• C.Sowjanya
• Prof. RVS Satyanarayana

Device-to-device (D2D) communications as underlays of cellular networks facilitate diverse local services and reduce base station traffic. However, D2D communication may cause interference with the primary cellular network. To avoid this problem, the network should flexibly allocate its resources and select a proper mode for users. Here, we formulate a joint mode selection and resource allocation problem to maximize the system throughput with a minimum required rate guarantee. A mode selection and resource allocation scheme based on particle swarm optimization (PSO) is proposed in which solutions are mapped onto particles and a fitness function embodies the constraints in a penalty function. Simulation results show its superiority over other schemes in terms of throughput and minimum required rate guarantee. This paper considers the design of optimal resource allocation policies in wireless communication systems which are generically modelled as a functional optimization problem with stochastic constraints. These optimization problems have the structure of a learning problem in which the statistical loss appears as a constraint, motivating the development of learning methodologies to attempt their solution. To handle stochastic constraints, training is undertaken in the dual domain. It is shown that this can be done with small loss of optimality when using near-universal learning parameterizations. In particular, since deep neural networks PSO and DNN are near-universal their use is advocated and explored. PSO are trained here with a model-free primal-dual method that simultaneously learns a PSO parameterization of the resource allocation policy and optimizes the primal and dual variables. Numerical simulations demonstrate the strong performance of the proposed approach on a number of common wireless resource allocation problems. The proposed system developed on MATLAB 2015b version.

particle swarm optimization (PSO), DNN, Prime dual learning, Device-to-device (D2D) etc.

"Resource Allocation Using Particle Swarm Optimization (PSO) in Wireless Networks ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.k55-k66, June-2022, Available :http://www.jetir.org/papers/JETIR2206A07.pdf

"Resource Allocation Using Particle Swarm Optimization (PSO) in Wireless Networks ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. ppk55-k66, June-2022, Available at : http://www.jetir.org/papers/JETIR2206A07.pdf