大规模MIMO系统中的一种自适应SIC检测算法

与传统系统相比,大规模多入多出（MIMO）系统能更加有效地提高频谱效率。利用传统的最小均方误差（MMSE）信号检测算法求解大规模MIMO系统,虽然检测结果接近最优,但是矩阵的求逆运算导致计算的复杂度非常高。提出了一种自适应排序干扰消除（SIC）检测算法,在逐次超松弛（SOR）迭代运算的基础上,通过干扰消除降低待检测矩阵的维度。通过仿真分析,得出所提算法的复杂度低于Jacobi、SOR检测算法,且在迭代次数较少的情况下,算法的误码率（BER）性能明显优于SOR检测算法。     

Partitioned scheduling for sphere decoding with runtime constraints for practical MIMO communication systems

This paper presents an effective scheduling scheme for sphere decoding (SD) with runtime constraints, targeting the practical multiple‐input multiple‐output (MIMO) communication systems where neither the interleaving scheme nor its block size cannot be designed freely. The proposed scheme imposes runtime constraints on SD to distribute the errors due to the early termination of SD. Because the distributed errors may be corrected effectively by forward error correction, the error‐rate performance can be improved; experimental results show that the performance improvement is approximately 2dB in terms of the signal‐to‐noise ratio to achieve a bit‐error rate of 10^?4 in 4 × 4 16‐QAM MIMO systems. Copyright © 2015 John Wiley & Sons, Ltd.     

Coherent detection for optical duobinary communication systems

We propose and analyze coherent detection schemes for optical duobinary modulation. Thus, new quantum limits are established at 15, 30, and 31 photons/bit for coherent duobinary based on homodyne, heterodyne synchronous, and heterodyne asynchronous detection, respectively.     

Large system decentralized detection performance under communication constraints

The problem of decentralized detection in a sensor network subjected to a total average power constraint and all nodes sharing a common bandwidth is investigated. The bandwidth constraint is taken into account by assuming non-orthogonal communication between sensors and the data fusion center via direct-sequence code-division multiple-access (DS-CDMA). In the case of large sensor systems and random spreading, the asymptotic decentralized detection performance is derived assuming independent and identically distributed (iid) sensor observations via random matrix theory. The results show that, even under both power and bandwidth constraints, it is better to combine many not-so-good local decisions rather than relying on one (or a few) very-good local decisions.     

Queueing models for systems with synchronization constraints

The authors consider queueing that occur naturally in the study of a class of resource-sharing problems under synchronization constraints such as resequencing and fork-join primitives. These queueing models are amenable to a representation in terms of a state recursion. The proposed methods of analysis are complementary and draw on classical ideas of queuing theory as well as on mathematical tools from the theory of stochastic ordering and ergodic theory. The state recursion is at the center of all aspects of the analysis, be it for developing the exact solutions, obtaining bounds on system performance or establishing the stability conditions. The ideas are illustrated on simple models of resequencing and fork-join synchronization, which emphasis put on deriving computable bounds on the performance measures     

Pilot-aided data detection in DS-CDMA communication systems

The paper deals with the performance evaluation of a pilot-aided channel parameter estimation method suitable for applications in direct-sequence code-division multiple-access (DS-CDMA) communication systems. Differently from previous approaches, a suitable selective interference cancellation algorithm is used in order to reduce multipath interference on the channel parameter estimation and the detection of the information-bearing signals due to pilot signal replicas. Simulation results demonstrate the good channel parameter estimation capability of the proposed method in the case of uplink communications and different types of receiving schemes. In order to highlight the good behavior of the proposed approach, performance comparisons are shown with the ideal case of perfect knowledge of the channel parameter values, as well as with the classical implementation of the considered channel parameter estimation algorithm.     

Improved error probability evaluation methods for direct detection optical communication systems

The problem of average error probability evaluation for direct detection binary optical communications in the presence of avalanche gain, intersymbol interference, and colored additive Gaussian noise is considered. Tight new upper and lower bounds, together with a modified Gaussian quadrature rule based on approximate moments, are derived and evaluated. The bounds are found to be much tighter than the Chernoff bound though only slightly more complex to evaluate, and can be used as approximations to the error probability in most cases of practical interest. Taken together the new bounds and the modified Gaussian quadrature rule form a comprehensive set of performance evaluation tools offering a judicious balance between complexity and accuracy.     

Blind detection of equalization errors in communication systems

In adaptive channel equalization, transmitted symbol estimates at the equalizer output may be in error because of excessive channel noise, convergence of the equalizer to a “closed-eye” local minimum, or error propagation if the equalizer has a decision feedback structure. This paper is concerned with the detection of equalization errors (i.e., errors in transmitted symbol estimates) in a blindfolded manner whereby no direct access to the channel input is required. The detection problem is cast into a binary hypothesis testing framework. Assuming a linear communication channel that is time-invariant during the test interval, a relationship between the presence of equalization errors and time variations in the underlying linear model taking the transmitted symbol estimates to the equalizer input is established. Based on this relationship, a uniformly most powerful test is constructed to detect the presence of equalization errors in finite-length observations. Finite sample size and asymptotic detection performance of the test is studied. A method for estimating the equalization delay without direct access to the channel input is developed. The effectiveness of the test is illustrated by way of computer simulations     

MIMO系统中基于星座约束的LAS检测算法

似然上升搜索(LAS)算法是一种启发式邻域搜索算法,能够对空分复用的大规模多输入多输出(MIMO)系统的接收信号进行检测。为了降低传统LAS算法的复杂度,提出了一种基于星座约束(CC)的CC–LAS算法。该算法利用一个星座约束(CC)结构判定每个候选解的可靠性,根据可靠性判定结果缩小候选解的邻域空间,再利用LAS算法对不可靠候选解进行检测。提出的CC–LAS算法通过忽略LAS邻域空间中大量不必要的邻居向量,排除对低可靠度信号的低效处理,从而大幅度降低了传统LAS算法的计算复杂度。仿真结果表明,提出的CC–LAS算法的误码率(BER)性能与传统的LAS算法非常接近,并且在信噪比(SNR)相同的情况下,能够大幅度降低计算复杂度。     

Signal detection games with power constraints

Formulates and solves maximin and minimax detection problems for signals with power constraints. These problems arise whenever it is necessary to distinguish between a genuine signal and a spurious one designed by an adversary with the principal goal of deceiving the detector. The spurious (or deceptive) signal is subject to certain constraints, such as limited power, which preclude it from replicating the genuine signal exactly. The detection problem is formulated as a zero-sum game involving two players: the detector designer and the signal designer. The payoff is the probability of error of the detector, which the detector designer tries to minimize and the deceptive signal designer to maximize. For this detection game, saddle point solutions-whenever possible-or otherwise maximin and minimax solutions are derived under three distinct constraints on the deceptive signal power; these distinct constraints involve lower bounds on (i) the signal amplitude, (ii) the time-averaged power, and (iii) the expected power. The cases of independent and identically distributed and correlated signals are considered     

空间光通信中分布式天线的信号检测研究

针对空间光通信中随机信道传播时延导致接收信号符号间干扰的特殊性使分布式发射天线多入多出(MIMO)信号的线性检测算法更加复杂这一问题,提出了一种基于Neyman-Pearson(NP)融合准则的分布式天线信号检测算法。仿真结果表明,当接收信号同步时,NP算法具有较好的健壮性,其性能优于等增益合并(EGC)算法,与最佳合并(OC)算法相当;当接收信号异步时,NP算法要明显优于EGC和OC算法,抑制接收符号间干扰,能体现出分布式天线系统的空间分集性能。     

Statistical detection for communication channels with intersymbol interference

The optimum detector under a fixed delay constraint D is derived for channels having memory and additive noise. The resulting receiver is recursive and does not grow with the message length. Its structure is presented for linear channels (AM and PSK) with known (or estimated) impulse response and noise statistics. The intersymbol interference is assumed to extend for L sampling periods and the receiver is allowed a "look-ahead" at D future received samples. Simulation results using actual channel characteristics show the detector to outperform a transversal equalizer even for relatively small values of D.     

Pilot embedding for joint channel estimation and data detection in MIMO communication systems

A novel pilot-aided joint channel estimation and data detection method for MIMO communication systems is proposed. Unlike, conventional methods where pilots are time-multiplexed with data symbols, a pilot-embedding method where low-level pilots are transmitted concurrently with the data is used to obtain an initial estimate of the channel such that a turbo decoding process can be started. The soft information obtained from the turbo decoder is subsequently used to improve channel estimates.     

Natural communication with information systems

Pervasive networking and sophisticated computing open opportunities for collaborative information processing independent of time and space. In this instance the information system becomes an enhancer of human intellect, as well as a mediator for communication among participants. The human user favors the sensory dimensions of sight, sound, and touch as primary channels of communication. Machines that can accommodate these modes promise flexibilities and functionalities that transcend the traditional mouse and keyboard. The paper describes research to establish human-computer interfaces that capture attributes of natural face-to-face communication. An experimental multimodal system is developed to study several aspects of natural style human-computer communication. While as yet primitive, the technologies of image and gaze processing, hands-free conversation, and force feedback tactile transduction are combined and used simultaneously for manipulating objects in a shared workspace. Software agents fuse the sensory signals to estimate and interpret user intent. Current areas of experimental application include disaster relief/crisis management, telemedicine/rehabilitation, and mobile office/wearable computers     

Cross-Layer optimization for LDPC-coded multirate multiuser systems with QoS constraints

In this paper, we propose a new multirate multiple-access wireless system implemented by variable spreading gain and chip-level random interleaving. The receiver employs a flexible chip-level iterative multiuser detection scheme where the variable spreading gain affects only the despreading parameters. Optimization across the physical and network layers in the uplink of such a system is treated. It is assumed that each user employs an low-density parity-check (LDPC) code to protect its data. At the physical layer, the quality of service (QoS) requirement is specified in terms of the target bit error rate (BER) of each user. Optimal user transmit powers are dynamically adjusted according to the current system load and the corresponding rate requirements. At the network layer, the QoS requirements include the call blocking probabilities, call connection delays, packet congestion probabilities and packet loss rates. To maximize the average revenue of the network subject to both call-level and packet-level QoS constraints, a multicriterion reinforcement learning (MCRL)-based adaptive call admission control (CAC) method is proposed that can easily handle multiple average QoS requirements. Unlike existing model-based approaches, the MCRL-based technique does not require the explicit knowledge of the state transition probabilities to derive the optimal policy. This feature is important when the number of states is so large that model-based optimization algorithms become infeasible, which is typically the case for a large integrated service network supporting a number of different service types.     

现代通信系统电源设计

通信设备使用的电源器件有很多种,从前端的功率因数校正(PFC)AC／DC电源到后端的高效DC／DC模块和负载点(POL)转换器,不一而足。从需要很高效率的中间总线转换器(IBC),到那些日趋细小轻巧的VoIP数字电话,以及要求多路紧密调节电压(7～13路输出)的数字用户线(xDSL)电源等,DC／DC电源在现代通信中获得了广泛应用。     

Optimal power control for Rayleigh-faded multiuser systems with outage constraints

How can we achieve the conflicting goals of reduced transmission power and increased capacity in a wireless network, without attempting to follow the instantaneous state of a fading channel? In this paper, we address this problem by jointly considering power control and multiuser detection (MUD) with outage-probability constraints in a Rayleigh fast-fading environment. The resulting power-control algorithms (PCAs) utilize the statistics of the channel and operate on a much slower timescale than traditional schemes. We propose an optimal iterative solution that is conceptually simple and finds the minimum sum power of all users while meeting their outage targets. Using a derived bound on outage probability, we introduce a mapping from outage to average signal-to-interference ratio (SIR) constraints. This allows us to propose a suboptimal iterative scheme that is a variation of an existing solution to a joint power control and MUD problem involving SIR constraints. We further use a recent result that transforms complex SIR expressions into a compact and decoupled form, to develop a noniterative and computationally inexpensive PCA for large systems of users. Simulation results are presented showing the closeness of the optimal and mapped schemes, speed of convergence, and performance comparisons.     

Consistency in models for distributed learning under communication constraints

Motivated by sensor networks and other distributed settings, several models for distributed learning are presented. The models differ from classical works in statistical pattern recognition by allocating observations of an independent and identically distributed (i.i.d.) sampling process among members of a network of simple learning agents. The agents are limited in their ability to communicate to a central fusion center and thus, the amount of information available for use in classification or regression is constrained. For several basic communication models in both the binary classification and regression frameworks, we question the existence of agent decision rules and fusion rules that result in a universally consistent ensemble; the answers to this question present new issues to consider with regard to universal consistency. This paper addresses the issue of whether or not the guarantees provided by Stone's theorem in centralized environments hold in distributed settings.     

Photodetectors for optical communication systems

The characteristics of high-sensitivity photodetectors suitable for wide bandwidth optical communication systems are summarized. Photodiodes, photomultipliers, and photoconductive detectors for wavelengths from 0.3 µm to 10.6 µm are covered. The use of internal current gain by means of avalanche and electron multiplication and by means of optical heterodyne detection to increase sensitivity of high speed photodetectors is discussed. The application to visible and infrared laser communication systems is reviewed.     

Data converters for communication systems

Data converters are playing an ever increasingly important role in digital communication channels. As VLSI technologies scale, more of the signal processing is performed in the digital domain, making superior converter design critical. Attributes of various modern analog-to-digital converters such as flash and ΣΔ are described