Joint channel pairing and power allocation optimization in two-way multichannel relaying.

We consider two-way amplify-and-forward relaying in a multichannel system with two end nodes and a single relay, using a two-slot multi-access broadcast (MABC) as well as time-division broadcast (TDBC) relaying strategies. We investigate the problem of joint subchannel pairing and power allocation to maximize the achievable sum-rate in the network, under an individual power budget at each node. To solve this challenging joint optimization problem, an iterative approach is proposed to decompose the problem into pairing optimization and joint power allocation optimization, and solve them iteratively. For given power allocation, we first consider the problem of subchannel pairing at the relay to maximize the achievable sum rate in TDBC-based network. Unlike in the one-way relaying case, our result shows that there exists no explicit SNR-based subchannel pairing strategy that is optimal for sum-rate maximization for two-way relaying. Nonetheless, for TDBC-based two way relaying, we formulate the pairing optimization as an axial 3-D assignment problem which is NP-hard, and propose an iterative optimization method to solve it with complexity O(N3). Based on SNR over each subchannel, we also propose sorting-based algorithms for scenarios with and without direct link, with a low complexity of O(N logN). For the joint power allocation at the relay and the two end nodes, we propose another iterative optimization procedure to optimize the power at the two end nodes and at the relay iteratively. By using different forms of optimization parameters, the sum-rate maximization problem turns out to be convex and the optimal solutions can be obtained for each subproblem. The simulation first demonstrates the proposed sorting-based pairing algorithm offers the performance very close to the iterative optimization method. Then, shows the gain of joint optimization approach over other pairing-only or power-allocation-only optimization approaches

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