Workload-Aware Adaptive Duplex Mode Selection for Mobile Ad Hoc Networks: A Workload Zone Estimation Approach

Full-duplex (FD) technology holds great promise for enhancing the spectral efficiency of Mobile Ad Hoc Networks (MANETs) and Wireless Sensor Networks (WSNs). However, the practical performance gain of FD over Half-Duplex (HD) is highly sensitive to the dynamic nature of traffic loads and residual self-interference. Existing Optimal Dynamic Selection Strategies (ODSS) often rely on static workload assumptions within a single time window, failing to capture long-term traffic fluctuations. Consequently, applying instantaneous switching strategies in highly bursty environments necessitates excessively frequent mode switching (e.g., the switching frequency can approach the total number of time windows), incurring prohibitive signaling overhead and unignorable MAC-layer adaptation delays. To overcome these concrete bottlenecks, this paper proposes a comprehensive traffic-aware adaptive duplex mode selection framework. First, we model the multi-scale dynamic workload using Dynamic Activated Probability in Short-term (DAPS) and Long-term (DAPL), effectively characterizing both bursty traffic (via Beta distribution) and Markov-modulated stable traffic. Second, by integrating physical layer performance analysis, we define the Break-even Workload Point (BWP) to partition traffic into Oversaturated (OZ) and Unsaturated (UZ) Workload Zones (WZs). Furthermore, to handle unknown future traffic with low complexity, we propose the Pre-scheduling Duplex selection based on the Workload zone Estimation (PDWE) algorithm. PDWE leverages a Hidden Markov Model (HMM) combined with a Rollout algorithm to estimate hidden traffic states and adaptively pre-schedule duplex modes. Simulation results demonstrate that the proposed strategy achieves near-optimal throughput (approximately 91% of the ideal ODSS) while reducing the duplex switching frequency by two orders of magnitude compared to instantaneous switching strategies. This approach offers a robust cross-layer solution for next-generation self-organizing networks.