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.     

Joint spectrum management and constrained partial crosstalk cancellation in a multi-user xDSL environment

In modern DSL systems, crosstalk is a major source of performance degradation. Crosstalk cancellation techniques have been proposed to mitigate the effect of crosstalk. However, the run-time complexity of these crosstalk cancellation techniques grows with the square of the number of lines. Therefore one has to be selective in cancelling crosstalk to reduce complexity. Secondly, crosstalk cancellation requires signal-level coordination between transmitters or receivers, which is not always available. Because of accessibility constraints, crosstalk between certain lines cannot be cancelled and so has to be mitigated through spectrum management. After a complexity study, this paper presents a solution for the joint spectrum management and constrained partial crosstalk cancellation problem. The complexity of the partial crosstalk cancellation part of the problem is reduced based on a line selection and user independence observation. However, to fully benefit from these observations, power loading has to be applied in the spectrum management part. We therefore also consider ON/OFF power loading, which has a low complexity and shows only a minor performance degradation compared to normal power loading. The resulting algorithm will be compared to currently available algorithms for independent spectrum management and partial crosstalk cancellation.     

基于随机共振的双门限协作频谱感知算法

针对现有频谱感知算法在低信噪比（SNR）环境中性能检测不佳的问题以及传统随机共振（SR）检测弱信号的方法在实际应用中存在的局限性,通过设置最优门限,计算出最优的协作用户数量,提出了一种基于随机共振的双门限协作频谱感知算法,并对提出的算法进行了性能分析。DCSSR算法通过将位于双门限不确定区域的统计数据经过随机共振系统,进一步提高频谱感知算法在低信噪比下的检测性能。仿真结果表明,在不同信噪比和虚警概率下,DCSSR算法相较于传统单门限能量协作算法、双门限能量协作算法以及单门限随机共振协作算法,检测性能都得到了提升。在信噪比为-20 dB时,提出的DCSSR算法相较于传统单门限能量检测协作算法,检测概率提高了80%。     

Efficient error detection in soft data fusion for cooperative spectrum sensing

The primary objective of cooperative spectrum sensing (CSS) is to determine whether a particular spectrum is occupied by a licensed user or not, so that unlicensed users called secondary users (SUs) can utilize that spectrum, if it is not occupied. For CSS, all SUs report their sensing information through reporting channel to the central base station called fusion center (FC). During transmission, some of the SUs are subjected to fading and shadowing, due to which the overall performance of CSS is degraded. We have proposed an algorithm which uses error detection technique on sensing measurement of all SUs. Each SU is required to re-transmit the sensing data to the FC, if error is detected on it. Our proposed algorithm combines the sensing measurement of limited number of SUs. Using Proposed algorithm, we have achieved the improved probability of detection (PD) and throughput. The simulation results compare the proposed algorithm with conventional scheme.     

Spectrum-efficient optical drop-add-drop network with a centralized multi-carrier light source

Traditional ROADM networks strictly follow the coarse ITU-T standard wavelength grids and channel spacings, which would result in low optical spectrum utilizations under dynamic traffic requests of variable spectrum lightpaths. This paper presents a spectrum-efficient optical drop-add-drop network with a centralized multi-carrier light source (C-MCLS). The C-MCLS generates thousands of optical carriers with uniform and narrow channel spacings. The optical carriers are distributed to each network node as light sources on demand through ROADMs designed with the carrier-drop function. Spectrum-aware optical carrier allocation is studied first in the proposed network. This paper proposes a Minimum Fragmentation Request First (MinFragRF) optical carrier allocation algorithm compared with the Maximum Spectrum Request First (MaxSRF) and Minimum Spectrum Request First (MinSRF) allocation algorithms. This paper also studies how channel spacings of optical carriers impact on the network performance under variable traffic demands. We perform both network analysis and simulations to evaluate the network performance in terms of the lightpath blocking probability (LP_BP) and the effective spectrum efficiency. We analytically derive the formulas of LP_BP and average effective spectrum efficiency in the proposed network. Simulation results show that the proposed network with more narrow channel spacings greatly reduces the lightpath blocking probability compared with the traditional ROADM network. The average effective spectrum efficiency of the proposed network can be improved about 100 % compared with that of the traditional ROADM network by choosing appropriate network design parameters. The MinFragRF allocation algorithm has a better LP_BP performance than that of the MaxSRF and has a better spectrum utilization efficiency than that of the MinSRF. The optimal channel spacing evaluations show that narrow channel spacings such as 6.25 and 12.5 GHz greatly improve LP_BP performance when low bit-rate traffic requests dominate in the traffic model. However, as the high bit-rate traffic requests increase, the performance advantage of narrow channel spacings is gradually disappearing.     

一种基于干扰温度限制的信道与功率联合分配新算法

随着无线通信业务的不断增长,频谱资源越来越紧缺,然而另一方面大量授权的无线频谱却被闲置或者利用率极低,于是认知无线电技术应运而生,已成为无线通信领域的研究热点。认知无线电的基本思想是次用户（认知用户）利用主用户（授权用户）未占用的空闲频谱进行通信,其可用无线资源是根据授权用户的频谱使用情况而动态变化的。因此,能否实现对系统可用无线资源的合理有效管理,对整个认知无线电系统性能的优劣起着决定性作用。本文提出了一种在干扰温度限制下基于公平的功率与信道联合分配算法,该算法在主用户干扰温度及次用户发射功率的双重限制下,以最大化系统容量为基本目标,实现信道与功率的联合分配,并且引入贫困线来保证各个用户信道分配的公平性。论文建立了该问题的非线性规划数学模型,给出了模型的求解方法,并进一步设计了具体分配算法及其步骤。论文对干扰门限分别为-90dBm、-95dBm、-100dBm、-105dBm、-110dBm时的系统归一化容量累积分布函数进行了仿真比较,发现当干扰门限越低时,本文算法的优势越明显。这是因为在干扰门限较低时,干扰温度限制是功率分配的主要制约因素,而本文的算法正是基于干扰门限进行分配的。因此基于干扰温度限制的公平的功率与信道联合分配算法具有良好的性能,在保证了系统的公平性效益的同时,提高了系统的归一化容量。      

基于生存系统模型的认知无线电网络频谱管理自治系统设计

针对动态频谱接入和认知无线电技术对频谱管理的新要求,采用分层的频谱管理理念,基于生存系统模型(Viable System Model,VSM)设计适合认知无线电网络的频谱管理自治系统,该系统通过节点参与频谱管理,网络自我约束等措施,实现认知无线电网络对频谱的自治。最后,将该系统应用于一种异构网络共存的频管案例设计中,仿真分析表明:本文提出的基于VSM的频谱管理自治系统响应时间大幅度降低;认证效率为O(1),较传统方式性能有很大提升。     

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.     

Coalitional game‐based behavior analysis for spectrum access in cognitive radios

The core of cognitive radio paradigm is to introduce cognitive devices able to opportunistically access the licensed radio bands. The coexistence of licensed and unlicensed users prescribes an effective spectrum hole‐detection and a non‐interfering sharing of those frequencies. Collaborative resource allocation and spectrum information exchange are required but often costly in terms of energy and delay. In this paper, each secondary user (SU) can achieve spectrum sensing and data transmission through a coalitional game‐based mechanism. SUs are called upon to report their sensing results to the elected coalition head, which properly decides on the channel state and the transmitter in each time slot according to a proposed algorithm. The goal of this paper is to provide a more holistic view on the spectrum and enhance the cognitive system performance through SUs behavior analysis. We formulate the problem as a coalitional game in partition form with non‐transferable utility, and we investigate on the impact of both coalition formation and the combining reports costs. We discuss the Nash Equilibrium solution for our coalitional game and propose a distributed strategic learning algorithm to illustrate a concrete case of coalition formation and the SUs competitive and cooperative behaviors inter‐coalitions and intra‐coalitions. We show through simulations that cognitive network performances, the energy consumption and transmission delay, improve evidently with the proposed scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

一种面向水下移动通信的组合差分扩频水声通信方法

针对水下移动平台(AUVs)直接序列扩频(DSSS)水声通信过程中大多普勒时变带来的频偏及载波相位跳变问题,该文提出一种组合差分扩频通信方法。该方法设计一种2维组合差分(TCD)扩频帧结构,接收端通过对重复码时域加窗相关实现时变多普勒粗估计;接收端提出一种频率压缩-能量接收器(FC-ED),通过采用能量检测接收器提高接收端处理多普勒容限,使用频率压缩法多频点压缩处理进一步提高系统鲁棒性,实现扩频码识别映射解码;最后提出一种组合差分算法,实现2维组合扩频间的极性差分解码,在能量接收映射解码基础上引入极性调制,进一步提高频谱利用率。经理论及仿真试验分析,该方法具备一定的抗时变多普勒能力,在恒加速度相对运动–8 dB信噪比条件下误码率小于10^–2。     

Availability-aware service provisioning in SD-EON-based inter-datacenter networks

The tremendous transmission capacity and flexible spectrum allocation scheme make elastic optical networks (EONs) one of the most promising infrastructures for constructing the interconnection in datacenter (DC) networks. Meanwhile, as DC traffics exhibit highly dynamic and heterogeneous features, differentiated service provisioning schemes are desired. In this paper, we take the advantage of centralized network control and management provided by the software-defined elastic optical networks (SD-EONs) and investigate availability-aware service provisioning in SD-EON-based inter-datacenter (inter-DC) networks. We first describe the problem of availability-aware service provisioning in SD-EON-based inter-DC networks and present the theoretical analysis for service availability. Then, we propose an availability-aware service provisioning algorithm (ASP) that leverages different path protection schemes to satisfy different service availability requirements. A service downgrading (SD) strategy is also designed as a supplement of ASP to further improve its performance. Simulation results show that the proposed ASP-SD algorithm can effectively improve the spectrum efficiency without sacrificing availability.     

频率估计的一种多段同频正弦信号频谱相关算法

为提高低信噪比条件下正弦信号的频率估计精度,针对多段同频正弦信号,该文提出一种基于频谱相关的频率估计算法。首先,构造加权因子对多段同频正弦信号频谱进行加权积累,得到最优加权积累频谱;然后,将多段同频正弦信号的最优加权积累频谱和累加频谱进行相关运算,得到频谱相关谱;最后,谱峰搜索频谱相关谱,实现频率的精确估计。模拟结果验证了该文算法的有效性。     

Distributed Cooperative Wideband Spectrum Sensing Algorithm Based on Subspace Methods

We present a novel distributed cooperative spectrum sensing algorithm from compressive sampling in wideband cognitive radio (CR) networks. Each CR utilizes compressive sampling to reduce data acquisition costs. A subspace method is then adopted to directly detect occupied channels without reconstructing the sparse spectrum. To obtain the spatial diversity gain, global signal subspace is estimated by the distributed projection approximation subspace tracking (DPAST) algorithm in which the CRs exchange information locally and cooperate without the need for a fusion center. Then, the orthogonality property of the signal subspace and noise subspace can be exploited to find spectral support to complete the spectrum sensing. We study the convergence behavior of the DPAST algorithm and evaluate the performance of spectrum sensing. Simulation results indicate that the DPAST can effectively estimate the global signal subspace, and the proposed compressed wideband spectrum sensing scheme performs better than spectrum sensing at a single CR.     

A universal frequency reuse scheme in LTE‐A heterogeneous networks

Effective inter‐cell interference mitigation has been extensively studied because of its outstanding cell‐edge signal quality improvement capability. Conventional static inter‐cell interference coordination strategies, including fractional frequency reuse and soft frequency reuse, have received much attention owing to their effectiveness in mitigating interference and low complexity in implementation. However, they are less effective when dealing with dense uneven traffic distributions and dynamic traffic demands and thus incur low spectrum utilization in some cells and spectrum shortage in others. This paper proposes a universal frequency reuse scheme in a two‐layer Long Term Evolution‐Advanced heterogeneous network to ensure good throughput for all user equipment (UE), especially UEs at cell edge. The proposed scheme allows each cell to use all the spectrum resources, limited by an orderly regulation of all sub‐bands. This scheme minimizes the potential occurrence probability of inter‐cell co‐sub‐band interference through an intra‐cell sub‐band resource management. Furthermore, a graph‐theoretic based sub‐band allocation algorithm is developed to optimize UE throughput performance, especially for the cell‐edge low signal to interference noise ratio UEs. A comprehensive performance comparison among different frequency reuse schemes is conducted by considering performance metrics, including cell‐edge throughput, average throughput, and signal to interference noise ratio cumulative distribution function. Simulation result shows that the universal frequency reuse scheme outperforms other two schemes significantly. Copyright © 2016 John Wiley & Sons, Ltd.     

A middleware service for employing and evaluating resource management algorithms in distributed networks

The first part of this paper introduces the design of a middleware‐based service which is valuable for distributed networks for mainly managing their resources. The second part evaluates the performance of a distributed intelligent network (D‐IN), which comprises the proposed service together with a resource management algorithm. We test the network's performance by building and emulating its basic functionality, based on distributed object technology (DOT), in a real environment. The resource management algorithm mainly aims at avoiding congestion and balancing load. Its implementation uses the ICALB algorithm (Comput. Commun. 2002; 25 (17):1548–1556) model. Its incorporation is succeeded through the use and implementation of the distributed middleware‐based service. It is a CORBA‐based service that is used for successfully managing resource management algorithms, such as ICALB, facilitate their operation, and solving classes of problems related to communications over the distributed network, sharing of resources spread over the network, scheduling, synchronization, and management of various tasks. By this means we argue that the method that we use can be employed for operating in various distributed networks. We also evaluate the network's performance by measuring various D‐IN node parameters with critical meaning and by showing the improvements that appeared to the D‐IN from the operation of both the ICALB algorithm and the proposed service. Copyright © 2005 John Wiley & Sons, Ltd.     

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.     

分层认知无线电网络中基于稳定匹配的资源分配算法

频谱资源的合理分配是认知无线电技术追求的目标之一,随着认知无线电网络中的次用户(SUs)数量不断增加,频谱资源的精确、实时分配与管控越来越难以实现。针对此问题,该文提出一种分层的认知无线电网络(CRN)架构,多个管理实体专注于为各层用户提供频谱服务;并在该架构下,提出一种基于稳定匹配的资源分配算法,用户通过自主协商形成分配结果,不仅保证了主用户(PUs)对次用户的功率限制,还充分考虑了各自的效用。仿真结果表明,所提算法的性能接近于最优方案,并降低了计算复杂度和系统时延。     

快变信道环境下基于支持向量回归的频谱预测

频谱预测是一种通过分析历史频谱数据获得频谱使用规律,从而预测未来频谱使用状态的技术。为了实现快变信道（本文指信道占用状态快速变化）环境下频谱状态的可靠预测,提出了一种基于支持向量回归的频谱预测算法。比较了在不同训练样本数时,该算法与一个典型的BP神经网络频谱预测算法的性能差异,结果表明所提算法在小样本学习时,预测效果更为理想。并在此基础上,加入正确检测概率和虚警概率,验证了当频谱检测不理想条件下,支持向量回归算法预测的可行性。      

采用支持向量机的宽带频谱感知算法

认知无线电系统中,压缩感知理论已广泛运用于宽带频谱检测。但是,压缩感知中的重构问题造成频谱检测算法计算复杂度高,且在低信噪比下检测效果不佳。本文提出了采用支持向量机的宽带频谱感知算法,该算法利用支持向量机建立频谱检测分类器,代替信号的重构与检测过程。根据系统对实时性的要求,分别设计了多级二元分类器感知算法和单级多元分类器感知算法。前者适用于分级数有限且实时性要求不高的场景,后者可大幅降低系统的算法复杂度,降低感知时间,适用于实时检测系统。仿真结果表明,与基于重构的能量检测算法相比,本文提出的两种算法均可以有效改善系统对噪声的鲁棒性,提高在较小信噪比下的检测性能。      

Joint spectrum load balancing and handoff management in cognitive radio networks: a non-cooperative game approach

We propose a non-cooperative game theory based algorithm for spectrum management problem in cognitive radio networks taking into account the spectrum handoff effects. The objective is to minimize the spectrum access time of Secondary Users (SUs) which are competing for spectrum opportunities in heterogeneous environment. In this paper, the preemptive resume priority (PRP) M/G/1 queuing model is used to characterize the multiple handoff and data delivery time of SUs. Also an explicit solution for channels selection probabilities of each SU is extracted for PRP M/M/1 model specifically. The effect of handoffs is considered as the interrupted packets which return to the SUs’ low priority queue when the high priority Primary User’s packets are arrived to take service. The queuing delay of SUs’ and the effect of these returned packets are considered in order to balance the load of SUs on channels so that the minimum spectrum access time is sensed by each SU. The non-cooperative spectrum load balancing with handoff management game is proposed to find a distributed solution for each SU. It is shown that this game has a unique Nash equilibrium point which can be achieved by SUs as decision makers. At this equilibrium, each SU incurs the minimum delay on all channels while the free spectrum holes of channels are utilized efficiently. Simulation results are provided to evaluate the performance of the proposed scheme in terms of spectrum access delay, fairness, and channels spectrum holes utilization.