IEEE Transactions on Wireless Communications · 2015 · 120 citations · 30 references
EngineeringComputer EngineeringElectrical EngineeringDigital CommunicationOptimizationWireless CommunicationsChannel CapacityChannel PowerNetwork OptimizationResource AllocationWireless Channel ModelingWireless NetworksChannel AllocationDuplex CommunicationFull-duplex CommunicationHalf-duplex CommunicationJoint Resource AllocationPoint-to-multipoint LinksPower AllocationRadio Resource Allocation
In-band wireless full‑duplex enables simultaneous transmission and reception on the same frequency, yet its network‑level benefit in large‑scale multi‑carrier, multi‑user OFDMA systems remains unclear due to complex resource allocation. We study a single‑cell full‑duplex OFDMA network with one full‑duplex base station and multiple full‑duplex mobile nodes, aiming to maximize sum‑rate by jointly optimizing subcarrier assignment and power allocation. An iterative algorithm jointly optimizes subcarrier assignment and power allocation, achieving local Pareto optimality in typical scenarios. Simulations show that the proposed algorithm achieves near‑optimal sum‑rate, outperforms half‑duplex schemes, and demonstrates how channel correlation, residual self‑interference, and BS‑node distance affect full‑duplex gain.
Recent advances in the physical layer have demonstrated the feasibility of in-band wireless full-duplex which enables a node to transmit and receive simultaneously on the same frequency band. While the full-duplex operation can ideally double the spectral efficiency, the network-level gain of full-duplex in large-scale networks remains unclear due to the complicated resource allocation in multi-carrier and multi-user environments. In this paper, we consider a single-cell full-duplex OFDMA network which consists of one full-duplex base station (BS) and multiple full-duplex mobile nodes. Our goal is to maximize the sum-rate performance by jointly optimizing subcarrier assignment and power allocation considering the characteristics of full-duplex transmissions. We develop an iterative solution that achieves local Pareto optimality in typical scenarios. Through extensive simulations, we demonstrate that our solution empirically achieves near-optimal performance and outperforms other resource allocation schemes designed for half-duplex networks. Also, we reveal the impact of various factors such as the channel correlation, the residual self-interference, and the distance between the BS and nodes on the full-duplex gain.
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