Low complexity margin adaptive resource allocation in downlink MIMO-OFDMA system

We study the downlink multiuser Multiple Input Multiple Output-Orthogonal Frequency Division Multiple Access (MIMO-OFDMA) system for margin adaptive resource allocation where the Base Station (BS) has to satisfy individual Quality of Service (QoS) constraints of the users subject to transmit power minimization. Low complexity solutions involve beamforming techniques for multiuser inter-stream interference cancellation. However, when beamforming is introduced in the margin adaptive objective, it becomes a joint beamforming and resource allocation problem. We propose a sub-optimal twostep solution which decouples beamforming from subcarrier and power allocation. First a reduced number of user groups are formed and then the problem is formulated as a convex optimization problem. Finally an efficient algorithm is developed which allocates the best user group to each subcarrier. Simulation results reveal comparable performance with the hugely complex optimal solution.     

Crosstalk-aware dynamic spectrum management algorithm for green DSL systems

Dynamic spectrum management (DSM) techniques mitigate crosstalk in digital subscriber line (DSL) networks by adapting the transmit spectra to the actual noise and channel conditions. Conventional DSM schemes are designed based on single-objective optimization, either belonging to the rate-adaptive or margin-adaptive category. In this paper, an efficient crosstalk-aware DSM (CA-DSM) algorithm which jointly considers both the data rate and power is proposed to search for the best rate-power tradeoff solution based on the network conditions. The crosstalk-aware power strategy prevents transmitters which contribute excessive crosstalk from being allocated high power, thereby reducing the aggregate crosstalk noise in the system. A convex cost function is used to formulate the DSM optimization problem wherein two coefficients are introduced to make the CA-DSM algorithm adaptive to different network conditions. An iterative power update strategy is proposed for the CA-DSM algorithm to minimize the cost function. Convergence properties of the CA-DSM algorithm along with existence and uniqueness of optimal power solutions are examined analytically and illustrated graphically. Simulation results show that the proposed CA-DSM algorithm can provide a significantly better rate-power tradeoff performance compared to existing spectrum management schemes.     

An optimal spectrum‐balancing algorithm for digital subscriber lines based on particle swarm optimization

This paper presents a new algorithm for optimal spectrum balancing in modern digital subscriber line (DSL) systems using particle swarm optimization (PSO). In DSL, crosstalk is one of the major performance bottlenecks, therefore various dynamic spectrum management algorithms have been proposed to reduce excess crosstalks among users by dynamically optimizing transmission power spectra. In fact, the objective function in the spectrum optimization problem is always nonconcave. PSO is a new evolution algorithm based on the movement and intelligence of swarms looking for the most fertile feeding location, which can solve discontinuous, nonconvex and nonlinear problems efficiently. The proposed algorithm optimizes the weighted rate sum. These weights allow the system operator to place differing qualities of service or importance levels on each user, which makes it possible for the system to avoid the selfish‐optimum. We can show that the proposed algorithm converges to the global optimal solutions. Simulation results demonstrate that our algorithm can guarantee fast convergence within a few iterations and solve the nonconvex optimization problems efficiently. Copyright © 2008 John Wiley & Sons, Ltd.     

Dynamic spectrum management for next-generation DSL systems

The performance of DSL systems is severely constrained by crosstalk due to the electromagnetic coupling among the multiple twisted pairs making up a phone cable. In order to reduce performance loss arising from crosstalk, DSL systems are currently designed under the assumption of worst-case crosstalk scenarios leading to overly conservative DSL deployments. This article presents a new paradigm for DSL system design, which takes into account the multi-user aspects of the DSL transmission environment. Dynamic spectrum management (DSM) departs from the current design philosophy by enabling transceivers to autonomously and dynamically optimize their communication settings with respect to both the channel and the transmissions of neighboring systems. Along with this distributed optimization, when an additional degree of coordination becomes available for future DSL deployment, DSM will allow even greater improvement in DSL performance. Implementations are readily applicable without causing any performance degradation to the existing DSLs under static spectrum management. After providing an overview of the DSM concept, this article reviews two practical DSM methods: iterative water-filling, an autonomous distributed power control method enabling great improvement in performance, which can be implemented through software options in some existing ADSL and VDSL systems; and vectored-DMT, a coordinated transmission/reception technique achieving crosstalk-free communication for DSL systems, which brings within reach the dream of providing universal Internet access at speeds close to 100 Mb/s to 500 m on 1-2 lines and beyond 1 km on 2-4 lines. DSM-capable DSL thus enables the broadband age.     

Optimal multiuser spectrum balancing for digital subscriber lines

Crosstalk is a major issue in modern digital subscriber line (DSL) systems such as ADSL and VDSL. Static spectrum management, which is the traditional way of ensuring spectral compatibility, employs spectral masks that can be overly conservative and lead to poor performance. This paper presents a centralized algorithm for optimal spectrum balancing in DSL. The algorithm uses the dual decomposition method to optimize spectra in an efficient and computationally tractable way. The algorithm shows significant performance gains over existing dynamics spectrum management (DSM) techniques, e.g., in one of the cases studied, the proposed centralized algorithm leads to a factor-of-four increase in data rate over the distributed DSM algorithm iterative waterfilling.     

Optimal dynamic spectrum allocation-assisted latency minimization for multiuser mobile edge computing

Mobile Edge Computing (MEC) has been envisioned as an efficient solution to provide computation-intensive yet latency-sensitive services for wireless devices. In this paper, we investigate the optimal dynamic spectrum allocation-assisted multiuser computation offloading in MEC for overall latency minimization. Specifically, we first focus on a static multiuser computation offloading scenario and jointly optimize users' offloading decisions, transmission durations, and Edge Servers' (ESs) resource allocations. Owing to the nonconvexity of our joint optimization problem, we identify its layered structure and decompose it into two problems: a subproblem and a top problem. For the subproblem, we propose a bisection search-based algorithm to efficiently find the optimal users' offloading decisions and ESs’ resource allocations under a given transmission duration. Second, we use a linear search-based algorithm for solving the top problem to obtain the optimal transmission duration based on the result of the subproblem. Further, after solving the static scenario, we consider a dynamic scenario of multiuser computation offloading with time-varying channels and workload. To efficiently address this dynamic scenario, we propose a deep reinforcement learning-based online algorithm to determine the near-optimal transmission duration in a real-time manner. Numerical results are provided to validate our proposed algorithms for minimizing the overall latency in both static and dynamic offloading scenarios. We also demonstrate the advantages of our proposed algorithms compared to the conventional multiuser computation offloading schemes.     

Fast Meta-heuristics for Multiuser Detection in DS-CDMA Systems

In [1], an evolution strategy (ES) multiuser detector was proposed and exhibits good performance. This letter analyzes the search behavior of the ES detector and points out it can be greatly enhanced via a simple technique. A heuristic multiuser detection algorithm is presented, which employs the neighborhood structure characteristics of the optimum multiuser detection (OMD) problem and produces local optima efficiently. A well-chosen perturbation strategy is applied to improve the solution quality in the following step. Simulations results show the meta-heuristic algorithm proposed can find the (near) optimum solution rapidly with lower computational complexity and has better bit error rate (BER) performance.     

Adaptive DFE Multiuser Receiver for CDMA Systems using Two-Step LMS-Type Algorithm: An Equalization Approach

This paper presents an adaptive decision feedback equalizer (DFE) based multiuser receiver for code division multiple access (CDMA) systems over smoothly time-varying multipath fading channels using the two-step LMS-type algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh-distributed tap coefficients. The receiver uses an adaptive minimum mean square error (MMSE) multiuser channel estimator based on the reduced Kalman least mean square (RK-LMS) algorithm to predict these tap coefficients (Kohli and Mehra, Wireless Personal Communication 46:507–521, 2008). We propose the design of adaptive MMSE feedforward and feedback filters by using the estimated channel response. Unlike the previously available Kalman filtering algorithm based approach (Chen and Chen, IEEE Transactions on Signal Processing 49:1523–1532, 2001), the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser receiver. The computer simulation results are presented to show the substantial improvement in its bit error rate performance over the conventional LMS algorithm based receiver. It can be inferred that the proposed multiuser receiver proves to be robust against the nonstationarity introduced due to channel variations, and it is also beneficial for the multiuser interference cancellation and data detection in CDMA systems.     

Advanced DSL management

Today's digital subscriber line deployments are often conservatively engineered to function in a statistically worst case environment. Crosstalk is treated as unknown and uncontrollable random noise, even though it is manmade. Other impairments are often treated by simply adding margin to crosstalk. While this simplistic practice currently suffices, it often provisions unnecessarily low bit rates. This article shows methods that can increase these bit rates and decrease DSL failure rates. Data can be collected about individual telephone lines and cables from loop databases, by automated test equipment, or from DSL modems. This data may then be fed into an advanced DSL management system with a database of DSL loop and noise characteristics, and an analysis engine that tailors DSL deployments to the actual individual line characteristics, to increase provisioned DSL bitrates while simultaneously increasing reliability and lowering maintenance costs. The maximum service can be provisioned with high accuracy, eliminating many service activation failures. Automated maintenance routines can even isolate faults before a customer experiences them. Dynamic spectrum management (DSM) treats crosstalk as the manmade noise it is, and jointly optimizes DSL transmit spectra and signals to minimize crosstalk and maximize received signals, allowing substantially higher DSL speeds than current practice. This opens the door for new services, including symmetric enterprise services and full video service, with minimal physical plant upgrade.     

Energy and spectral efficiency trade‐off for the downlink OFDM‐distributed antenna systems

This paper investigates an energy efficient optimization scheme for the downlink multiuser OFDM‐distributed antenna systems. We adopt a multicriteria optimization method to offer a systematic study on the relationship between spectral efficiency (SE) and energy efficiency (EE). First, we transform the energy efficient optimization problem with high complexity into a simpler downlink multiuser OFDM problem. Then, using the weighted sum method in multicriteria optimization, an optimal energy efficient scheme is presented to allocate the available power to balance the trade‐off between SE and EE efficiently. Simulation results demonstrate that the energy efficient scheme is effective, and there existed a trade‐off between SE and EE in the downlink multiuser OFDM‐distributed antenna systems. Copyright © 2013 John Wiley & Sons, Ltd.     

Robust Linear Receivers for Multiaccess Space–Time Block-Coded MIMO Systems: A Probabilistically Constrained Approach

Traditional multiuser receiver algorithms developed for multiple-input–multiple-output (MIMO) wireless systems are based on the assumption that the channel state information (CSI) is precisely known at the receiver. However, in practical situations, the exact CSI may be unavailable because of channel estimation errors and/or outdated training. In this paper, we address the problem of robustness of multiuser MIMO receivers against imperfect CSI and propose a new linear technique that guarantees the robustness against CSI errors with a certain selected probability. The proposed receivers are formulated as probabilistically constrained stochastic optimization problems. Provided that the CSI mismatch is Gaussian, each of these problems is shown to be convex and to have a unique solution. The fact that the CSI mismatch is Gaussian also enables to convert the original stochastic problems to a more tractable deterministic form and to solve them using the second-order cone programming approach. Numerical simulations illustrate an improved robustness of the proposed receivers against CSI errors and validate their better flexibility as compared with the robust multiuser MIMO receivers based on the worst case designs.     

An Equalizer Adaptation Algorithm to Reduce Jitter in Binary Receivers

This brief describes a hardware-efficient technique for adaptive equalization that minimizes jitter in baseband binary nonreturn-to-zero serial links. Whereas traditional least mean square (LMS) adaptation minimizes the mean squared error only at the center of the received eye pattern, this algorithm explicitly includes low jitter as part of its optimization criteria. The resulting equalizer coefficients provide a compromise between maximizing noise margin and minimizing jitter at the equalizer output. The adaptation algorithm operates on 1-bit (signed) signals and can be efficiently combined with binary phase detection in an integrated receiver. Behavioral simulations for a 10-Gb/s optical fiber link show that the proposed approach improves timing margin compared with sign–sign LMS adaptation.     

基于IPSO-ICA算法的盲多用户检测

为了有效抑制CDMA通信系统中的多址干扰,提出了一种将新改进的粒子群(IPSO)算法应用到基于独立分量分析(ICA)的盲多用户检测中的方法.首先在IPSO算法中,使用自适应非线性递减惯性权重w降低早熟概率,利用拉伸技术打破早熟现象,从而使最优解更加精确.然后将IPSO算法融合到ICA算法中,得到IPSO-ICA算法来进行盲多用户检测.最后仿真结果表明,在相同通信环境下,该盲多用户检测比已有的基于FastICA和PSO-ICA算法的盲多用户检测的误码率更小,收敛速度更快.     

An Adaptive Multiuser Detection Algorithm for CDMA Systems Using Antenna Diversity

Based on the minimum mean squared error (MMSE) between the data stream and the linear combiner output, a new multiuser detection (MUD) algorithm that combines space–time (ST) processing and antenna array on direct-sequence CDMA signals is proposed. The proposed ST-MUD algorithm is proved to be equivalent to two existing MMSE-based ST-MUD algorithms, and the theoretical BER performances for all the three algorithms are the same. The most attractive feature of the new ST-MUD algorithm is based on the fact that the new method does not require explicit estimation of channel and signaling information. This avoids any channel estimation error, and the method is thus more robust and more accurate than the other two ST-MUD algorithms in practical implementation. Adaptation of the proposed ST-MUD algorithm is implemented by using training sequences. Performance of this new multiuser detector is compared with that of two existing MMSE multiuser detectors and the conventional single-user space–time rake receiver through simulations. The proposed ST-MUD algorithm provides a performance better than existing algorithms and is especially suitable for practical CDMA systems.     

单天线功率约束下的能效预编码优化设计

针对多小区多用户下行链路系统,研究了能效传输预编码设计问题。不同于传统设计中的和功率约束,由于实际系统中各天线的功率由其各自配备的功率放大器的线性度所限制,考虑更加实际的单天线功率约束。目标优化问题建模为最大化能效/谱效,同时满足各用户速率约束以及单天线功率约束。为了求解该优化问题,利用凸近似逼近的方法,将原始问题转化为凸优化问题,并提出了一种有效迭代优化算法求解该优化问题。MATLABAL数值仿真结果验证了所提算法的有效性。      

DSL: Dynamic and Self‐Learning Schedule Method of Multiple Controllers in SDN

For the reliability of controllers in a software defined network (SDN), a dynamic and self‐learning schedule method (DSL) is proposed. This method is original and easy to deploy, and optimizes the combination of multiple controllers. First, we summarize multiple controllers’ combinations and schedule problems in an SDN and analyze its reliability. Then, we introduce the architecture of the schedule method and evaluate multi‐controller reliability, the DSL method, and its optimized solution. By continually and statistically learning the information about controller reliability, this method treats it as a metric to schedule controllers. Finally, we compare and test the method using a given testing scenario based on an SDN network simulator. The experiment results show that the DSL method can significantly improve the total reliability of an SDN compared with a random schedule, and the proposed optimization algorithm has higher efficiency than an exhaustive search.     

一种基于禁忌搜索的多用户检测方法

本文提出一种实现码分多址(ＣＤＭＡ)系统上多用户检测(ＭＵＤ)的禁忌搜索(ｔａｂｕｓｅａｒｃｈ)的方法。 该方法利用传统检测方法的输出作为初始解,直接应用禁忌搜索算法来解决最佳多用户检测的非线性优化组合问题。通过分析以及对同步和异步情况的仿真表明,该方法简单易于实现,具有多项式的计算复杂度,对远近问题不敏感,并且能够得到与最佳检测方法(ＯＤ)非常接近的误码率性能和抗多址干扰性能．     

An efficient resource-allocation scheme for spatial multiuser access in MIMO/OFDM systems

Fast adaptive transmission has been recently identified as a key technology for exploiting potential system diversity and improving power-spectral efficiency in wireless communication systems. An adaptive resource-allocation approach, which jointly adapts subcarrier allocation, power distribution, and bit distribution according to instantaneous channel conditions, is proposed for multiuser multiple-input multiple-output (MIMO)/orthogonal frequency-division multiplexing systems. The resultant scheme is able to: 1) optimize the power efficiency; 2) guarantee each user's quality of service requirements, including bit-error rate and data rate; 3) ensure fairness to all the active users; and 4) be applied to systems with various types of multiuser-detection schemes at the receiver. For practical implementation, a reduced-complexity allocation algorithm is developed. This algorithm decouples the complex multiuser joint resource-allocation problem into simple single-user optimization problems by controlling the subcarrier sharing according to the users' spatial separability. Numerical results show that significant power and diversity gains are achievable, compared with nonadaptive systems. It is also demonstrated that the MIMO system is able to multiplex several users without sacrificing antenna diversity by using the proposed algorithm.     

A New Algorithm for Optimum Multiuser Detection in Synchronous CDMA Systems

Optimum multiuser detection for Code Division Multiple Access (CDMA) systems requires the solution of an NP-hard combinatorial optimization problem. It is well known that the computational complexity of the optimum multiuser detector is exponential with the number of active users in the system. In order to reduce the complexity of the optimum multiuser detection, we propose a Reduced Complexity Maximum Likelihood (RCML) algorithm that includes a set of novel certain boundary rules and characteristics. We investigate the performance and complexity tradeoffs for the RCML algorithm by conducting a set of simulations; Maximum Likelihood (ML) detection as a reference for performance comparisons, and relaxation based Semidefinite Programming (SDPB) algorithm as a reference for complexity comparisons. We show that the RCML algorithm is a promising algorithm for its computational savings over relaxation based algorithms in lightly-to-moderately loaded CDMA systems, and for its optimality in highly loaded CDMA systems.