2026· IEEE Transactions on Wireless Communications· Vol 25, pp. 20977-20990· 0 citations· 38 references
Abstract
The next generation of wireless systems extends ultra-reliable low-latency communications (URLLC) to the realm of massive connections, termed mURLLC. To address the inherent conflict between stringent quality of service (QoS) requirements in URLLC and the problem of severe and highly fluctuating interference behind demands of massive connectivity, effective fast fading (FF) mitigation and resource allocation strategies are crucial. Through in-depth analysis of FF characteristics, this paper derives optimized configurations for two FF mitigation approaches: protection margin reservation and $K$ -repetition. Furthermore, we integrate these FF mitigation strategies into a hierarchical-clustering (HC)-based resource allocation algorithm for configured-grant in mURLLC. This results in a highly practical and efficient algorithm for managing radio resources and interference in mURLLC scenarios. Simulation results demonstrate that our proposed algorithm achieves over 65% reduction in resource consumption without compromising reliability, significantly enhancing network capacity to support demanding mURLLC applications.
Efficient frequency allocation in device-to-device (D2D) communication remains a critical challenge due to the need to mitigate interference while maintaining high quality of service (QoS). Traditional static allocation methods fail to adapt to dynamic network conditions, leading to inefficient spectrum utilization and degraded performance. This paper proposes a dynamic clustering-based adaptive frequency allocation (DCB-AFA) framework to address these limitations in wireless networks operating under continuously changing environments. The proposed approach leverages user location information and communication patterns to form adaptive clusters that minimize intra-network interference while enabling efficient D2D connectivity. A machine learning-based prediction mechanism is incorporated to anticipate user behavior and dynamically adjust cluster boundaries and resource allocation strategies. Furthermore, a QoS-aware feedback system continuously monitors network conditions and refines allocation decisions to improve performance metrics such as throughput, latency, and energy efficiency. Experimental evaluation demonstrates that the proposed DCB-AFA scheme significantly enhances spectrum utilization, reduces interference, and lowers power consumption compared to conventional approaches, making it a robust solution for next-generation wireless networks.
Noor Ahmad, D. Bhardwaj· Journal of High Speed Networ...· 0 citations
As wireless networks transition toward the 6G era, supporting strictly heterogeneous services such as eMBB, URLLC, and mMTC over a unified infrastructure becomes a fundamental challenge. Traditional Radio Access Network (RAN) slicing often relies on upper-layer logical abstractions, which fail to address physical inter-slice interference and the boundary effect of cellular architectures. This paper proposes a novel Profile-Aware Hierarchical RAN Slicing Framework for User-Centric Cell-Free Massive MIMO systems to overcome these limitations. The proposed framework comprises four hierarchical stages: utility-based profile-aware clustering, dynamic inter-slice resource partitioning for power and bandwidth, hybrid central processing unit-to-access point power budgeting, and real-time power allocation using a Bipartite Graph Convolutional Network (BiGCN). By incorporating service-specific requirements into physical layer resource management, the framework ensures strict quality-of-service isolation and global energy efficiency. Simulation results demonstrate that the proposed integrated framework achieves a high Jain’s Fairness Index, exceeding 0.95 for most profiles and provides up to a 48-fold energy efficiency improvement for battery-constrained devices compared to non-slicing baselines. Furthermore, the BiGCN-based allocation module attains near-optimal performance with millisecond-level inference latency, confirming its feasibility for mission-critical real-time applications. This comprehensive approach effectively eliminates the trade-off between aggregate throughput and individual reliability, providing a scalable solution for next-generation sliced networks.
Ja-Eun Kim, Hye-Yoon Jeong, Ji-Woo Lee et al.· IEEE Access· 0 citations
This article addresses the planning and allocation of spectral resource blocks for unicast (UC) and Multicast-Broadcast Single Frequency Network (MB-SFN) transmissions in dense Sixth-Generation (6G) cellular networks, where the choice of transmission mode directly influences spectral efficiency and Quality of Service (QoS). The objective is to identify the conditions under which the intercellular cooperation inherent to MB-SFN becomes more efficient than the UC mode for spectral resource block utilization under QoS constraints. To this end, we conduct a comparative performance analysis based on: i) Monte Carlo (MC) simulations, used as a numerical benchmark to accurately capture complex radio interactions, and ii) a fluid analytical framework, based on a continuous approximation of the network in which the discrete structure of base stations is replaced by a homogeneous surface density. Within this framework, we derive analytical expressions for the Signal-to-Interference-plus-Noise Ratio (SINR), enabling a tractable characterization of aggregate interference. Resource block allocation expressions are then proposed for both modes, incorporating SINR and outage probability as QoS constraints. The main contribution of this paper lies in deriving, using the fluid framework, an explicit analytical expression for the critical user threshold that characterizes the switch from UC mode to MB-SFN mode, beyond which the latter becomes more spectrum-efficient. The switching decision highlights the duality between the two modes: MB-SFN is constrained by the minimum SINR with resource consumption independent of the number of users, whereas UC mode depends on the average SINR and consumption proportional to the number of users. An in-depth analysis of the combined effect of network parameters is also conducted, highlighting their interactions and their influence on the switching threshold. Finally, the strong agreement with MC simulations validates the accuracy of the fluid framework, providing an effective analytical tool for optimizing adaptive transmission strategies.
M. Younes, C. Perrine· IEEE Open Journal of the Com...· 0 citations
This manuscript investigates the challenges arising from the interaction between cell discontinuous transmission/reception (DTX/DRX) for network energy saving (NES) and contention-based random access (CBRA) in 5G new radio (NR) networks and beyond. While cell DTX/DRX significantly reduces network power consumption, it can negatively impact CBRA performance by increasing access delay and reducing the success rate. To address these issues, we propose two enhanced CBRA schemes with mathematical modeling and Monte Carlo simulation results demonstrating significant improvements in CBRA performance under dense 5G NR and 6G NES environments. The first scheme introduces a Secondary MSG1 Opportunity to dynamically allocate radio resources and mitigate collisions. The second scheme employs Multiple Uplink (UL) Grant Occasions for MSG3 to reduce contention among User Equipments (UEs). We detail the operation of the proposed CBRA schemes and analyze their potential to improve CBRA performance in 5G NR and beyond, while effectively supporting NES.
Jisoo Park, J. Ahn, Junhwan Lee· International Conference on...· 0 citations
This formulation provides a rigorous and tractable framework for distributed spectrum sharing in 6G O-RAN systems, with the potential to support intelligent and adaptive control in future wireless networks.
E. Spyrou, Chrysostomos D. Stylios, V. Kappatos et al.· Future Internet· 0 citations
Link 16 is a frequency-hopping tactical data link that employs four statically assigned Message Packing Structures (MPSs), each imposing a fixed trade-off among throughput, slot efficiency, and anti-jamming protection. Because these assignments are fixed prior to deployment, current Link 16 networks cannot adapt to runtime variations in traffic load, communication range, or interference conditions, often resulting in inefficient slot utilization. This paper proposes a simulation-based dynamic message packing framework that enables runtime MPS selection based on queue occupancy and inter-participant distance while preserving the standard TDMA structure and waveform. To address contested electromagnetic environments, the baseline mechanism is extended with a lightweight interference-aware component that biases MPS selection toward protection-capable structures based on estimated jammer severity, without altering the underlying adaptation triggers. The proposed framework is implemented in a C++ Link 16 simulation environment and evaluated under five operational scenarios, including non-congested and congested traffic, static and dynamic communication ranges, and probabilistic jammer interference. Results show that under non-congested conditions, the mechanism remains throughput-neutral, with the number of transmitted MPSs closely matching the number of delivered messages, while significantly reducing wasted slot capacity and improving the adaptive use of protection features. Under congestion, dynamic MPS selection enables efficient multi-message packing within TDMA slots, resulting in substantial throughput gains and improved slot utilization. Under jammer interference, throughput decreases due to increased packet loss; however, the extended mechanism preserves a higher absolute delivery rate than static packing by systematically increasing the use of redundancy-enabled and combined protection MPSs, reflecting a shift from capacity-oriented to resilience-oriented adaptation under degraded channel conditions. Overall, the proposed framework provides a practical, standards-compliant runtime optimization for Link 16 systems, enabling improved efficiency under light load, enhanced throughput under congestion, and adaptive resilience under interference.
F. Abut, Mehmet Kızıldağ· IEEE Access· 0 citations