Maximization of average number of correctly received symbols over multiple channels in the presence of idle periods

In this study, optimal channel switching (time sharing) strategies are investigated under average power and cost constraints for maximizing the average number of correctly received symbols between a transmitter and a receiver that are connected via multiple flat-fading channels with additive Gaussian noise. The optimal strategy is shown to correspond to channel switching either among at most three different channels with full channel utilization (i.e., no idle periods), or between at most two different channels with partial channel utilization. Also, it is stated that the optimal solution must operate at the maximum average power and the maximum average cost, which facilitates low-complexity approaches for obtaining the optimal strategy. For two-channel strategies, an upper bound is derived, in terms of the parameters of the employed channels, on the ratio between the optimal power levels. In addition, theoretical results are derived for characterizing the optimal solution for channel switching between two channels, and for comparing performance of single channel strategies. Sufficient conditions that depend solely on the systems parameters are obtained for specifying when partial channel utilization cannot be optimal. Furthermore, the proposed optimal channel switching problem is investigated for logarithmic cost functions, and various theoretical results are obtained related to the optimal strategy. Numerical examples are presented to illustrate the validity of the theoretical results.     

Optimal signaling and detector design for M-ary communication systems in the presence of multiple additive noise channels

An M-ary communication system is considered in which the transmitter and the receiver are connected via multiple additive (possibly non-Gaussian) noise channels, any one of which can be utilized for the transmission of a given symbol. Contrary to deterministic signaling (i.e., employing a fixed constellation), a stochastic signaling approach is adopted by treating the signal values transmitted for each information symbol over each channel as random variables. In particular, the joint optimization of the channel switching (i.e., time sharing among different channels) strategy, stochastic signals, and decision rules at the receiver is performed in order to minimize the average probability of error under an average transmit power constraint. It is proved that the solution to this problem involves either one of the following: (i) deterministic signaling over a single channel, (ii) randomizing (time sharing) between two different signal constellations over a single channel, or (iii) switching (time sharing) between two channels with deterministic signaling over each channel. For all cases, the optimal strategies are shown to employ corresponding maximum a posteriori probability (MAP) decision rules at the receiver. In addition, sufficient conditions are derived in order to specify whether the proposed strategy can or cannot improve the error performance over the conventional approach, in which a single channel is employed with deterministic signaling at the average power limit. Finally, numerical examples are presented to illustrate the theoretical results.     

针对不确定流量的多收发机无线网络资源优化研究

多收发机无线网络具有多接口多信道多跳的特点,是今后无线网络发展的趋势。该网络中信道与链路的资源分配,涉及路由、信道分配以及链路调度的联合优化。在以往的研究中通常对网络流量模型进行简化,假设其是确定且相对稳定的。考虑到实际网络中流量不确定性的特征,以网络吞吐量最大化为目标,提出传输流约束、信道资源约束以及干扰约束条件下的资源分配联合优化模型,以及基于不确定流量条件下资源分配最优解的链路调度策略。仿真实验结果证明所提出的路由、信道分配及链路调度方案能够更好地适应变化的网络流量需求。     

Hadamard quantum broadcast channels

We consider three different communication tasks for quantum broadcast channels, and we determine the capacity region of a Hadamard broadcast channel for these various tasks. We define a Hadamard broadcast channel to be such that the channel from the sender to one of the receivers is entanglement-breaking and the channel from the sender to the other receiver is complementary to this one. As such, this channel is a quantum generalization of a degraded broadcast channel, which is well known in classical information theory. The first communication task we consider is classical communication to both receivers, the second is quantum communication to the stronger receiver and classical communication to other, and the third is entanglement-assisted classical communication to the stronger receiver and unassisted classical communication to the other. The structure of a Hadamard broadcast channel plays a critical role in our analysis: The channel to the weaker receiver can be simulated by performing a measurement channel on the stronger receiver’s system, followed by a preparation channel. As such, we can incorporate the classical output of the measurement channel as an auxiliary variable and solve all three of the above capacities for Hadamard broadcast channels, in this way avoiding known difficulties associated with quantum auxiliary variables.     

Improved low-complexity zero-padded OFDM receivers

The recently suggested Generalized Prefix–Orthogonal Frequency Division Multiplexing (GP–OFDM) uses an optimal non-zero guard interval (GI). A GI consisting of all zeros is also known, and the technique is referred to as Zero Padding (ZP–OFDM). ZP–OFDM performs very well, but suffers from a complexity problem. This paper provides two improved and low-complexity receiver designs for ZP–OFDM, which make the convolutions between the transmitted signal and the channel skew-cyclic. The channel matrix becomes ϕ-circulant. Both designs require a one-dimensional optimization. The first new design requires the result of the optimization to be available at the transmitter. The second new design eliminates completely the feedback to the transmitter. Simulation results indicate that proposed ZP–OFDM receivers have significant performance advantages compared with existing ZP–OFDM receivers such as ZP–OFDM–OLA and ZP–OFDM–FAST. The performance advantages are maintained in the presence of channel estimation errors and error-correction coding.     

空时分组编码在多入多出系统中的容量分析

研究瑞利衰落信道下正交空时分组编码的信道容量,针对收端已知信道状态信息(CSI)以及收发两端均知CSI的2种情况,给出相应的容量分析及计算公式的推导。在收端已知CSI情况下,采用泰勒级数展开方法,给出一种信道容量的近似表达式,该式可有效简化原有精确公式的计算,获得与真实值非常相似的结果。在收发两端均知CSI情况下,提出一种基于最陡下降算法的简单计算方法,用于求解最优中断门限值,该方法可避免原有求解方法的大量搜索和计算。仿真结果表明,所给出的信道容量精确表达式以及近似表达式均与相应的计算机仿真结果一致,从而验证了所推公式的有效性。     

A convex optimization approach to signal reconstruction over switching networks

In this paper we consider signal reconstruction over communication network channels that can be modeled as input switching systems. Such systems can be associated with a variety of applications including control and estimation over networks. In particular, we formulate the signal reconstruction problem as a prototypical model matching problem where the various mappings involved belong to a class of input switching systems. The design interest is placed on minimizing the worst case or stochastic average performance of this model matching system over all possible switchings with an H₂ norm as the performance criterion. This minimization is performed over all stable receivers R in the class of input switching systems. For the particular setup at hand, and in the case of matched switching, two convergent sequences to the optimal solution from above and below respectively are formulated in terms of quadratic programs. An approximate solution with any a priori given precision is possible by finite truncation. Also, it is shown that in the cases of arbitrary, partially matched or unmatched switching, the optimal receiver R need not depend on the switching sequence and that it can be obtained as a linear time-invariant solution to an associated H₂ norm optimization.     

Capacity-approaching block-based transceivers with reduced redundancy

We present a transceiver structure for a frequency selective channel that allows the introduction of reduced redundancy. At the same time we optimize the transmitter and receiver in this structure to maximize the information rate. We show that we can decouple the problem of optimizing the transmitter and the receiver in two different problems by using to the data processing inequality of information theory. The problem of finding the transmitters is a difficult non-linear optimization problem. For that reason we present two simple algorithmic procedures in order to obtain suboptimal solutions. We present simulation results that show that the proposed design outperforms other existing ones in the literature. We also show that the proposed scheme is asymptotically optimal in the sense that it approaches the channel capacity.     

Comprehensive Capacity Ensured Distributed Binary Power Allocation in Dense Cognitive Networks

Considering the capacity gain of the secondary system and the capacity loss of the primary system caused by the newly accessing user, a distributed binary power allocation (admittance criterion) is proposed in dense cognitive networks including plentiful secondary nodes. The case that the secondary nodes can detect both transmitter and receiver of the primary system is analyzed first; considering that it is hard for the secondary system to detect the primary receiver without assuming the cooperation with primary system, the case that the secondary nodes only have the information about the primary transmitter is analyzed thereafter. In particular, we propose a simple estimation strategy to transform the problem of detecting primary receiver to the problem of detecting primary transmitter for the latter case. And a general power allocation scheme which is suitable for both of two cases is proposed afterward. By simulations, the restriction on the distance between secondary transmitter and primary receiver, and the restriction on the distance between secondary and primary transmitters are respectively achieved for the two cases. These two restrictions reflect that the capacities of both primary system and secondary system can be ensured to the predefined extents if these two restrictions on the distances are respectively satisfied in two cases.     

一种基于有限信道的能量高效节点调度机制

在低负载、低功耗无线传感器网络中,节点状态切换的能量消耗因为用于数据传输的能量较小而变得不可忽略。针对此问题,提出了结合多信道技术与时分多路访问( TDMA)技术的节点调度算法。该算法设计了基于接收端的连续时隙分配策略以减少节点状态切换次数,并且在可用无线信道有限的约束条件下,提出了信道分配与时隙调整机制,实现了时隙重用并最小化有限信道约束对优化节点状态切换次数的影响。仿真实验结果表明,当可用无线信道数为3~5时,算法能够有效地改善节点能量效率。当可用无线信道数大于3之后,算法能够获得优化的数据汇聚时间。     

多天线Rayleigh衰落相关信道的平均信道容量

研究了空间衰落相关的Rayleigh信道的平均信道容量,其发射端和接收端均采用多天线系统.在实际情况中,接收端有理想的信道状态信息,而发射端没有任何信道信息,因此在各发射天线上采用等功率分配进行发射.本文推导了具有2根发射天线和多根接收天线（TIMO）衰落相关信道的平均信道容量,将其和Monte-Carlo仿真结果比较,并进一步研究空间相关性对信道容量的影响.数值结果表明：信道的空间相关性降低了平均信道容量,而且不同于多入单出（MISO）信道,当信噪比一直增大,由相关性带来的容量损失也增大且不收敛.     

MIMO‐UWB smart antenna communication characteristics for different antenna arrays of transmitters

The channel capacity of indoor multiple‐input multiple‐output ultra‐wide band (MIMO‐UWB) transmission for smart antenna is presented. The genetic algorithm (GA) is used to synthesize the radiation pattern of the directional antenna array to maximize the capacity performance in indoor MIMO‐UWB communication system. Three types of antenna arrays such as circular shape, L shape and Y shape arrays are used in the transmitter and their corresponding capacity on several paths in the indoor environment are calculated. The UWB impulse responses of the indoor channel for any transmitter‐receiver location are computed by applying shooting and bouncing ray/image (SBR/image) techniques, inverse fast Fourier transform and Hermitian processing. By using the calculated frequency response, the capacity performance of the synthesized antenna pattern on MIMO‐UWB system can be computed. Based on the topography of the antenna array and the capacity formula, the array pattern synthesis problem can be reformulated into an optimization problem and solved by the GA algorithm. The GA algorithm optimization is applied to a high order nonlinear optimization problem. The novelties of our approach is not only choosing capacity as the cost function instead of sidelobe level of the antenna pattern, but also considering the antenna feed length effect of each array element. The cost function for the problem is nonsmooth and discontinuous with respect to the antenna pattern. It is difficult to solve by gradient methods, since the derivative is hard to derive. The GA algorithm is employed to optimize the excitation voltages and feed lengths for these antenna arrays to increase the capacity. The strong point of the GA is that it can find out the solution even if the performance index cannot be formulated by simple equations. Numerical results show that the synthesized antenna array pattern is effective to focus maximum gain to the LOS path for these antenna arrays. In other words, the receiver can increase the received signal energy to noise ratio. The synthesized array pattern also can mitigate severe multipath fading in complex propagation environment. As a result, the capacity can be increased substantially in indoor MIMO‐UWB communication system. The investigated results can help communication engineers improve their planning and design of indoor wireless communication. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

A cross-layer optimization framework for joint channel assignment and multicast routing in multi-channel multi-radio wireless mesh networks

Existing literature on multicast routing protocols in wireless mesh networks (WMNs) from the view point of the links involved in routing are divided into two categories: schemes are aimed at multicast construction with minimal interference which is known as NP hard problem. In contrast, other methods develop network-coding-based solutions with the main objective of throughput maximization, which can effectively reduce the complexity of finding the optimal routing solution from exponential to polynomial time. The proposed framework in this paper is placed in the second category. In multi-channel multi-radio WMNs (MCMR WMNs), each node is equipped with multiple radios, each tuned on a different channel. In this paper, for the first time, we propose a cross-layer convex optimization framework for joint channel assignment and multicast throughput maximization in MCMR WMNs. The proposed method is composed of two phases: in the first phase, using cellular learning automata, channels are assigned to the links established between the radios of the nodes in a distributed fashion such that the minimal interference coefficient for each link is provided. Then, the resultant channel assignment scheme is utilized in the second phase for throughput maximization within an iterative optimization framework based on Lagrange relaxation and primal problem decomposition. We have conducted many experiments to contrast the performance of our solution against many representative approaches.     

Physical-layer secrecy outage of spectrum sharing CR systems over fading channels

In this paper, we investigate the physical-layer secrecy outage performance of underlay spectrum sharing systems over Rayleigh and log-normal fading channels in the presence of one eavesdropper. In particular, the secondary transmitter sends data to the legitimate receiver under the constraints of the interference temperature at the primary receiver, while suffering the wiretap from the eavesdropper. Closed-form and approximated expressions are derived for the secrecy outage probability over Rayleigh and log-normal fading channels, respectively. The accuracy of our performance analysis is verified by simulation results.     

Broadcast anti-jamming systems

In a traditional anti-jamming system a transmitter who wants to send a signal to a single receiver spreads the signal power over a wide frequency spectrum with the aim of stopping a jammer from blocking the transmission. In this paper, we consider the case that there are multiple receivers and the transmitter wants to broadcast a message to all receivers such that colluding groups of receivers cannot jam the reception of any other receiver. We propose efficient coding methods that achieve this goal and link this problem to well-known problems in combinatorics. We also link a generalisation of this problem to the Key Distribution Pattern problem studied in combinatorial cryptography.     

一种基于人工噪声的MISO相关信道物理层安全方法

现有基于人工噪声的物理层安全方法都假设信道是相互独立的,但是多天线通信系统中存在的信道空间相关性会降低系统安全容量。针对这一问题,设计了一种基于人工噪声的多入单出(MISO)相关信道物理层安全方法。通过合法用户信道参数的协方差矩阵得到发送端的信道相关矩阵,利用该矩阵与合法用户信道参数乘积的零空间作为人工噪声的生成空间,随机生成人工噪声对窃听方实现干扰。仿真结果表明,在存在信道空间相关性的情况下,本方法比现有方法的平均系统安全容量提高了约0.5 bit/s/Hz。     

Adaptive power allocation with quality-of-service guarantee in cognitive radio networks

This paper proposes a novel power control policy for a cognitive radio network as an effort to maximize throughput under the average interference power constraint. The underlined policy ensures delay-related quality of service (QoS) requirements with reduced interference to the primary user. In this work we also take into account the peak and average transmit power constraints for the secondary user. An optimization problem associated with the power control policy is formulated based on a cross-layer framework, where the queue on data link layer is serviced by the power control policy at the physical layer. A recursive algorithm under the power constraints is developed to solve for the optimal solution. It is shown that the reduction of average interference to the primary user is related closely to the QoS requirements. The analysis derives the average interference power limits to the primary user in fading channels with guaranteed QoS requirements for the secondary user. The numerical results show the effectiveness of the proposed power control policy.     

Strong Converse for the Feedback-Assisted Classical Capacity of Entanglement-Breaking Channels

Quantum entanglement can be used in a communication scheme to establish a correlation between successive channel inputs that is impossible by classical means. It is known that the classical capacity of quantum channels can be enhanced by such entangled encoding schemes, but this is not always the case. In this paper, we prove that a strong converse theorem holds for the classical capacity of an entanglement-breaking channel even when it is assisted by a classical feedback link from the receiver to the transmitter. In doing so, we identify a bound on the strong converse exponent, which determines the exponentially decaying rate at which the success probability tends to zero, for a sequence of codes with communication rate exceeding capacity. Proving a strong converse, along with an achievability theorem, shows that the classical capacity is a sharp boundary between reliable and unreliable communication regimes. One of the main tools in our proof is the sandwiched Rényi relative entropy. The same method of proof is used to derive an exponential bound on the success probability when communicating over an arbitrary quantum channel assisted by classical feedback, provided that the transmitter does not use entangled encoding schemes.     

Optimal Resource Allocation in Overlay Multicast

Although initially proposed as the deployable alternative to IP multicast, the overlay network actually revolutionizes the way network applications can be built. In this paper, we study the rate allocation problem in overlay-based multirate multicast, which can be understood as a utility-based resource allocation problem. Each receiver is associated with a utility defined as a function of its streaming rate. Our goal is to maximize the aggregate utility of all receivers, subject to network capacity constraint and data constraint. The latter constraint is unique in overlay multicast, mainly due to the dual role of end hosts as both receivers and senders. We use a price-based approach to address this problem. Two types of prices, network price and data price, are generated with regard to the two constraints of the problem. A distributed algorithm is proposed, where each receiver adjusts its flow rate according to the associated network price and data price. The algorithm is proved to converge to the optimal point, where the aggregate utility of all receivers is maximized. We implement our algorithm using an end-host-based protocol. Our protocol purely relies on the coordination of end hosts to accomplish tasks originally assigned to network routers, which makes it directly deployable to the existing network infrastructure.     

蜂窝网中基于分布式约束满足算法的改进信道分配

随着蜂窝网业务需求的不断增长,如何利用有限的信道资源在各小区间进行复用,以便既能避免移动用户之间的干扰,又能满足所有移动用户的话务请求,使蜂窝系统容量大大增加,已成为一项重要研究课题。此类问题属于NP-hard的信道分配问题(Channel Assignment Problem,CAP),将CAP问题形式化为分布式约束满足问题(DC-SP),然后提出基于改进现有的信道分配策略,以获得更高的信道利用率、较令人满意的系统服务质量,尽可能满足所有用户的话务请求。将利用尽可能简单、搜寻时间短的算法,并将现有的benchmark问题进行仿真。实验表明,该方案对有效改进信道分配问题,充分利用有限的信道资源,降低系统的阻塞率,有着较好的应用前景。