A hybrid system of cellular mode and device-to-device(D2D)mode is considered in this paper,where the cellular resource is reused by the D2D transmission.With the objective of capacity maximization,the power optimization of D2D sub-system is considered,taking into account quality of service(QoS)requirement.The power optimization problem is divided into two stages:The first stage is the admission control scheme design based on the QoS requirement of D2D users,and the second is power allocation to maximize aggregate throughput of admissible D2D users.For the D2D admission control problem,a heuristic sorting-based algorithm is proposed to index the admissible D2D links,where gain to Interference ratio(GIR)sorting criterion is used.Applying an approximate form of Shannon capacity,the power allocation problem can be solved by convex optimization and geometric programming tools efficiently.Based on the theoretical analysis,a practical algorithm is proposed.The precision can reach a trade-off between complexity and performance.Numerical simulation results confirm that combining with GIR sorting method,the proposed scheme can significantly improve the D2D system's capacity and fairness.
FU Zi-xi HU Chun-jing PENG Tao LU Qian-xi WANG Wen-bo
In this article,the capacity of wireless multi-hop networks with the frequency hopping(FH) technique is derived.Different from the previous work based on non-spread spectrum(SS) system,this study is based on frequency hopping spread spectrum(FHSS) and the retransmission mechanism.The analysis results show that the normalized transport capacity decreases as 1/Mλ,when the total available frequency band is divided into M sub-bands for frequency hopping and the nodes are randomly distributed in space according to a Poisson point process with intensity λ .In this work,the best transmission range per hop to get the maximum capacity is also derived.Besides,the results summarize how the capacity of FH wireless multihop networks is affected by the outage probability,target signal to interference plus noise ratio(SINR) and other system parameters.
Although multiple-input-multiple-output (MIMO) detection has received much research attention in the past years,to the author's knowledge,few detection methods demonstrate optimal/near-optimal performance with low complexity.This paper proposes to incorporate automatic retransmission request (ARQ) with sub-optimal MIMO detectors so as to achieve both favorable performance and low complexity.In the study,retransmission delay induced by ARQ is exploited as a source of improving the detection performance of low complexity algorithms.In particular,the detection performance of sub-optimal algorithms improved by introducing ARQ is analyzed theoretically.A sufficient condition for such scheme to achieve full-diversity performance is also derived which relates detection performance with number of transmission times.Moreover,throughput cost by retransmission is deduced as well as its lower bound.The zero-forcing (ZF) equalizer cooperating with ARQ,as a case study,is shown to have evident performance improvement through theoretical analysis.And numerical results are presented to verify the effectiveness of the proposed scheme which boosts the performance of sub-optimal detector and possesses lower implementation complexity for practical reality simultaneously.
The scheduling algorithm based on the three-way handshaking scheme in IEEE 802.16d-2004 standard has some serious problems because of the complexity of the algorithm and low scheduling efficiency.To enhance the scheduling efficiency and improve the performance of multi-hop wireless mesh networks(WMNs),one distributed scheduling algorithm that can maximize the spatial and time reuse with an interference-based network model is proposed.Compared to the graph-based network model,the proposed network model can achieve a better throughput performance with maximal spatial reuse.Furthermore,this proposed scheduling algorithm also keeps fairly scheduling to all links,with a priority-based polling policy.Both the theoretical analysis and simulation results show that this proposed distributed scheduling algorithm is simple and efficient.
