In this work, a multiple user deep neural network-based non-orthogonal multiple access
(NOMA) receiver is investigated considering channel estimation error. The decoding of the …

In this paper, we explore the possibilities and advantages of cooperative relaying with the
addition of non-orthogonal multiple access (NOMA). First, the possibilities of NOMA for fifth …

We present a new noise‐resilient secondary control scheme for voltage and frequency
synchronisation of an autonomous microgrid (MG). The communication network is an …

Fifth generation (5G) wireless networks' system performance is dependent on having perfect
knowledge of the channel state information (CSI). Deep learning (DL) has helped improve …

In the current scenario, where all the services have become online, the demand for
increased capacity, low symbol error rate (SER), better data rate, and low latency with high …

In this letter, we propose a handover-count based minimum-variance-unbiased (MVU)
estimate of user velocity in heterogeneous-networks (HetNets). Since mobility management …

In modern wireless communication scenarios, non-orthogonal multiple access (NOMA)
provides high throughput and spectral efficiency for fifth generation (5G) and beyond 5G …

Non-orthogonal multiple access (NOMA) networks play an important role in defense
communication scenarios. Deep learning (DL)-based solutions are being considered as …

With the tremendous increase in wireless user traffic, investigation on the end-to-end
reliability of wireless networks in practical conditions such as non-homogeneous fading …

In order to maximize energy efficiency in heterogeneous networks (HetNets), a turbo Q-
Learning (TQL) combined with multistage decision process and tabular Q-Learning is …