relays such that the minimum per stream received SINR is improved at each iteration. Simulation results show that the proposed algorithm improves fairness among data-streams of all users and outperforms existing strategies in terms of minimum user rate and bit error rate.
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