Non-cooperative power control game for adaptive modulation and coding

Adaptive modulation and coding (AMC) provides the flexibility to match modulation and coding scheme (MCS) to signal to interference plus noise ratio (SINR) of users. To reduce the transmission power and maintain the transmission quality, power control is normally combined with AMC. While the target SINR of power control is fixed, therefore non-cooperative power control game for AMC (NPGA) algorithm was proposed to adapt to the dynamic target SINR changes according to MCS. In NPGA, we formulate system transmission efficiency via utility, where the utility function is constructed based on the modulation and coding efficiency with non-cooperative game theory. It is demonstrated theoretically that NPGA can satisfy the conditions of the supermodular games, and its solution is optimal. The simulation results show that NPGA can improve system transmission efficiency and signal quality with low transmission power, and the convergence performance of NPGA is more fast-effectiveness compared with geometric programming algorithms.     

Distributed power control for multiuser cognitive radio networks with quality of service and interference temperature constraints

One of the most challenging problems in dynamic resource allocation for cognitive radio networks is to adjust transmission power of secondary users (SUs) while quality of service needs of both SUs and primary users (PUs) are guaranteed. Most power control algorithms only consider interference temperature constraint in single user scenario while ignoring the interference from PUs to SUs and minimum signal to interference plus noise ratio (SINR) requirement of SUs. In this paper, a distributed power control algorithm without user cooperation is proposed for multiuser underlay CNRs. Specifically, we focus on maximizing total throughput of SUs subject to both maximum allowable transmission power constraint and SINR constraint, as well as interference temperature constraint. To reduce the burden of information exchange and computational complexity, an average interference constraint is proposed. Parameter range and convergence analysis are given for feasible solutions. The resource allocation is transformed into a convex optimization problem, which is solved by using Lagrange dual method. In computer simulations, the effectiveness of our proposed scheme is shown by comparing with distributed constrained power control algorithm and Nash bargaining power control game algorithm. Copyright © 2014 John Wiley & Sons, Ltd.     

Adaptive Congestion Prediction in Vehicular Ad-hoc Networks (VANET) Using Type-2 Fuzzy Model to Establish Reliable Routes

Urban areas are more prone to accidents and traffic congestions due to ever-increasing vehicles and poor traffic management. The increase in the emission of harmful gases is another important issue associated with vehicular traffic. Attaining a level of QOS is often challenging as it has to meet the eco-friendly factors along with reliable and safe transportation. Smart and accurate congestion management systems in VANET can significantly reduce the risk of accidents and health issues. To fulfil the requirements of QOS the congestion control methods should consider the properties such as fairness, decentralization, network characteristics, and application demands in VANET. We proposed an Adaptive Congestion Aware Routing Protocol (ACARP) for VANET using the dynamic artificial intelligence (AI) technique. The ACARP presents the adaptive congestion detection algorithm using the type-2 fuzzy logic AI technique. The fuzzy model detects the congestion around each vehicle using three fuzzy inputs viz. bandwidth occupancy, link quality, and moving speed. This is followed by inference model to estimate congestion probability for each vehicle. Finally, defuzzification determines status of congestion detection using the pre-defined threshold value for each vehicle. The status of congestion and its probability values were utilized to establish safe and reliable routes for data transmission. It also saves significant communication overhead and hence congestions in the network. The simulation results provide the evidence that the proposed protocol improves the QOS and assist in reduction of traffic congestions significantly.

     

认知无线网络中一种非合作博弈功率控制算法

针对现有的功率控制算法中存在的干扰问题和功率消耗过大问题,设计出一种新的效用函数,并根据此效用函数提出了一个基于非合作博弈的新的功率控制算法。首先,在效用函数中分别为信干噪比和功率设定了不同的代价因子,并将信道状态概念引入到代价因子里面,使其能够更加合理地控制用户,避免用户过度增加发射功率,同时减小了用户间的干扰;其次,证明了该算法纳什均衡的存在性和唯一性;最后,给出了所提算法的流程图。仿真结果表明,与Nash算法相比,在保证非授权用户服务质量( QoS)前提下,该算法功率消耗明显降低,并且具有较好的抗背景噪声性能;与K-G( Koskie-Gajic)算法相比,该算法保证了所有的用户的信干噪比满足上下限阈值要求,并且提高了系统容量。     

Interference-aware node access scheme in UAV-aided VANET

In vehicular Ad Hoc network (VANET),frequent link handovers and channel interference can lead to increased transmission delay and decreased network throughput.To address the issues,unmanned aerial vehicle (UAV) were introduced to cooperate with vehicles and construct UAV-assisted air-ground integrated VANET.An interference-aware node access scheme was proposed.The node access problem was formulated as a multi-objective optimization problem considering link transmission rate,link handovers and transmit power.Then the optimization problem was decomposed into two convex optimization sub-problems by dual decomposition method,the sub-problem jointly optimizes handovers and link transmission rate while the sub-problem optimizes the transmit power based on link reliability.Finally,simulation results show that the proposed mechanism can effectively improve data delivery ratio,average end-to-end delay and network throughput.     

Joint optimal power control and beamforming in wireless networksusing antenna arrays

The interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to increase the capacity in wireless communication networks. The minimum variance distortionless response beamformer maximizes the signal-to-interference-and-noise ratio (SINR) when it is employed in the receiver of a wireless link. In a system with omnidirectional antennas, power control algorithms are used to maximize the SINR as well. We consider a system with beamforming capabilities in the receiver, and power control. An iterative algorithm is proposed to jointly update the transmission powers and the beamformer weights so that it converges to the jointly optimal beamforming and transmission power vector. The algorithm is distributed and uses only local interference measurements. In an uplink transmission scenario, it is shown how base assignment can be incorporated in addition to beamforming and power control, such that a globally optimum solution is obtained. The network capacity and the saving in mobile power are evaluated through numerical study     

A preset threshold based cross-tier handover algorithm for uplink co-channel interference mitigation in two-tier femtocell networks

This paper considers the co-channel interference mitigation problem and proposes a preset threshold based cross-tier handover algorithm for uplink co-channel interference mitigation in two-tier femtocell networks. The proposed cross-tier handover algorithm introduces a preset threshold cross-tier handover policy, which takes into account both the time-to-stay (TTS) of a macrocell user equipment (MUE)/femtocell user equipment (FUE) in a femtocell/the macrocell, and the received signal to interference plus noise ratio (SINR) at a femtocell access point (FAP)/the macrocell base station (MBS) in making a cross-tier handover decision for an MUE/FUE. A cross-tier handover decision is made by comparing the TTS of an MUE/FUE in a femtocells/the macrocell and the SINR at a FAP/the MBS with a preset TTS threshold and different SINR thresholds. The objective of the preset threshold based cross-tier handover algorithm is to increase the received SINR at the MBS/FAPs and thus improve the network performance. The performance of the proposed cross-tier handover algorithm with the minimum power transmission and the optimal power transmission is analyzed, respectively. Numerical results show that the proposed preset threshold based cross-tier handover algorithm can significantly improve the network performance in terms of the outage probability, user sum rate, and network capacity.     

On the Constrained Stochastic Gradient Algorithm: Model, Performance, and Improved Version

This paper discusses the constrained stochastic gradient (CSG) algorithm used for controlling antenna arrays, aiming to maximize the signal-to-interference-plus-noise ratio (SINR) in mobile communications. Firstly, analytical expressions for the first moment of the weight vector and the SINR characteristic of the standard CSG algorithm are derived for two interferer signals, considering small step-size conditions and assuming Gaussian signal, interference, and noise. From these model expressions, the CSG algorithm performance is assessed, which predicts undesired behavior (termed here unbalanced behavior, pertaining to an unbalance between maximizing signal power and minimizing interference power) when one or more interference angles-of-arrival are close to the signal angle-of-arrival and the angle-of-arrival spreads of the involved signals are small. Finally, by using the model expressions, an improved CSG (ICSG) algorithm is proposed to compensate the unbalanced behavior of the standard CSG algorithm. The accuracy of the proposed model and the effectiveness of the modified algorithm are assessed through numerical simulations.      

一种新的认知无线电功率分配算法（英文）

Most resource allocation algorithms are based on interference power constraint in cognitive radio networks.Instead of using conventional primary user interference constraint,we give a new criterion called allowable signal to interference plus noise ratio(SINR) loss constraint in cognitive transmission to protect primary users.Considering power allocation problem for cognitive users over flat fading channels,in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user,we propose a new power allocation algorithm.The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.     

VDNet: an infrastructure‐less UAV‐assisted sparse VANET system with vehicle location prediction

Vehicular Ad Hoc Network (VANET) has been a hot topic in the past few years. Compared with vehicular networks where vehicles are densely distributed, sparse VANET have more realistic significance. The first challenge of a sparse VANET system is that the network suffers from frequent disconnections. The second challenge is to adapt the transmission route to the dynamic mobility pattern of the vehicles. Also, some infrastructural requirements are hard to meet when deploying a VANET widely. Facing these challenges, we devise an infrastructure‐less unmanned aerial vehicle (UAV) assisted VANET system called V ehicle‐D rone hybrid vehicular ad hoc Net work (VDNet), which utilizes UAVs, particularly quadrotor drones, to boost vehicle‐to‐vehicle data message transmission under instructions conducted by our distributed vehicle location prediction algorithm. VDNet takes the geographic information into consideration. Vehicles in VDNet observe the location information of other vehicles to construct a transmission route and predict the location of a destination vehicle. Some vehicles in VDNet equips an on‐board UAV, which can deliver data message directly to destination, relay messages in a multi‐hop route, and collect location information while flying above the traffic. The performance evaluation shows that VDNet achieves high efficiency and low end‐to‐end delay with controlled communication overhead. Copyright © 2016 John Wiley & Sons, Ltd.     

A fuzzy logic approach to beaconing for vehicular ad hoc networks

Vehicular Ad Hoc Network (VANET) is an emerging field of technology that allows vehicles to communicate together in the absence of fixed infrastructure. The basic premise of VANET is that in order for a vehicle detect other vehicles in the vicinity. This cognizance, awareness of other vehicles, can be achieved through beaconing. In the near future, many VANET applications will rely on beaconing to enhance information sharing. Further, the uneven distribution of vehicles, ranging from dense rush hour traffic to sparse late night volumes creates a pressing need for an adaptive beaconing rate control mechanism to enable a compromise between network load and precise awareness between vehicles. To this end, we propose an intelligent Adaptive Beaconing Rate (ABR) approach based on fuzzy logic to control the frequency of beaconing by taking traffic characteristics into consideration. The proposed ABR considers the percentage of vehicles traveling in the same direction, and status of vehicles as inputs of the fuzzy decision making system, in order to tune the beaconing rate according to the vehicular traffic characteristics. To achieve a fair comparison with fixed beaconing schemes, we have implemented ABR approach in JIST/SWANs. Our simulation shows that the proposed ABR approach is able to improve channel load due to beaconing, improve cooperative awareness between vehicles and reduce average packet delay in lossy/lossless urban vehicular scenarios.     

Joint optimization and threshold structure dynamic programming with enhanced priority scheme for adaptive VANET MAC

Nodes in vehicular ad-hoc network (VANET) are highly mobile, traversing in unpredictable and varying environment. Therefore, contention window size and transmission power should adapt according to the high mobility transmission environment. In this paper, we propose an adaptive VANET medium access control (MAC) layer with joint optimization for VANET (MACVS) which aims at minimizing average delay and maximizing packet success rate. An adaptive joint optimization with proposed threshold structure dynamic programming, with closed loop feedback control system, is designed to optimize contention window size and transmission power. Adaptive optimization is done based on road traffic conditions and transmission reliable distance range (depicted by interference and noise), by monitoring the continuous change and threshold of received signal strength to interference and noise ratio. Mathematical expressions have been developed for the MACVS optimization framework, and the produced analytical results show good agreement with the simulation results. Simulations with different arrival rates and urban map of city center show that the proposed MACVS with low complexity joint optimization effectively reduces end-to-end delay while achieving high packet success rate under various network traffic condition.     

基于扩频序列自相关性的导航接收机干扰抑制

提出了一种抑制信号干扰的波束形成算法.利用GNSS信号中扩频序列的强自相关性在信号捕获后,采用GNSS信号多个周期的相关峰值估计相关值中的信号协方差矩阵,使用相关前、后的协方差矩阵在最大化输出信噪比准则下得到最优权.所提算法处理时无需GNSS信号和干扰方向的先验知识.仿真与实测结果表明:与功率倒置方法和Spectral SelfCoherence Restoral (SCORE)算法相比,经所提算法处理后的GNSS信号信干噪比获得明显提高.     

CADMA: collision-avoidance directional medium access for vehicular ad hoc networks

Quick and accurate message transmission is an important research topic for vehicular ad hoc networks (VANET). Most studies assume that the periodic broadcast of beacon frames between vehicles increases the safety of the driver. In particular, there has been a lot of research into broadcasting based on carrier sense multiple access with collision avoidance (CSMA/CA) algorithms for medium access. However, the CSMA/CA algorithm is not an optimum technique for the VANET system, due to the transfer delay that occurs in inducing frequent collisions on transmission signals. In this paper, we propose a collision-avoidance directional medium access (CADMA) protocol and infrastructure-utilized clustering method for VANET to support reliable data transfer. In the proposed scheme, the CADMA protocol uses non-competitive transmission methods and cluster heads (CHs) to manage access by allocating the nodes resources. In addition, the roadside unit (RSU) helps with the clustering process. The simulation results indicate that the CADMA can reduce transmission delays and the collision rate of the broadcasting signal, and have shown that the CADMA can be effectively utilized for the VANET systems.     

Feedback‐based multi‐layered STBC system for MIMO multi‐cellular networks with cochannel interference

A feedback‐based multi‐layered STBC (MLSTBC) system, which is adapted to cochannel interference, is proposed. This system can adjust its transmitter configuration so that the largest throughput for the given SINR is obtained, also, it can use joint beamforming and power control to minimize cochannel interference so that the throughput requirement is satisfied. We propose an iterative algorithm to realize joint beamforming and power control for the feedback‐based MLSTBC system, and in this algorithm, we derive the required SINR and the corresponding transmitter configuration for attaining the throughput requirement. Some properties and simulation results are presented, they show that the proposed algorithm helps the feedback‐based MLSTBC system increase the probability of the success in meeting the throughput requirement, also they show that the feedback‐based MLSTBC system results in larger throughput than MLSTBC (with fixed transmitter configuration), STBC, and V‐BLAST. Copyright © 2010 John Wiley & Sons, Ltd.     

Delay-aware reliable broadcast scheme based on power control for VANETs简

In vehicular Ad-hoc network（VANET）, many multi-hop broadcast schemes are employed to widely propagate the warning messages among vehicles and the key is to dynamically determine the optimal relay vehicle for retransmission. In order to achieve reliable and fast delivery of warning messages, this paper proposes a delay-aware and reliable broadcast protocol（DR-BP） based on transmit power control technique. First, a comprehensive model is derived to evaluate the transmission in vehicle-to-vehicle communications. This model considers the wireless channel fading, transmission delay and retransmissions characters occurring in the physical layer/medium access control（PHY/MAC） layer. Then, a local optimal relay selection mechanism based on the above model is designed. In DR-BP scheme, only the vehicle selected as the optimal relays can forward warning messages and the transmit power is time-varying. Finally, extensive simulations verify the performance of DR-BP under different traffic scenarios. Simulation results show that DR-BP outperforms the traditional slotted 1-persistence（S1P） and flooding scheme in terms of packets delivery ratio and transmission delay.     

OFDMA毫微微小区网络中基于效用公平的功率控制策略

毫微微小区(Femtocell)网络能够增强室内覆盖,提高系统容量,但是在频谱共享正交频分多址(OFDMA) Femtocell网络中,同频干扰严重限制了网络的性能。针对频谱共享Femtocell网络中的上行链路,基于网络效率和毫微微小区用户间的公平性,该文提出合作纳什议价功率控制博弈模型,该博弈模型不仅考虑了对宏基站的干扰,而且考虑了毫微微小区用户最小信干噪比(SINR)需求。根据该博弈模型,进一步分析了具有帕累托(Pareto)最优的Kalai-Smorodingsky(KS)议价解。仿真结果表明,该策略既能保证用户公平性、最小SINR需求,又能够有效提高网络频谱利用率。     

Joint beamforming and power control in downlink multiuser multiple‐input multiple‐output systems

In this paper, we study joint beamforming and power control for downlink multiple‐input multiple‐output systems with multiple users and target values for signal‐to‐interference plus noise ratios (SINRs). We formulate this as a constrained optimization problem of minimizing total interference subject to constraints on the beamforming vector norms, target SINRs, and total transmit power. Necessary and sufficient conditions satisfied by the optimal beamformer and power allocation are presented, and a new algorithm for joint beamforming and power control is proposed. This adapts the beamforming vectors and transmit powers incrementally, and it stops when the specified SINR targets are achieved with minimum powers. The proposed algorithm is illustrated with numerical results obtained from simulations, which study its convergence and compare it with other similar algorithms. Copyright © 2013 John Wiley & Sons, Ltd.     

多用户JT MIMO系统下行联合功率分配算法

文中提出一种多用户MIMO下行联合发送（简称JTMIMO）技术中的功率分配算法。首先给出了多用户JT MIMO下行链路模型，并导出了下行信道干扰模型和有偏信道信息下的SINR公式。在此基础上，文中提出一种适用于多用户JTMIMO下行链路的联合功率分配算法，仿真验证表明：通过合理分配用户的发送功率，在满足每个用户信干比（SINR）的前提下，最小化总传榆能量具有较好的能量效率。     

基于信干噪比的无人机集群分布式编队控制算法

编队控制和组网通信是无人机集群保持队形稳定和执行协同任务的前提条件。现有的编队控制算法侧重于队形控制,往往对无人机之间的通信因素考虑较少。针对无人机集群组网编队问题,设计了基于信干噪比(Signal to Interference plus Noise Ratio,SINR)的分布式编队控制算法。该算法兼顾接入覆盖与网络连通性要求,以SINR为参考构建虚拟作用力,能够使无人机以分布式控制的方式自主移动到通信质量更优的位置并维持稳定的拓扑结构。仿真结果表明,该算法可以适用于不同场景,能够在保证网络连通稳定的前提下优化目标区域用户的通信质量,并且具有较高的接入覆盖率和编队稳定性。