Effective 5G Wireless Downlink Scheduling and Resource Allocation in Cyber-Physical Systems

Abstract

In emerging Cyber-Physical Systems (CPS), the demand for higher communication performance and enhanced wireless connectivity is increasing fast. To address the issue, in our recent work, we proposed a dynamic programming algorithm with polynomial time complexity for effective cross-layer downlink Scheduling and Resource Allocation (SRA) considering the channel and queue state, while supporting fairness. In this paper, we extend the SRA algorithm to consider 5G use-cases, namely enhanced Machine Type Communication (eMTC), Ultra-Reliable Low Latency Communication (URLLC) and enhanced Mobile BroadBand (eMBB). In a simulation study, we evaluate the performance of our SRA algorithm in comparison to an advanced greedy cross-layer algorithm for eMTC, URLLC and LTE (long-term evolution). For eMTC and URLLC, our SRA method outperforms the greedy approach by up to 17.24%, 18.1%, 2.5% and 1.5% in terms of average goodput, correlation impact, goodput fairness and delay fairness, respectively. In the case of LTE, our approach outperforms the greedy method by 60%, 2.6% and 1.6% in terms of goodput, goodput fairness and delay fairness compared with tested baseline.

Comparative Analysis of Scheduling Algorithms in 5G Uplink Transmission

“…The goodput illustrates the successful delivery of data packets to the UE. It does not take into consideration packet retransmissions and thus the value for goodput is lower than for throughput [25]. The goodput can be expressed as follows [13]:…”

Time-based resource allocation for downlink in heterogeneous wireless cellular networks

“…The authors in [25] further compared the performance of different approaches for user association and RA. In [26], three use cases in HWCNs were investigated, including mobile broadband, machine-type communication and ultra-reliable low-latency communication, with the deployment of scheduling and RA optimisation.…”

Ultra-Reliable Low-Latency Communication (URLLC) in 5G Networks: Enabling Mission-Critical Applications

“…techniques simulate and examine URLLC behavior under various network conditions and traffic scenarios using tools for network simulation, such as ns-3, OPNET, or MATLAB/Simulink. Researchers can explore the effects of many parameters on URLLC performance through simulations, including channel conditions, mobility patterns, and resource allocation schemes(Vora & Kang, 2018).Experimental Testbeds: To simulate URLLC communication in controlled situations, experimental testbeds deploy real-world hardware and software components. optimizing URLLC performance while lowering resource and energy overhead.…”