Resource Allocation for Physical Layer Security in Heterogeneous Network with Hidden Eavesdropper

The tremendous performance gain of heterogeneous networks(Het Nets) is at the cost of complicated resource allocation. Considering information security, the resource allocation for Het Nets becomes much more challenging and this is the focus of this paper. In this paper, the eavesdropper is hidden from the macro base stations. To relax the unpractical assumption on the channel state information on eavesdropper, a localization based algorithm is first given. Then a joint resource allocation algorithm is proposed in our work, which simultaneously considers physical layer security, cross-tier interference and joint optimization of power and subcarriers under fairness requirements. It is revealed in our work that the considered optimization problem can be efficiently solved relying on convex optimization theory and the Lagrangian dual decomposition method is exploited to solve the considered problem effectively. Moreover, in each iteration the closed-form optimal resource allocation solutions can be obtained based on the Karush-Kuhn-Tucker(KKT) conditions. Finally, the simulation results are given to show the performance advantages of the proposed algorithm.

Energy-Efficient Transceiver Design for Multi-Pair Two-Way Relay Systems

In this paper, we focus on energy-efficient transceiver and relay beamforming design for multi-pair two-way relay system. The multi-antenna users and the multi-antenna relay are considered in this work. Different from the existing works, the proposed algorithm is energy-efficient which is more applicable to the future green network. It considers both the sum-MSE problem and the power consumption problem for the users under the relay power constraint. Based on the optimal condition decomposition(OCD) method, the energy-efficient precoders at the users can be designed separately with limited information exchanged. The proposed relay beamforming algorithm is based on the alternative direction method of multipliers(ADMM) which has simpler iterative solution and enjoys good convergence. Simulation results demonstrate the performance of the proposed algorithms in terms of power consumption and MSE performance.

Distributed Chunk-Based Optimization for MultiCarrier Ultra-Dense Networks

In this paper,a distributed chunkbased optimization algorithm is proposed for the resource allocation in broadband ultra-dense small cell networks.Based on the proposed algorithm,the power and subcarrier allocation problems are jointly optimized.In order to make the resource allocation suitable for large scale networks,the optimization problem is decomposed first based on an effective decomposition algorithm named optimal condition decomposition(OCD) algorithm.Furthermore,aiming at reducing implementation complexity,the subcarriers are divided into chunks and are allocated chunk by chunk.The simulation results show that the proposed algorithm achieves more superior performance than uniform power allocation scheme and Lagrange relaxation method,and then the proposed algorithm can strike a balance between the complexity and performance of the multi-carrier Ultra-Dense Networks.

Distributed Resource Allocation in Ultra-Dense Networks via Belief Propagation

Ultra-dense networking is widely accepted as a promising enabling technology to realize high power and spectrum efficient communications in future 5G communication systems. Although joint resource allocation schemes promise huge performance improvement at the cost of cooperation among base stations,the large numbers of user equipment and base station make jointly optimizing the available resource very challenging and even prohibitive. How to decompose the resource allocation problem is a critical issue. In this paper,we exploit factor graphs to design a distributed resource allocation algorithm for ultra dense networks,which consists of power allocation,subcarrier allocation and cell association. The proposed factor graph based distributed algorithm can decompose the joint optimization problem of resource allocation into a series of low complexity subproblems with much lower dimensionality,and the original optimization problem can be efficiently solved via solving these subproblems iteratively. In addition,based on the proposed algorithm the amounts of exchanging information overhead between the resulting subprob-lems are also reduced. The proposed distributed algorithm can be understood as solving largely dimensional optimization problem in a soft manner,which is much preferred in practical scenarios. Finally,the performance of the proposed low complexity distributed algorithm is evaluated by several numerical results.

Balancing QoE and Fairness of Heterogeneous Traffics Based on Equivalent Rate Scaling

With great increase of mobile service in recent years,high quality of experience(QoE) is becoming a comprehensive and major goal for service provider.To unify evaluations of different services,mean opinion score(MOS) as a subjective assessment is usually adopted for accurate and convincing reflection of user perceived quality.In this paper,we consider the effect of the burst transmission of best effort(BE) traffic on the uses with real time video traffic in the same cell.We extend the rate scaling process which was initially used to shape burstiness of BE users as interference to handle the scenario that BE users act as resource competitors with video users.A power reallocation strategy between the two types of users is presented and an algorithm further improving the fairness of BE users is proposed.The simulation results demonstrate that the proposed algorithm can not only promote the QoE of both types of users,but also guarantee the fairness among users.

二乙酰氨乙酸乙二胺联合瑞替普酶对消化道大出血患者纤溶系统的影响

目的探讨二乙酰氨乙酸乙二胺联合瑞替普酶对消化道大出血患者纤溶系统的影响。方法选取2014年8月-2018年1月在青海仁济医院诊治的消化道大出血患者73例,根据治疗方法的不同分为观察组40例与对照组33例,均采用生长抑素治疗方法,对照组给予瑞替普酶静脉溶栓治疗,观察组在对照组治疗基础上给予二乙酰氨乙酸乙二胺治疗,所有患者都用药观察3 d,比较两组临床疗效和止血时间、输血量、住院时间等临床指标的情况,检测D-二聚体和纤维蛋白原(FIB)含量,同时在治疗前后进行血小板黏附率与聚集率的测定。结果对照组的治疗总有效率为84.8%,观察组为97.5%,观察组显著高于对照组(P<0.05)。观察组的止血时间、输血量、住院时间都显著少于对照组(P<0.05)。观察组治疗后的血小板黏附率、聚集率高于治疗前,也高于对照组,差异均有统计学意义(P<0.05),对照组治疗后血小板黏附率、聚集率与治疗前比较,差异无统计学意义。经治疗后两组的D-二聚体和FIB值均低于治疗前,同组治疗前后比较差异有统计学意义(P<0.05),治疗后观察组低于对照组,差异有统计学意义(P<0.05)。结论二乙酰氨乙酸乙二胺联合瑞替普酶治疗消化道大出血患者能改善纤溶系统的变化,增加血小板活性,从而更加有效发挥止血作用,提高治疗效果。