期望信号功率对MVDR算法性能的影响分析

当接收数据中存在期望信号时,即使是入射信号互相独立, 最小方差无失真响应（minimum variance distortionless response ,MVDR）算法性能都受期望信号功率的影响。在各入射信号相互独立的前提下,本文先是分析了期望信号功率对期望信号输出功率和干扰加噪声输出功率的影响,接着分析了该影响下的输出信干噪比（SINR,signal-to-interference-plus-noise ratio）以及它的收敛速度的变化情况。分析表明,输出SINR在一定范围内是随着期望信号功率的变大而增加,但是当期望信号功率变大到一定程度后,干扰被抑制的强度会随着期望信号功率的变大而减弱,从而导致输出SINR不再随期望信号功率的增大发生变化。SINR的收敛速度也随期望信号功率的增大而变慢。仿真验证了分析结果的有效性。      

SINR and throughput improvement for VANET using fuzzy power control

This paper proposes transmission power control for vehicular ad hoc network (VANET) using fuzzy system. Despite the potential advantages of VANET especially for safety and intelligent transportation system, some challenges are discovered during the implementation of VANET. Main challenges emerge because of the dynamic environment and high mobility of vehicle. Furthermore, the interference due to the shared‐spectrum usage can significantly decrease the quality of signal. Fuzzy system is implemented to control the transmission power based on the signal to interference and noise ratio (SINR) difference with the targeted value of the receiver vehicle and the interference inflicted by the transmitter vehicle. The algorithm of fuzzy power control for VANET is proposed, and the performance is evaluated through the simulations. The results of simulations show that the proposed algorithm can increase SINR of vehicles especially the vehicles with SINR value below the target. Thus, the average of SINR and the throughput of the system can be increased as well.     

Minimum-noise-variance beamformer with an electromagnetic vectorsensor

We study the performance of the minimum-noise-variance beamformer employing a single electromagnetic (EM) vector sensor that is capable of measuring the complete electric and magnetic fields induced by EM signals at one point. Two types of signals are considered: one carries a single message, and the other carries two independent messages simultaneously. The state of polarization of the interference under consideration ranges from completely polarized to unpolarized. We first obtain explicit expressions for the signal to interference-plus-noise ratio (SINR) in terms of the parameters of the signal, interference, and noise. Then, we discuss some physical implications associated with the SINR expressions. These expressions provide a basis for effective interference suppression as well as generation of dual-message signals of which the two message signals have minimum interference effect on one another. We also analyze the characteristics of the main-lobe and side-lobe of the beampattern of an EM vector sensor and compare them with other types of sensor arrays     

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.     

Coverage analysis of cell‐edge users in heterogeneous wireless networks using Stienen's model and RFA scheme

In heterogeneous wireless networks, signal‐to‐interference‐plus‐noise ratio (SINR) suffers degradation due to strong interference received by users from offloaded macro base station (mBS). Similarly, cell‐edge users experience low SINR due to their distant locations. Moreover, small base stations (sBSs) located in the vicinity of mBS experience reduced coverage due to the high transmit power of mBS. To overcome these limitations, we use Stienen's model as a base station deployment strategy to improve network performance gain. More specifically, we use reverse frequency allocation (RFA) as an interference management scheme together with Stienen's model to significantly improve SINR, enhance edge user coverage, and avoid sBS deployment near the mBS. In the proposed set‐up, the available coverage region is divided into two noncontiguous regions, ie, center region and outer region. Furthermore, mBSs are uniformly distributed throughout the coverage region using independent Poisson point processes, while sBSs are deployed only in outer region using Poisson hole process (PHP). Closed‐form expressions for coverage probabilities are characterized for the proposed model. Numerical results show that the proposed scheme yields improved SINR with enhanced edge user coverage and requires fewer number of sBSs.     

The maximin algorithm for adaptive arrays and frequency-hopping communications

An algorithm is described for maximizing of the signal-to-interference-plus-noise ratio (SINR) at the output of an adaptive array. The algorithm discriminates between the desired signal and any interference on the basis of the spectral characteristics of frequency-hopping signals. The algorithm maximizes the SINR by maximizing the desired.signal output power while simultaneously minimizing the interference-plus-noise output power. Rapid convergence of the weights to the steady-state values is achieved by the adjustment of the loop gain as a function of the estimated SINR at each iteration. Implementation of the algorithm in conjunction with a frequency-hopping modem is explained. Computer simulation results describe both the steady-state and transient responses of the system under various jamming conditions. The results indicate a rapid dynamic response and the steering of deep nulls over a wide range of the SINR.     

Cell Selection for Load Balancing in Heterogeneous Networks

The vision of advanced long-term evolution (LTE-A) project is set to ultimate increase of network capacity in heterogeneous networks (HetNets). In HetNets with small cell configuration, a considerable majority of user devices is eventually connected to the macrocell base station (MBS), while small base stations (BSs), such as femtocell access points (FAPs), are still without any user. This results in unbalanced load and reduces the data rate of macrocell user equipment (MUE). In this paper, a method is proposed for load balancing among FAPs, while desired throughput is achieved. The proposed method uses the estimated received signal strength from different BSs and adjusted pilot signals. Under the critical signal to interference plus noise ratio (SINR) condition, a list of candidate FAPs is prepared. The updated candidate list henceforth does not include the least visited FAPs, which in turn leads to lower unnecessary handoffs. Once the BS with the highest number of free RBs and the highest pilot signal power is selected, FAP allocates the RBs with higher SINRs (qualified RBs) to user. In the case of FAP unavailability, the algorithm compels users to connect to the MBS with adequate qualified RBs. The performance of the proposed method was evaluated under a variety of FAPs density, and the number and velocity of users in terms of throughput and Jain’s fairness index. The results evidence affordable improvements in the throughput and Jain’s index in comparison with other methods.     

Interference alignment scheme for massive MIMO system

The performance of massive multiple-input multiple-output （MIMO） system is limited by pilot contamination. To reduce the pilot contamination, uplink and downlink precoding algorithms are put forward based on interference alignment criterion. In the uplink receiving processing, the target function aligns the pilot contamination and the interference signals to the same null space and acquires the maximal space degree of the desired signals. The uplink receiving precoding matrix is solved on maximal signal to interference plus noise ratio （SINR） criterion considering the impact of the pilot contamination on channel estimations. The uplink receiving precoding matrix is used as the downlink transmitting precoding matrix. Exploiting the channel reciprocity, it is proved that, if the uplink receiving precoding matrix achieves maximal S1NR, the identical precoding matrix can be used in the downlink transmission and acquires maximal signal to leakage plus noise ratio （SLNR）. Simulations show that the spectrum efficiency of the proposed algorithm can reach about 1.5 times higher than that of popular matched filtering （MF） precoding algorithm, and about 1.1 times higher than multi-cell minimum mean square error （MMSE） precoding algorithm. The performance of the proposed algorithm can be improved approximately linearly with the increasing of the number of antennas.     

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.     

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.     

CDMA系统智能天线盲自适应波束形成

给出了基于最大化信号对干扰和噪声的功率比(MSINR)准则的盲自适应波束形成在线递推算法,旨在提高DS-CDMA系统中智能天线的性能.将MSINR准则转化为一种新的等价的无约束准则函数,通过最大化此准则函数来在线估计最优波束形成向量.算法直接利用了DS-CDMA系统解扩前和解扩后的观测信号,无须训练序列.通过在线迭代估计,降低了计算波束权值的复杂度.不同通信环境中的仿真结果表明,该算法具有较高的估计精度和很好的抗多址干扰能力.     

欠定线性瞬时混合盲分离矩阵求解算法

针对欠定线性瞬时混合中的混合矩阵条件数较大的情况,使用最小二乘估计算法求解源信号造成的噪声放大问题,研究了一种求解分离矩阵的算法。此方法基于最大信干噪比的原则建立代价函数,通过最优化此函数得到分离矩阵。仿真实验表明,该算法与最小二乘算法相比可以改善在混合矩阵条件数较大时噪声放大影响下的分离性能。     

基于Bayes估计和数据流间功率分配的联合干扰相位对齐算法

针对信道状态信息（CSI）存在时延和误差的情况,本文提出了适用于多小区MIMO-BC的基于Bayes估计和数据流间功率分配的联合干扰相位对齐算法.首先,发送端通过Bayes估计获得当前CSI的最佳估计;其次,通过最大化期望信号功率与小区间干扰功率的比值来设计干扰抑制矩阵;而在反向通信时,通过最大化信干比来设计预编码;进一步地,结合注水算法来优化功率分配.最后,采用相位对齐将数据流间的干扰旋转到目标接收数据流的信号空间中,进而增强目标数据流的接收功率.仿真表明,无论是在理想CSI还是时延误差CSI,本文算法较其他算法都有一定的性能优势.     

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。     

Finite data performance analysis of a sidelobe canceller

The performance of the generalized sidelobe canceller (GSC) is affected by the desired signal (DS) even if all signals are uncorrelated with each other when the DS exists in the received array data with finite snapshot number. Under the condition that the DS is blocked totally in the auxiliary array, a novel expression of the weight vector of the GSC, where the auxiliary array is separated from the main array, is derived for the finite data. Based on the new weight vector, the corresponding expressions of the output signal-to-interference-plus-noise ratio (SINR) can be developed for the case that all signals, including the DS and interference signals, are independent with each other. Then, effects on the SINR for some parameters, including the signal-to-noise ratio, the array antenna number, the direction-of-arrival of the interference signal and the interference-to-noise ratio, are studied, respectively. Some guidelines can thus be obtained for the practical application.

     

基于拉伸处理的宽带频域接收波束形成方法

为了抑制宽带干扰信号,提出了一种基于频域的宽带接收波束形成方法。该方法针对线性调频信号,在对接收信号做拉伸处理和窄带滤波之后,进行傅立叶变换划分为许多窄带,然后对不同频带的信号按窄带方法（例如采样矩阵求逆法）接收波束形成。与传统的频域方法相比,大大降低了数据率和计算量,易于工程实现;与拉伸处理波束形成方法相比,该方法能有效抑制宽带干扰,阵列输出信号干扰噪声比高。最后计算机仿真证实了新方法的有效性。     

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.     

时分双工蜂窝系统的智能天线研究和性能评估

智能天线是移动多媒体通信亟待解决的关键技术,本文研究了一种适用于时分双工蜂窝系统,基于非线性判决反馈空间均衡器和递归最小平方算法的智能天线。提出了双向链路信号对干扰加噪声功率比的算法以及阵列波束方向增益和信干比累积分布函数两种性能评估方法。仿真结果表明：该智能可以抵消同波道干扰,改善信干比,减小频率复用系数。     

非线性盲辨识补偿处理的宽带超外差接收机

提出了一种基于非线性盲辨识补偿处理的新型宽带超外差接收机。在时域,分别提取接收前端输出信号的大信号成分（大功率频率分量）和小信号成分（主要包含非线性失真分量）,并以大信号的非线性模型与小信号的残差平方和最小作为其非线性行为模型参数的辨识准则,利用加权迭代改善算法实现模型参数的自适应提取和更新,最后在线实时地对接收机输出信号进行数字域后补偿处理。实测结果表明,在同时多信号接收的情况下,该非线性盲辨识补偿处理可将整机的无杂散失真动态范围(SFDR)提高超过20dB,极大地提高了在强干扰存在时对微弱信号接收与检测的能力。      

Low-complexity joint beamforming and power allocation for SINR balancing in cognitive radio networks

We consider the Signal-to-Interference plus Noise Ratio (SINR) balancing problem involving joint beamfoming and power allocation in the Cognitive Radio (CR) network, wherein the Single-Input Multi-Output Multiple Access Channels (SIMO-MAC) are assumed. Subject to two sets of constraints: the interference temperature constraints of Primary Users (PUs) and the peak power constraints of Cognitive Users (CUs), a low-complexity joint beamforming and power allocation algorithm called Semi-Decoupled Multi-Constraint Power Allocation with Constraints Preselection (SDMCPA-CP) for SINR balancing is proposed. Compared with the existing algorithm, the proposed SDMCPA-CP can reduce the number of matrix inversions and matrix eigen decompositions significantly, especially when large numbers of PUs and CUs are active, while still providing the optimal balanced SINR level for all the CUs.