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Dynamic Resource Allocation With QoS Provisioning in Cell-Free Massive MIMO Networks
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DOI：10.1109/tvt.2026.3666218.png)
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Abstract
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Cell-free massive MIMO (CF-mMIMO) is a promising technology to support ultra-reliable and low-latency communication (URLLC). In bandwidth-limited CF-mMIMO networks, uniform spectrum allocation can degrade performance due to variations in channel conditions, while bursty URLLC traffic makes it challenging to satisfy stringent end-to-end delay and reliability requirements. Motivated by these challenges, this paper proposes a joint dynamic resource optimization framework for physical resource block (PRB) allocation and uplink power control, aiming to minimize long-term average uplink transmit power under statistical QoS constraints on both transmission and queueing latency, as well as transmission errors and queueing violations. By leveraging Lyapunov optimization, the long-term stochastic problem is transformed into a series of per-slot deterministic subproblems. The resulting subproblems are efficiently solved by the Joint Optimization Algorithm for Dynamic PRB Allocation and Power Control (JOA-DPAPC). To handle the non-convexity of short-packet rates in PRB allocation, a novel concave lower bound is introduced, which remains valid even when the signal-to-interference-plus-noise ratio (SINR) is zero. The Low-complexity PRB Allocation (LPA) algorithm is proposed to solve the user equipment (UE) and PRB association problem. To solve the power control problem, two methods, Quadratic Transformation with CVX (QTC) and Interference Decoupling Bisection (IDB), are proposed, with IDB achieving significant runtime reduction which is suitable for real-time deployment. Simulations show that, compared with benchmark schemes, the IDB-based JOA-DPAPC reduces the average end-to-end delay by at least 11.36% and uplink power by at least 17.43% . Moreover, IDB-based JOA-DPAPC significantly reduces the runtime compared to the QTC-based method, with a reduction of 99.96% . The proposed algorithm also maintains excellent queue stability under bursty traffic conditions, further demonstrating its robustness and practical applicability.
Keywords:
Cell-free massive MIMO
QoS
resource allocation
URLLC
Lyapunov optimization
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7.1
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1.7W
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6.6W
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Cited Papers