Multi-antenna relay network beamforming design for multiuser peer-to-peer communications.

In this work, we consider a multi-user peer-to-peer relay network with multiple multiantenna relays which employ amplify-and-forward relaying protocol. Assuming distributed relay beamforming strategy, we investigate the design of each relay processing matrix to minimize the per-antenna relay power usage for given users??? Signal-to-Noise Ratio (SNR) targets. As the problem is NP-hard, we develop an approximate solution through the Lagrange dual domain. Through a sequence of transformations, we obtain a semi-closed form solution which can be determined by solving an efficient semi-definite programming problem. We also consider the semi-definite relaxation (SDR) approach. Compared with this SDR approach, the proposed solution has significantly lower computational complexity. The benefit of such a solution is apparent when the optimal solution can be obtained by both approaches. When the solution is suboptimal, simulations show that the SDR approach has better performance. Thus, we propose a combined method of the two approaches to trade-off performance and complexity. Simulations showed the effectiveness of such a combined method. In the next step, we change the previous objective and constraints to turn the optimization problem into a total power minimization problem for the relay network. We use an approximation by solving this problem in the Lagrange dual domain, and we finally obtain a semi-closed form solution through the dual approach. The use of the SDR approach to solve this problem is also discussed. After analysis, we find the two methods have an advantage over different aspects, thus we propose a combined method for this problem. We eventually compare the two combined methods to see the performance difference in the per-antenna power case and the total relay power case, and discuss reasons for this difference

Power efficient designs for 5G wireless networks

In this dissertation, to step forward towards green communication, we study power efficient solutions in three potential 5G wireless networks, namely an asynchronous multicarrier two-way Amplify-and-Forward (AF) relay network, a multi-carrier two-way Filter-and-Forward (FF) network, and a massive Multiple Input Multiple Output (MIMO) network using the Non-Orthogonal Multiple Access (NOMA) scheme. In the first network, two transceivers using the Orthogonal Frequency Division Multiplexing (OFDM) scheme communicate through multiple relays in an asynchronous manner. As an attempt to design a simple solution, we assume the AF protocol at the relays. We jointly design the power allocation and distributed beamforming coefficients to minimize the total transmission power subject to sum-rate constraints. We propose an optimal semi-closed form solution to this problem and we show that at the optimum, the end-to-end channel has only one non-zero tap. To extend the first work to high data-rate scenarios, we consider a second relaying-based network which consists of two OFDM-based transceivers and multiple FF relays. We propose two approaches to tackle a total transmission power minimization problem: a gradient steepest descent-based technique, and a low-complexity method enforcing a frequency-flat Channel Impulse Response (CIR) response at the optimum. As the last network, we consider a massive MIMO-NOMA network with both co-located and distributed structures. We study the joint problem of power allocation and user clustering to minimize the total transmit power subject to QoS constraints. We propose a novel clustering algorithm which groups the correlated users into the same cluster and has an unique ability to automatically switch between using the spatial-domain-MIMO and the power-domain-NOMA. We show that our proposed method can substantially improve the feasibility probability and power consumption performance compared to existing methods