Cooperative Scheduler to Enhance Massive Connectivity in 5G and Beyond by Minimizing Interference in OMA and NOMA

Mwakwata, Collins Burton; Elgarhy, Osama; Alam, Muhammad Mahtab; Moullec, Yannick Le; Pärand, Sven; Trichias, Konstantinos; Ramantas, Kostas

doi:10.1109/jsyst.2021.3114338

Cited by 12 publications

(7 citation statements)

References 27 publications

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“…In the considered scenario, cellular base stations supporting NB-IoT services share their scheduling table for inter-cell interference avoidance scheduling. Mwakwata et al also investigated the impact of a designed cooperative scheduler for orthogonal multiple access and non-orthogonal multiple access scenarios in cellular networks with massive connectivity [ 13 ]. Li and Cai investigated cooperative control methods for uplink transmissions in cellular networks by considering device-to-device relay transmissions and network coding in dense areas [ 14 ].…”

Section: Related Workmentioning

confidence: 99%

Lyapunov Drift-Plus-Penalty-Based Cooperative Uplink Scheduling in Dense Wi-Fi Networks

Kim,

Kim

2024

Sensors

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In high-density network environments with multiple access points (APs) and stations, individual uplink scheduling by each AP can severely interfere with the uplink transmissions of neighboring APs and their associated stations. In congested areas where concurrent uplink transmissions may lead to significant interference, it would be beneficial to deploy a cooperative scheduler or a central coordinating entity responsible for orchestrating cooperative uplink scheduling by assigning several neighboring APs to support the uplink transmission of a single station within a proximate service area to alleviate the excessive interference. Cooperative uplink scheduling facilitated by cooperative information sharing and management is poised to improve the likelihood of successful uplink transmissions in areas with a high concentration of APs and stations. Nonetheless, it is crucial to account for the queue stability of the stations and the potential delays arising from information exchange and the decision-making process in uplink scheduling to maintain the overall effectiveness of the cooperative approach. In this paper, we propose a Lyapunov drift-plus-penalty framework-based cooperative uplink scheduling method for densely populated Wi-Fi networks. The cooperative scheduler aggregates information, such as signal-to-interference-plus-noise ratio (SINR) and queue status. During the aggregation procedure, propagation delays are also estimated and utilized as a value of expected cooperation delays in scheduling decisions. Upon aggregating the information, the cooperative scheduler calculates the Lyapunov drift-plus-penalty value, incorporating a predefined model parameter to adjust the system accordingly. Among the possible scheduling candidates, the proposed method proceeds to make uplink decisions that aim to reduce the upper bound of the Lyapunov drift-plus-penalty value, thereby improving the network performance and stability without a severe increase in cooperation delay in highly congested areas. Through comprehensive performance evaluations, the proposed method effectively enhances network performance with an appropriate model parameter. The performance improvement is particularly notable in highly congested areas and is achieved without a severe increase in cooperation delays.

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Section: Related Workmentioning

confidence: 99%

Lyapunov Drift-Plus-Penalty-Based Cooperative Uplink Scheduling in Dense Wi-Fi Networks

Kim,

Kim

2024

Sensors

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“…This fact motivated us to study high-dimensional incidence matrices. On the other hand, it is well known that ongoing research is trying to find an optimized scheduler in the power domain NOMA, such as [11] and [12]. However, the incidence matrix, which is the counterpart of the scheduler in code domain NOMA, has received little attention.…”

Section: Introductionmentioning

confidence: 99%

Design of Incidence Matrices With Limited Constellation Expansion in Massive Connectivity NOMA Systems

2023

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Non-orthogonal multiple-access (NOMA) is designed to transmit massive amounts of user communications. The incidence matrix manages the relationship between users and resources. This study focused on increasing user supportability and complexity reduction using larger incidence matrices. Our approach to optimizing the incidence matrix to improve system capacity and reduce complexity is based on two critical mathematical concepts: Parallel classes in hypergraph theory and combinatorial designs allow us to explore and extend incidence matrices. Frame theory is used to estimate matrix structures. Then, we investigate applications utilizing our incidence matrix designs-Simple Orthogonal Multi-Arrays (SOMA). The characteristics of SOMA reflect the unique Latin Square pattern, allowing us to produce a highly flexible and fair resource allocation matrix. SOMA designs let us support overload factors over 500%. The theoretical performance analysis equations of our NOMA system were established to support dynamic adaptability and optimization. We implemented and evaluated security methods for eavesdroppers. The prototype of the user hierarchy allows a higher-priority group to have a lower error rate without significantly affecting the system's performance. Finally, the Monte Carlo simulation indicated that our NOMA systems allow higher degrees of freedom and lower complexity than other NOMA schemes while maintaining graceful error rates with a maximum 33% improvement.INDEX TERMS Incidence matrix, NOMA, combinatorial design, frame theory, SOMA.

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“…Other methods include assigning orthogonal resources in a time-frequency grid to achieve high spectrum and throughput efficiency.The latest 5G deployments use Orthogonal Multiple Access (OMA) systems, which provide orthogonality in terms of frequency resources [12]. In this context, proactive scheduling and sophisticated multiple access mechanisms are required as proposed in our earlier study [13].…”

Section: Introductionmentioning

confidence: 99%

“…The main two differences between this paper and [13] are 1) an interference minimization problem for stand-alone O-DU for O-RAN is formulated and 2) the problem is further extended to a coordinated O-DU case. The power and resource scheduling for both stand-alone and coordinated O-DU is carried out for NOMA and compared with OMA.…”

Section: Introductionmentioning

confidence: 99%

Inter O-DUs Coordination for Scheduling of Massive Users in O-RAN

Latif

Alam

Moullec

2023

2023 Joint European Conference on Networks and Communications &Amp; 6G Summit (EuCNC/6G Summit)

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Open Radio Access Network (O-RAN) is a decentralized, intelligent, and open network architecture. RAN Network Functions (RNF) are split into Open Central Unit (O-CU), Open Distributed Unit (O-DU), and Open Radio Unit (O-RU), which are deployed on commercial hardware and cloud nodes as containerized Network Functions (CNFs). This paper presents a coordination architecture between O-RAN Distributed Units (O-DU) for scheduling a massive number of users. We propose a Non-Orthogonal Multiple Access (NOMA) based access technique for interference avoidance and scheduling of such a massive number of users through a cooperative strategy. This involves sharing individual scheduling tables to compute interference for subsequent User Equipment (UEs) transmissions in the network. The results of the interference calculations are then fed into O-DU schedulers. The scheduler of each O-DU shares the radio resources among the UEs to have minimum interference.The proposed scheme's effectiveness in terms of throughput, energy efficiency, and connectivity is examined through simulations. The results show that the proposed method reduces the effects of interference, making it better suited to the needs of dense deployments. Users operating under the proposed approach experience up to +30% and -10% improvements in achieved user data rates and energy consumption, respectively, when compared to the absence of a coordination architecture.

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Cooperative Scheduler to Enhance Massive Connectivity in 5G and Beyond by Minimizing Interference in OMA and NOMA

Cited by 12 publications

References 27 publications

Lyapunov Drift-Plus-Penalty-Based Cooperative Uplink Scheduling in Dense Wi-Fi Networks

Lyapunov Drift-Plus-Penalty-Based Cooperative Uplink Scheduling in Dense Wi-Fi Networks

Design of Incidence Matrices With Limited Constellation Expansion in Massive Connectivity NOMA Systems

Inter O-DUs Coordination for Scheduling of Massive Users in O-RAN

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