Dynamic algorithm transformations (DAT)-a systematic approach tolow-power reconfigurable signal processing

In this paper, dynamic algorithm transformations (DATs) for designing low-power reconfigurable signal-processing systems are presented. These transformations minimize energy dissipation while maintaining a specified level of mean squared error or signal-to-noise ratio. This is achieved by modeling the nonstationarities in the input as temporal/spatial transitions between states in the input state-space. The reconfigurable hardware fabric is characterized by its configuration state-space. The configurable parameters are taken to be the filter taps, coefficient and data precisions, and supply voltage V_dd. An energy-optimal reconfiguration strategy is derived as a mapping from the input to the configuration state-space. In this strategy, taps are powered down starting with the tap with the smallest value [w_k²/Σ_m(w_k)] (where w_k and Σ_m(w_k) are, respectively, the adders, redundant-to-binary conversion, tree adders, coefficient and energy dissipation of the kth tap). Optimal values for precision and supply voltage V_dd are subsequently computed from the roundoff error and critical path delay requirements, respectively. The DAT-based adaptive filter is employed as a near-end crosstalk (NEXT) canceller in a 155.52-Mb/s asynchronous transfer mode-local area network transceiver over category-3 wiring. Simulation results indicate that the energy savings range from -2% to 87% as the cable length varies from 110 to 40 m, respectively, with an average saving of 69%. An average saving of 62% is achieved for the case where the supply voltage V_dd is kept fixed     

Novel FEXT Cancellation and Equalization for High Speed Ethernet Transmission

In high-speed multi-pair wireline communication systems, such as 10 Gigabit Ethernet over Copper (10GBASE-T), far-end crosstalk (FEXT) becomes a major impairment and needs to be suppressed to increase data rates. Conventional techniques based on crosstalk cancellation are not suitable for FEXT due to the fact that the disturbing source of FEXT is generally unknown to the victims. This paper presents two different approaches to efficiently deal with FEXT over unshielded twisted-pair (UTP) copper cables. To eliminate the error propagation problem in practice, both approaches use the Tomlinson–Harashima Precoding (THP) technique which however makes the transceiver design nontrivial. In the first approach, FEXT is treated as noise and a new feedforward FEXT canceller is proposed. Compared with conventional techniques, the proposed FEXT canceller can mitigate the non-causal part of FEXT, thus leading to better FEXT cancellation performance. In the second approach, FEXT is treated as signal, and the general multi-input multi-output (MIMO) equalization technique is combined with the TH precoding technique to deal with both intersymbol interference (ISI) and FEXT. Different from the existing works, the proposed designs comply with the 10GBASE-T standard and they are suitable in real applications. Simulation results verify that the proposed approaches can achieve much better performance in terms of decision-point signal-to-noise ratio (DP-SNR) than conventional techniques. It is also shown that the hardware complexity of the transceiver can be reduced by about 37.2% by utilizing the increased DP-SNR in the proposed designs.      

Energy‐Efficient Adaptive Dynamic Sensor Scheduling for Target Monitoring in Wireless Sensor Networks

Due to uncertainties in target motion and randomness of deployed sensor nodes, the problem of imbalance of energy consumption arises from sensor scheduling. This paper presents an energy‐efficient adaptive sensor scheduling for a target monitoring algorithm in a local monitoring region of wireless sensor networks. Owing to excessive scheduling of an individual node, one node with a high value generated by a decision function is preferentially selected as a tasking node to balance the local energy consumption of a dynamic clustering, and the node with the highest value is chosen as the cluster head. Others with lower ones are in reserve. In addition, an optimization problem is derived to satisfy the problem of sensor scheduling subject to the joint detection probability for tasking sensors. Particles of the target in particle filter algorithm are resampled for a higher tracking accuracy. Simulation results show this algorithm can improve the required tracking accuracy, and nodes are efficiently scheduled. Hence, there is a 41.67% savings in energy consumption.     

Demand Side Management for Thermally Activated Building Systems Based on Multiple Linear Regression

The building sector and its heating and cooling represent one of the major consumer of energy worldwide. Simultaneously, the share of fluctuating generation of renewable energies in the energy mix increases. Therefore storage and demand side management technologies are required. The new adaptive and predictive control algorithm for thermally activated building systems (TABS) based on multiple linear regression (AMLR) presented in this paper enables the application of demand side management (DSM) strategies. Based on simulations, different strategies have been compared with each other. By applying the AMLR algorithm, electricity energy cost savings of 38% could be achieved compared to the conventional control strategy for TABS, while increasing the thermal comfort. At the same time, thermal energy demand can be reduced in the range between 4% to 8%, and pump operation time from 86% to 89%.     

Statistical reference criteria for adaptive signal processing indigital communications

A general criterion for the design of adaptive systems in digital communications called the statistical reference criterion is proposed. The criterion is based on imposition of the probability density function of the signal of interest at the output of the adaptive system, with its application to the scenario of highly powerful interferers being the main focus of this paper. The knowledge of the PDF of the wanted signal is used as a discriminator between signals so that interferers with differing distributions are rejected by the algorithm. Its performance is studied over a range of scenarios. Equations for gradient-based coefficient updates are derived, and the relationship with other existing algorithms like the minimum variance and the Wiener criterion are examined     

能量收集通信系统中功率和调制方式的在线联合优化策略

针对源节点配备能量收集装置的点对点能量收集无线通信系统,该文以最大化长期平均传输速率为目标,提出一种基于Lyapunov优化框架的在线功率控制和自适应调制联合优化策略。由于能量到达和信道状态的随机性,优化问题是一个随机优化问题。利用Lyapunov优化框架将电池操作和可用能量约束下的长期时间优化问题转化为每时隙以虚队列“漂移加惩罚”最小化为目标的发送功率、调制方式和帧长的联合优化问题,并求解。该算法仅依赖当前的电池状态和信道状态信息做出决策,计算复杂度低,实用性强。仿真结果显示,所提算法通过联合优化发送功率、调制方式和帧长,能够高效地利用收集的能量,适应信道变化,长期平均实际可达的信息传输速率要明显优于贪婪和半功率算法,即使相比较以信道容量最大化为目标的离线注水算法和其他对比算法,在实际可达的信息传输速率上也有优势。     

Adaptive multiuser detection and beamforming for interferencesuppression in CDMA mobile radio systems

This paper considers the problem of interference suppression in direct-sequence code-division multiple-access (DS-CDMA) systems over fading channels. An adaptive array receiver is presented which integrates multiuser detection, beamforming, and RAKE reception to mitigate cochannel interference and fading. The adaptive multiuser detector is formulated using a blind constrained energy minimization criterion and adaptation is carried out using a novel algorithm based on set-membership parameter estimation theory. The proposed detector overcomes the shortcomings of conventional LMS- and RLS-type algorithms, namely, that of slow convergence and large computational load, respectively. This is especially the case when strong interferers are present or when the number of adaptive weights is relatively large. DS-CDMA systems can have a relatively large number of spatially distributed interferers. Thus beamforming is based on direction-of-arrival (DOA) estimates provided by an approximate maximum-likelihood estimator (DOA-MLE). Unlike previous approaches, the DOA-MLE exploits the structure of the DS-CDMA signaling scheme resulting in robust performance and simple implementation in the presence of angle spreading. The overall method is suitable for real-time implementation and can substantially improve the interference suppression capabilities of a CDMA system     

Simultaneous suppression of multiaccess and narrow-bandinterference in asynchronous CDMA networks

This paper handles the simultaneous suppression of narrow-band and multiaccess interference in asynchronous CDMA networks. We consider both linear one-shot detection and block-detection, showing that, in both cases, the presence of an external narrow-band interferer generally results in the need for time-varying processing. As to the linear one-shot detectors, we derive both a zero-forcing and a minimum mean square error detector, showing that they are members of an only family, wherein the optimization criterion is the constrained minimization of a suitably defined output interference energy. We also present a comparative performance assessment between the various detection strategies, studying the impact of both the optimization criterion and other system parameters, such as the oversampling ratio and the length of the observation window. We also handle the problem of blind and adaptive detection. At first we show that the linear one-shot receivers are readily amenable to a blind implementation, upon off-line estimation of the covariance matrix of the observables. Next, we consider the problem of an adaptive implementation of a periodically time-varying minimum mean square error receiver, introducing and assessing a new cyclic recursive least squares (RLS) algorithm: we show that, unlike the conventional RLS algorithms, the new algorithm is capable of tracking the periodically time-varying variation of the receiver structure, induced by the presence of a data-like narrow-band interferer     

自适应遗传灰狼优化算法求解带容量约束的车辆路径问题

带容量约束的车辆路径问题是NP难的组合优化问题,精确算法无法在合理的时间内得到有效的解.本文提出了一种采用灰狼空间整数编码和先路由后分组解决方案生成策略的自适应遗传灰狼优化算法用于求解带容量约束的车辆路径问题.该算法提出了移动平均自适应灰狼更新策略和灰狼基因遗传策略提高全局收敛能力,同时提出带3-opt的劣势点启发邻域搜索策略来增强算法的全局和局部搜索能力.实验结果表明：所提出算法具有较高的计算精度和较强的寻优能力,有较高的鲁棒性,通过与自适应扫描和速度推测粒子群优化算法、K均值聚类和灰狼优化混合算法、大邻域搜索和蚁群优化混合算法、基于精英选择的多种群人工蜂群算法、基于集覆盖的扩展节省算法、混合变邻域生物共栖搜索算法等6个算法对比证明了算法的有效性.     

Energy optimal control for time-varying wireless networks

We develop a dynamic control strategy for minimizing energy expenditure in a time-varying wireless network with adaptive transmission rates. The algorithm operates without knowledge of traffic rates or channel statistics, and yields average power that is arbitrarily close to the minimum possible value achieved by an algorithm optimized with complete knowledge of future events. Proximity to this optimal solution is shown to be inversely proportional to network delay. We then present a similar algorithm that solves the related problem of maximizing network throughput subject to peak and average power constraints. The techniques used in this paper are novel and establish a foundation for stochastic network optimization     

The Cyclostationary Nature of Crosstalk Interference from Digital Signals in Multipair Cable--Part I: Fundamentals

This paper considers the cyclostationary nature of digital signals when determining crosstalk interference between such signals in multipair cable. This approach is necessary as the interference is only relevant at the decision instants in the receivers of the disturbed systems and any time variation of this interference with respect to the sampling instants changes the effect of this interference; previous studies in the area have ignored the cyclostationary nature of the digital signal. Expressions for the time-varying mean and variance of far-end and near-end crosstalk (FEXT and NEXT) have been derived. These expressions demonstrate the inherently smaller time variation of the NEXT interference when compared to the FEXT interference. An interesting result is that the calculation of the time-averaged value of the variance of FEXT and NEXT interference still requires the use of the cyclostationary properties of the digital signal. The results of this paper are extended and applied to various examples of the engineering of digital line systems in multipair cable in Part II of this paper.     

改进粒子群算法优化低功耗自适应集簇分层的路由算法

针对LEA低C功H算法的簇头分布不合理、网络能耗不均的问题,在耗自适应集簇分层路由算法。首先将分割线的选择LE问A题CH转协议的基础上,提出了一种改进粒子群算法优化化成带约束的非线性优化问题,然后利用粒子群算法求解,并针对粒子群算法的不足进行相应的改进,最后采用仿真实验测试算法的性能。仿真结果表明,相对于其它改进LEACH路由算法,本文算法有效提高了网络的能量利用率,能够实现节点之间的能耗均衡,使无线传感器的网络生存时间得到延长。     

Cross-Layer Multi-Packet Reception Based Medium Access Control and Resource Allocation for Space-Time Coded MIMO/OFDM

In this paper, a cross-layer design framework for multi-input multi-output (MIMO)/orthogonal frequency division multiplexing (OFDM) based wireless local area networks (WLANs) is proposed. In contrast to conventional systems where the medium access control (MAC) and physical (PHY) layers are separately optimized, our proposed methodology jointly designs a multi-packet reception (MPR) based protocol with adaptive resource allocation. Specifically, a realistic collision model is employed by taking into consideration the PHY layer parameters such as channel information, space-time coded beamforming and multiuser detection, as well as sub-carrier, bit, and power allocation. The allocation problem is formulated, so as to maximize the system throughput, subject to the constraints from both the MAC and PHY layers. These constraints depend on the results of access contention, data packets? length, users? spatial correlation and the quality of channel feedback information. An iterative algorithm is then provided to obtain the optimal solution. Simulation results will show that our proposed approach achieves significant improvement in system performance such as average throughput and packet delay, compared with conventional schemes where cross-layer design and optimization is not used.     

Review and analytical comparison of recursive and nonrecursiveequalization techniques for PAM transmission systems

After near-end crosstalk (NEXT), the principal problem with pulse amplitude modulation (PAM) is intersymbol interference (ISI). The author presents an analytical comparison of various recursive and nonrecursive subtractive equalization techniques which may be used to remove ISI. Properties of subscriber loop responses which may be used in the design of simple and efficient equalizers are also explored. Simulation results are presented comparing the performances of many of the described equalizer structures for an 800 kb/s 2B1Q PAM transmission system operating over 12 kft of 24 AWG cable     

Vectored transmission for digital subscriber line systems

This paper describes the "vectored" transmission technique for digital subscriber line (DSL) systems, which utilizes user coordination at the central office or optical network unit. This method exploits the colocation of the downstream transmitters and of the upstream receivers, in order to achieve far-end crosstalk (FEXT) cancellation and perform multiuser transmission optimization. The performance improvements are particularly pronounced in environments with strong FEXT such as in very high-speed DSL. Discrete multitone is employed for each user with additional constraints on the cyclic prefix length and with the assumption of block-synchronized transmission and reception for downstream and upstream transmission correspondingly. Within each tone, upstream crosstalk is removed by multiple-input-multiple-output decision feedback at the receiving side, while downstream crosstalk is eliminated by analogous preprocessing at the transmitting side. Additionally, the issue of transmission energy allocation in frequency and among users is addressed. Assuming frequency-division duplexing, the corresponding optimization problem is formulated and solved via convex programming both for a fixed upstream-downstream band plan and for a dynamically programmable band plan. The case of power backoff as a means to reduce the impact of crosstalk on alien systems is also treated. Interestingly, the performance of the proposed methods is shown to be very close to known information theory bounds     

Adaptive single snapshot beamforming: a new concept for therejection of nonstationary and coherent interferers

An approach to adaptive beamforming (adaptive reconstruction of a desired signal in the presence of interferers and noise) that uses just a single snapshot to calculate the antenna weights is presented. As in previous studies, a structured and grouped array of sensor elements is assumed. The concept exploits the induced special data structure, which can be described as a generalized rank-one eigenvalue problem and can be solved by means of a linear (overdetermined) system solver. Arbitrary signal statistics are allowed and no difficulties with nonstationary, and coherent interferers arise. Furthermore, the algorithm does not exhibit any transient behavior. Simulations verify its good performance in comparison with the optimum beamformer     

A stochastic importance sampling methodology for the efficientsimulation of adaptive systems in frequency nonselective Rayleigh fadingchannels

We present an IS stochastic technique for the efficient simulation of adaptive systems which employ diversity in the presence of frequency nonselective slow Rayleigh fading and additive, white, Gaussian noise. The computational efficiency is achieved using techniques based on importance sampling (IS). We utilize a stochastic gradient descent (SGD) algorithm to determine the near-optimal IS parameters that characterize the dominant fading process. After accounting for the overhead of the optimization algorithm, average speed-up factors of up to six orders of magnitude [over conventional Monte Carlo (MC)] were attained for error probabilities as low as 10^-11 for a fourth-order diversity model     

An efficient block adaptive decision feedback equalizer implemented in the frequency domain

In this paper, a new block adaptive decision feedback equalizer (DFE) implemented in the frequency domain is derived. The new algorithm is suitable for applications requiring long adaptive equalizers, as is the case in several high-speed wireless communication systems. The inherent "causality" problem appearing in the block adaptive formulation of the DFE equations is overcome by using tentative decisions in place of the unknown ones within each block. These tentative decisions are subsequently improved by using an efficient iterative procedure, which finally converges to the optimum decisions in a few iterations. This procedure is properly initialized by applying a minimization criterion that utilizes all the available information. The whole algorithm, including the iterative procedure, is implemented in the frequency domain and exhibits a considerable reduction in computational complexity, as compared with the conventional DFE, offering, at the same time, a noticeable increase in convergence speed. Additionally, the level of the steady-state MSE, which is achieved by the new algorithm, is practically insensitive to the block length.     

Subband adaptive filtering with real-valued subband signals foracoustic echo cancellation

Adaptive filtering in subbands was originally proposed to overcome the limitations of conventional least-mean-square (LMS) algorithms. In general, subband adaptive filters offer computational savings, as well as faster convergence over the conventional LMS algorithm. However, improvements to current subband adaptive filters could be further enhanced by a more elegant choice of their design/structure. Classical subband adaptive filters employ DFT-based analysis and synthesis filter banks which results in subband signals that are complex-valued. The authors modify the structure of subband adaptive filters by using single-sideband (SSB) modulated analysis and synthesis filter banks, which result in subband signals that are real-valued. This simplifies the realisation of subband adaptive filters     

Fast adaptive blind beamforming algorithm for antenna array in CDMA systems

In this paper, the maximum signal-to-interference-plus-noise ratio (MSINR) beamforming problem in antenna-array CDMA systems is considered. In this paper, a modified MSINR criterion presented in a previous paper is interpreted as an unconstrained scalar cost function. By applying recursive least squares (RLS) to minimize the cost function, a novel blind adaptive beamforming algorithm to estimate the beamforming vector, which optimally combines the desired signal contributions from different antenna elements while suppressing noise and interference, is derived. Neither the knowledge of the channel conditions (fading coefficients, signature sequences and timing of interferers, statistics of other noises, etc.) nor training sequence is required. Compared with previously published adaptive beamforming algorithms based on the stochastic-gradient method, it has faster convergence and better tracking capability in the time-varying environment. Simulation results in various signal environments are presented to show the performance of the proposed algorithm.