Efficient multiobjective optimization And resource allocation of massive Mimo for high speed 5g communication Systems

Abstract

Fifth Generation (5G) communication technology eases newlineinterconnection of heterogeneous devices to meet the end-user demands in a newlineservice-centric manner. The conventional issues such as infrastructure, newlinecoalition, communication mode, mobility, etc. are addressed using rapid and newlineadaptive interconnecting methods in 5G. In particular, the resource constraint newlinenature of the devices in the communication network is a common problem newlinethat defaces the performance of data and service sharing. 5G communications newlineoffer high bandwidth and less latency for service-oriented approaches in the newlinedistributed platform. The quality of service (QoS) and quality of experience newline(QoE) of the users are leveraged in this scope of 5G services. 5G technologies newlineformulate the multiple usages of devices such as camera, MP3, audio player newlineetc. This gives the end user and service consumers to acquire information and newlineexchange data through short-range communication devices. However, newlineresource allocation is a commanding optimization that is required to leverage newlinethe performance of users by satisfying QoS and QoE. Besides, multi-input newlinemulti-output (MIMO), technique requires complex resource allocation and newlinehence retaining the support for diverse applications and services to meet the newlineuser demands. This research work focuses on improving the resource newlineallocation features of 5G network through different proposals that balances newlinethe resource availability and service responses in an optimal manner. newlineThe first proposal introduces a multi-objective optimization for newlineresource allocation in 5G massive MIMO. This resource allocation is newlinefacilitated using deep neural network (DNN). This method is named as multiobjective newlinesine cosine algorithm (MOSCA) that considers signal-interference newlinenoise ratio (SINR), energy utilization and energy efficiency (EE) for optimal newlineresource allocation process newline