Jul 2026· International Conference Computing Methodologies and Communication· pp. 319-328· 0 citations· 22 references
Abstract
Massive Multiple Input Multiple Output (M-MIMO) technology plays an important role in Fifth-Generation (5G) and beyond communication systems. It provides more benefits from enhanced Spectral Efficiency (SE) to improve energy efficiency and more consistency. These advantages are possible with accurate Channel State Information (CSI) present at the Base Station (BS). Verifying accurate CSI is difficult because of the required size of the coherence interval and the resulting limitations on pilot sequence length. So, Pilot Contamination (PC) is introduced when reusing the pilot sequences in nearby cells, which delays the SE enhancement. PC is presented as a bottleneck that limits the achievable throughput of multi-cell massive MIMO systems. In this work, a method for assigning pilot signals and improving pilot sequences is proposed using a Dynamic Attention-based Adaptive Autoformer (DA3) to reduce the effects of PC and increase the system's SE and throughput. The DA3-based Fractional Pilot Reuse (FPR) model classifies users as cell-center or cell-edge based on their Signal-to-Interference-plus-Noise Ratios (SINRs) values. Cell-edge users having lower SINR assign orthogonal pilots to reduce inter-cell interference, while cell-center users with higher SINR reuse the same pilots across different cells to enhance SE and throughput. The DA3 parameters, distance threshold, pilot reuse factor, and pilot allocation are optimized using the Secant Optimization Algorithm (SOA), which helps to increase the SE and throughput in the MIMO system. The developed SOA achieves near-optimal performance with lower computational complexity, thus making it highly suitable for interference management and eliminating the PC issues. The performance of the proposed model is tested with the classical pilot resource allocation methods to confirm its effectiveness.
In time-division duplex (TDD) massive multiple-input multiple-output (MIMO) systems, users send pilot sequences for channel state estimation in a fixed time interval, which leads to pilot redundancy if users undergo longer coherence time than the prescribed channel estimation interval, and consequently reduces the net sum spectral efficiency of the systems. In this paper, we propose an adaptive channel estimation scheme for TDD massive MIMO systems, where base stations can reuse the aged channel state information (CSI) by exploiting the temporal correlation inherent in channel aging. We introduce a Fisher transformation method for temporal correlation estimation to determine the CSI estimation interval. We also derive the closed-form expressions of the spectral efficiency with channel aging effect and design a threshold to control the channel aging error introduced by CSI reuse. Numerical results demonstrate that our proposed adaptive scheme yields significant performance gains in spectral efficiency across various communication scenarios.
Zhouyi Qian, Shaowei Wang· IEEE Transactions on Wireles...· 0 citations
Rate-splitting multiple access (RSMA) is a promising technique for massive MIMO systems, while hybrid precoding provides an effective means to balance transmission performance and energy consumption. However, existing studies mainly focus on fully-connected architectures, while hybrid precoding design for massive MIMO-RSMA systems with energy-efficient partially-connected architecture remains unexplored in the literature. To fill in this research gap, we propose an adaptive cross-entropy (ACE)-based hybrid precoding scheme. The analog precoder is designed using a probabilistic search over discrete phases, iteratively sampling and updating selection probabilities. Then, the weighted minimum mean-squared error (WMMSE) algorithm is employed to jointly optimize the digital precoder and the common rate allocation. Simulation results demonstrate that the proposed scheme maintains competitive MMF performance while achieving superior energy efficiency.
Zhihua Li, Ming-Yang Si, Xuehan Wang et al.· IEEE Communications Letters· 0 citations
Efficient uplink processing in distributed massive multiple-input multiple-output (D-mMIMO) systems requires effective local combining to significantly mitigate inter-user interference. Recent zero-forcing (ZF) based combining schemes, such as partial full-pilot ZF (PFZF) and protected weak PFZF (PWPFZF), rely on heuristic threshold-based user grouping that may lead to inefficient utilization of spatial degrees of freedom across access points. To address this limitation, we propose an adaptive pilot-aware local combining scheme, generalized PFZF (G-PFZF), that dynamically allocates spatial degrees of freedom based on local channel conditions and replaces heuristic grouping with a decentralized pilot-level optimization framework. Numerical results demonstrate that the proposed G-PFZF scheme achieves significantly higher sum spectral efficiency compared to PFZF and PWPFZF.
Mohd Saif Ali Khan, Karthik R.M., Samar Agnihotri· International Conference on...· 0 citations
Scheduling in multiuser multiple input multiple output (MU-MIMO) systems is essential for efficient resource allocation and overall performance enhancement. In this work, a multiuser scheduling problem is formulated to maximize the product of user equipments'(UEs) aggregate satisfactions, which maintains user fairness. Solving such a combinatorial problem using exhaustive search (EX), which requires evaluating all possible multiuser groups within a massive number of resource blocks (RBs), is prohibitive. Instead, we propose an efficient users'satisfaction based scheduling approach (US-SA). In our US-SA, a low dimension sub-grouping matrix is constructed {at each frame}, which is used to schedule the best multiuser group in each time slot; satisfied users are eliminated from the scheduling process. Our US-SA performs close to the optimal EX method in terms of satisfaction, transmitted data amount, spectral efficiency, latency, and fairness with lower computational cost. Moreover, our experiments demonstrate that the proposed scheme outperforms competing techniques.