A maximum power point tracking (MPPT) technique plays an important role to ensure maximum photovoltaic (PV) output power is extracted under stochastic weather conditions. The research to date tends to focus on developing a standalone optimization MPPT algorithm rather than looking into a hybrid MPPT algorithm. This paper introduces particle swarm optimization (PSO) to optimize the maximum PV output power and to determine the best design variable for penalising the step size of the conventional methods namely the perturb and observe (PO) and the incremental conductance (IC). With the help of the hybrid MPPT algorithm (PSO+IC and PSO+PO), the step size is no longer fixed, and it is changing according to the solar irradiance. To evaluate the proposed hybrid algorithm, a single-stage grid connected PV system is designed for several different scenarios with various weather conditions. The performance of the hybrid MPPT algorithm and the conventional methods is compared. The results demonstrate that the hybrid MPPT algorithm is remarkably better than the conventional methods in terms of the output power ripple and the settling time.

Non-orthogonal multiple access (NOMA) scheme is emerging as an enabling technology for 5G wireless networks, which address the growing demand for capacity that is mostly made up of high quality video content. In this paper, by combining the principles of NOMA and layered coding, the sum rate is enhanced for multicast video streaming. An optimization problem for power allocation is formulated to maximize the overall sum rate whilst achieving the total transmission power constraints and target rates. A near-optimal scheme and a low-complexity closed form solution are proposed. Numerical simulation results show that the proposed schemes offer better sum rate performance than the existing schemes. The closed form solution incurs performance degradation relative to the near-optimal solution but with a much lower complexity. Furthermore, the proposed schemes provide a superior degree of fairness towards the users with poor channel conditions.

The application of non-orthogonal multiple access (NOMA) to multi-layer multicast video streaming is envisioned to address the explosively growing demand for capacity which is dominated mostly by multimedia content. In this paper, a joint power allocation and subgrouping scheme is developed to enhance the performance of NOMA-based multi-layer multicast systems. An optimization problem is formulated to maximize the overall sum multicast rate whilst satisfying the maximum transmission power and proportional rate constraints. Due to the complexity of the optimization problem, we first derive two power allocation techniques for the 2-layer case considering arbitrary subgrouping which are based on the iterative implementation and closed-form analysis, respectively. We then generalize the lowcomplexity closed-form solution for the general multi-layer case. This scheme successively allocates power to each layer stream while assuring that the minimum target rate and proportionality are guaranteed, particularly for the transmission rate of the highpriority base layer stream. A sub-optimal joint power allocation and subgrouping scheme is also designed by incorporating the power allocation scheme into the proposed iterative subgrouping techniques. Simulation results show the effectiveness of the power allocation and subgrouping schemes in enhancing the sum multicast rate performance. In addition, the proposed power allocation scheme ensures substantially higher rates for the base layer stream, which is crucial in robust delivery of standard quality video to all users.

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