Improved Resource Allocation in 5G MTC Networks

Effective resource allocation has always been one of the serious challenges in wireless communication. A considerable number of machine type communication (MTC) devices in 5G with variable quality of service (QoS) aggravates this challenge even further. Existing Resource allocation schemes in MTC are usually considering signal to noise ratio (SNR), which provides preference to MTC devices based on distance rather than their QoS requirements. This paper proposes a resource allocation scheme with dynamic priorities for MTC devices with multiple radio access technologies (RATs). The proposed resource allocation scheme has two main parts namely medium access and resource allocation. The medium access leverages the broadcast nature of wireless signal and MTC devices' wait time to assign priorities using capillary band in a secure and integral way. At resource allocation, SNR, total induced transmission delay, and transmission-Awaiting MTC devices are used to assign resources in the cellular band. The rumination of two-staged dynamic priorities in the proposed scheduling scheme brings significant performance improvements in outage and success probabilities. Compared to SNR-based schemes, the proposed mechanism performs well by expressively improving the outage and success probability by 20% and 30%, respectively.1

Efficient Resource Allocation of Latency Aware Slices for 5G Networks

It’s noticed that 5G mobile networks are considered to be an emerging technology that serve multiple users with varying types of applications having different quality of service (QoS) needs. Network slicing enables us to accommodate diverse services on the same infrastructure by using multiple virtual networks on the same physical infrastructure of the network. In this paper, a resource allocation framework to fairly share the network resources among different slices subject to delay sensitive requirements based on the priority factor of each slice to use the available radio resources efficiently is proposed. This priority factor depends on the weight of each slice and considering the quality of service of each one. The proposed framework ensures that each slice can share the high limits of allowable resources to achieve the least allowable latency as it is the most significant feature in 5G cellular networks. Packet loss and packet scheduling delay are used as performance metrics when comparing with other existing resource allocation algorithms. The simulation validated that our framework could serve the delay sensitive slices with the least allowable delay and a guaranteed throughput

Rate-Splitting Random Access Mechanism for Massive Machine Type Communications in 5G Cellular Internet-of-Things

The cellular Internet-of-Things has resulted in the deployment of millions of machine type communication (MTC) devices under the coverage of a single gNodeB (gNB). These massive number of devices should connect to the gNodeB (gNB) via the random access channel (RACH) mechanism. Moreover, the existing RACH mechanisms are inefficient when dealing with such large number of devices. To address this issue, we propose the rate-splitting random access (RSRA) mechanism, which uses rate splitting and decoding in rate-splitting multiple access (RSMA), to improve the RACH success rate. The proposed mechanism divides the message into common and private messages and enhances the decoding performance. We demonstrate, using extensive simulations, that the proposed RSRA mechanism significantly improves the success rate of MTC in cellular IoT networks. We also evaluate the performance of the proposed mechanism with increasing number of devices and received power difference. © 2021 IEEE