基于多功率移动锚节点WSN智能定位算法

为了降低定位成本及提高定位精度,提出了一种使用单个锚节点移动进行未知节点坐标计算的SAPSO-SMPMA算法。该算法采用单个移动锚节点游历定位区域,并通过功率控制发射不同功率的信标信号,未知节点利用收到的不同位置锚节点信息结合自适应权重粒子群算法计算节点坐标。考虑到实际应用时锚节点可能带有误差,故加入了锚节点矢量误差分析。仿真表明,本算法在充分考虑锚节点自身误差及大幅降低定位成本的情况下,定位精度仍然较高,是一种实用的定位算法。

Optimal Power Allocation for Multiuser Underlay Cognitive Radio Networks under QoS and Interference Temperature Constraints

Power allocation is an important issue for Cognitive Radio Networks(CRNs),since it needs to consider the Quality of Service(QoS) for Secondary Users(SUs) while maintaining the interference power to Primary User(PU) below the Interference Temperature(IT) threshold. In this paper, based on Euclidean projection, we propose a distributed power control algorithm with QoS requirements to minimise the total power consumption of SUs under the time-varying channel scenario. Considering the maximum transmit power constraints and the minimum signal to interference plus noise constraints for each SU, together with the IT constraints for each PU, the power allocation problem is transformed into a convex optimization problem without auxiliary variables, and is solved by the Lagrangian dual method with less information exchange.Simulation results demonstrate that the proposed scheme is superior to the Iterative Water-Filling Algorithm(IWFA).

The New Architecture with Time-Spatial Consistency for 5G Networks

While operators have started deploying fourth generation(4G) wireless communication systems,which could provide up to1 Gbps downlink peak data rate,the improved system capacity is still insufficient to meet the drastically increasing demand of mobile users over the next decade.The main causes of the above-mentioned phenomenon include the following two aspects:1) the growth rate of the network capacity is far below that of user's demand,and 2) the relatively deterministic wireless access network(WAN) architecture in the existing systems cannot accommodate the prominent increase of mobile traffic with space-time domain dynamics.In order to address the above-mentioned challenges,we investigate the time-spatial consistency architecture for the future WAN,whilst emphasizing the critical roles of some spectral-efficient techniques such as Massive multiple-input multiple-output(MIMO),full-duplex(FD)operation and heterogeneous networks(HetNets).Furthermore,the energy efficiency(EE)of the HetNets under the proposed architecture is also evaluated,showing that the proposed user-selected uplink power control algorithm outperforms the traditional stochastic-scheduling strategy in terms of both capacity and EE in a two-tier HetNet.The other critical issues,including the tidal effect,the temporal failure owing to the instantaneously increased traffic,and the network wide load-balancing problem,etc.,are also anticipated to be addressed in the proposed architecture.(Abstract)

Proposal for a cross layer scheme for real-time wireless video

This paper focuses on the design of the cross layer between the video application layer and the MIMO physical layer. MIMO physical layer research has promised an enormous increase in the capacity of wireless communication systems. Also MIMO wireless systems operate under fading conditions where the channel faces arbitrary fluctuations. Since the wireless channel changes over each coherence period, the capacity of the wireless channel, given the power constraints, changes. Hence to make efficient use of the available capacity one needs to adapt the video bit rate. However it is impossible to adapt at the application layer as changing the parameters of the video takes more time than the coherence period of the channel. In this paper we address this problem through a novel solution and also investigate its performance through a simulation study.

Joint channel allocation and power control with fairness in multi-hop cognitive radio networks

This paper investigates channel allocation and cognitive radio networks. The color-sensitive graph power control schemes in OFDM-based multi-hop coloring （CSGC） model is viewed as an efficient solution to the spectrum assignment problem. The model is extended to combine with the power con- trol strategy to avoid interference among secondary users and adapt dynamic topology. The optimiza- tion problem is formulated encompassing the channel allocation and power control with the interfer- ence constrained below a tolerable limit. Meanwhile, the proposed resource allocation scheme takes the fairness of secondary users into account in obtaining the solution of optimization. Numerical re- suits show that the proposed strategy outperforms the existing spectrum assignment algorithms on the performance of both the network throughput and minimum route bandwidth of all routes, as well as the number of connected multi-hop routes which implies the fairness among secondary users.

A projected gradient based game theoretic approach for multi-user power control in cognitive radio network

The fifth generation （5G） networks have been envisioned to support the explosive growth of data demand caused by the increasing traditional high-rate mobile users and the expected rise of interconnections between human and things. To accommodate the ever-growing data traffic with scarce spectrum resources, cognitive radio （CR） is considered a promising technology to improve spectrum utilization. We study the power control problem for secondary users in an underlay CR network. Unlike most existing studies which simplify the problem by considering only a single primary user or channel, we investigate a more realistic scenario where multiple primary users share multiple channels with secondary users. We formulate the power control problem as a non-cooperative game with coupled constraints, where the Pareto optimality and achievable total throughput can be obtained by a Nash equilibrium （NE） solution. To achieve NE of the game, we first propose a projected gradient based dynamic model whose equilibrium points are equivalent to the NE of the original game, and then derive a centralized algorithm to solve the problem. Simulation results show that the convergence and effectiveness of our proposed solution, emphasizing the proposed algorithm, are competitive. Moreover, we demonstrate the robustness of our proposed solution as the network size increases.