Distributed Power Allocation With Rate Constraints in Gaussian Parallel Interference Channels

This paper considers the minimization of transmit power in Gaussian parallel interference channels, subject to a rate constraint for each user. To derive decentralized solutions that do not require any cooperation among the users, we formulate this power control problem as a (generalized) Nash equilibrium (NE) game. We obtain sufficient conditions that guarantee the existence and nonemptiness of the solution set to our problem. Then, to compute the solutions of the game, we propose two distributed algorithms based on the single user water-filling solution: The sequential and the simultaneous iterative water-filling algorithms, wherein the users update their own strategies sequentially and simultaneously, respectively. We derive a unified set of sufficient conditions that guarantee the uniqueness of the solution and global convergence of both algorithms. Our results are applicable to all practical distributed multipoint-to-multipoint interference systems, either wired or wireless, where a quality of service in (QoS) terms of information rate must be guaranteed for each link.     

Cognitive Radio MIMO Gaussian Broadcast Channels with the Power Constraint

The cognitive radio multiple-input multiple-output Gaussian broadcast channels are studied where multiple antennas are available for both primary users and secondary users in a spectrum sharing environment, and the sum-rate capacity is also obtained under both the SUs’ transmit power constraint and interference power constraint at the primary receivers. The paper principally consists of two steps. First, a duality technique and dirty paper coding are adopted to simplify the channels. Second, we propose an iterative power allocation algorithm to obtain the maximum sum-rate capacity and examine the effects of the constraint parameters on the concerned quantities. Finally, numerical simulation results are presented to validate the proposed theoretical analysis.     

Capacity Results for Block-Stationary Gaussian Fading Channels With a Peak Power Constraint

A peak-power-limited single-antenna block-stationary Gaussian fading channel is studied, where neither the transmitter nor the receiver knows the channel state information, but both know the channel statistics. This model subsumes most previously studied Gaussian fading models. The asymptotic channel capacity in the high signal-to-noise ratio (SNR) regime is first computed, and it is shown that the behavior of the channel capacity depends critically on the channel model. For the special case where the fading process is symbol-by-symbol stationary, it is shown that the codeword length must scale at least logarithmically with SNR in order to guarantee that the communication rate can grow logarithmically with SNR with decoding error probability bounded away from one. An expression for the capacity per unit energy is also derived. Furthermore, it is shown that the capacity per unit energy is achievable using temporal on–off signaling with optimally allocated on symbols, where the optimal on-symbol allocation scheme may depend on the peak power constraint.      

Frame Synchronization for Gaussian Channels

The problem of locating a periodically inserted frame synchronization pattern in random data for aM-ary digital communication system operating over the additive white Gaussian noise channel is considered. The optimum maximum-likelihood decision rule, high signal-to-noise approximate maximum likelihood decision rule, and ordinary correlation decision rule for frame synchronization are derived for both coherent and noncoherent phase demodulation. A general lower bound on synchronization probability is derived for the coherent correlation rule. Monte Carlo computer simulations of all three decision rules, along with evaluations of the lower bound for the coherent correlation rule, were performed for the coherent MPSK, coherent, and noncoherentMary orthogonal, and 16 QAM signaling schemes. These results show that in each case the high signal-to-noise maximum-likelihood rules have a performance nearly equal to that of the maximum-likelihood rules over a wide range of practically interesting signal-to-noise ratios (SNR's). These high SNR decision rules also provide significant performance improvement over the simple correlation rules. Moreover, they are much simpler to implement than the maximum-likelihood decision rules and, in fact, are no more complex than the correlation rules.     

On Maximizing Coverage in Gaussian Relay Channels

Results for Gaussian relay channels typically focus on maximizing transmission rates for given locations of the source, relay, and destination. We introduce an alternative perspective, where the objective is maximizing coverage for a given rate. The new objective captures the problem of how to deploy relays to provide a given level of service to a particular geographic area, where the relay locations become a design parameter that can be optimized. We evaluate the decode-and-forward (DF) and compress-and-forward (CF) strategies for the relay channel with respect to the new objective of maximizing coverage. When the objective is maximizing rate, different locations of the destination favor different strategies. When the objective is coverage for a given rate, and the relay is able to decode, DF is uniformly superior in that it provides coverage at any point served by CF. When the channel model is modified to include random fading, we show that the monotone ordering of coverage regions is not always maintained. While the coverage provided by DF is sensitive to changes in the location of the relay and the path loss exponent, CF exhibits a more graceful degradation with respect to such changes. The techniques used to approximate coverage regions are new and may be of independent interest.      

和速率约束下衰落高斯MIMO广播信道的和功率优化

 本文研究了在系统和速率一定的条件下有着高斯噪声的衰落MIMO广播信道和功率最小化问题.该问题通常存在于无线通信系统动态资源分配中,是和功率约束下衰落MIMO下行链路和速率最大化的互补问题.首先利用MIMO MAC和MIMO BC的对偶性,将问题描述和转化为凸最优化问题,在此基础上,利用子梯度法和二分法,设计了相应的快速迭代的多用户注水算法,用于计算基站的发射功率.理论分析和数值仿真结果表明,该算法全局有效地收敛于最小的和功率.     

空间相关信道下的交替多用户调度算法

针对多用户多输入多输出（MIMO）系统,研究了空间相关信道下的多用户调度问题。通过推导用户信道向量夹角的统计特征,分析了多用户调度算法对所调度用户间正交性的影响。分析结果表明在空间相关信道下现有基于串行搜索的调度方法在统计意义上降低了被调度用户之间的正交性,从而导致基于串行搜索的调度算法与最优的穷举搜索之间存在较大的性能差距。为了提高相关信道下多用户MIMO系统的性能,提出了一种基于交替搜索的多用户调度算法及其低复杂度实现方法。仿真结果表明,所提出的用户调度算法能够有效地弥补基于串行搜索的调度方法的性能损失,在空间独立信道和空间相关信道下以较低的计算复杂度获得接近穷举搜索的最优性能。      

Feedback Capacity of Stationary Gaussian Channels

The feedback capacity of additive stationary Gaussian noise channels is characterized as the solution to a variational problem in the noise power spectral density. When specialized to the first-order autoregressive moving-average noise spectrum, this variational characterization yields a closed-form expression for the feedback capacity. In particular, this result shows that the celebrated Schalkwijk-Kailath coding achieves the feedback capacity for the first-order autoregressive moving-average Gaussian channel, positively answering a long-standing open problem studied by Butman, Tiernan-Schalkwijk, Wolfowitz, Ozarow, Ordentlich, Yang-Kavc?ic?-Tatikonda, and others. More generally, it is shown that a k-dimensional generalization of the Schalkwijk-Kailath coding achieves the feedback capacity for any autoregressive moving-average noise spectrum of order k. Simply put, the optimal transmitter iteratively refines the receiver's knowledge of the intended message. This development reveals intriguing connections between estimation, control, and feedback communication.     

Efficient Shadow Encoding Scheme Towards Power Spectrum Density in Digital Network Communication

Wireless Personal Communications - Digital communication based on the conversion of data which only possible through digital conversion techniques. From the last couple of years, many digital...     

Efficient Modulation for Band-Limited Channels

This paper attempts to present a comprehensive tutorial survey of the development of efficient modulation techniques for bandlimited channels, such as telephone channels. After a history of advances in commercial high-speed modems and a discussion of theoretical limits, it reviews efforts to optimize two-dimensional signal constellations and presents further elaborations of uncoded modulation. Its principal emphasis, however, is on coded modulation techniques, in which there is an explosion of current interest, both for research and for practical application. Both block-coded and trellis-coded modulation are covered, in a common framework. A few new techniques are presented.     

Towards a Universal Data Transport System

It is anticipated that a ubiquitous data transport system will require integration of local area and wide area networks. The combined network will need to present a uniform appearance to the user, be effective as a transport mechanism for a great variety of traffic patterns, and be economically appropriate for a wide range of consumer products. Learning from telephony and from experiments with a local area network, we conclude that the transport system must seek a clean separation of function and protocol between the network and its users. This separation is achieved by a byte-stream architecture that carries control and data bytes over switched virtual circuits. A DATAKIT packet switch demonstrates how the byte-stream concept can integrate local area and wide area network objectives. This switch is an assembly of interface modules connected by a pair of short passive buses. Each type of interface module serves one type of remote equipment and, if need be, terminates the protocol of that equipment. There are interface modules for trunks that lead to other packet switches, for terminals, and for host computers. Other modules provide system timing, switching, network control, and maintenance support.     

Efficient approximation of Gaussian filters

This article presents improvements to the efficient approximation of Gaussian filters by sequentially applying uniform box filters. For 1-D filters, a simple and nearly optimal fit criterion for the length S of the box filters to the approximated Gaussian is given. For 2-D filters, a new method is introduced to improve the circular symmetry and the lowpass properties of the approximation without increasing the computational complexity. Finally, a multirate implementation for large Gaussian filters is presented that requires significantly fewer floating-point operations than the standard technique     

Capacity Region and Optimum Power Control Strategies for Fading Gaussian Multiple Access Channels With Common Data

A Gaussian multiple access channel (MAC) with common data is considered. Capacity region when there is no fading is known in an implicit form. We provide an explicit characterization of the capacity region and provide a simpler encoding/decoding scheme than that mentioned in work by Slepian and Wolf. Next, we give a characterization of the ergodic capacity region when there is fading, and both the transmitters and the receiver know the channel perfectly. Then, we characterize the optimum power allocation schemes that achieve arbitrary rate tuples on the boundary of the capacity region. Finally, we provide an iterative method for the numerical computation of the ergodic capacity region and the optimum power control strategies.     

Hessian and Concavity of Mutual Information, Differential Entropy, and Entropy Power in Linear Vector Gaussian Channels

Within the framework of linear vector Gaussian channels with arbitrary signaling, the Jacobian of the minimum mean square error and Fisher information matrices with respect to arbitrary parameters of the system are calculated in this paper. Capitalizing on prior research where the minimum mean square error and Fisher information matrices were linked to information-theoretic quantities through differentiation, the Hessian of the mutual information and the entropy are derived. These expressions are then used to assess the concavity properties of mutual information and entropy under different channel conditions and also to derive a multivariate version of an entropy power inequality due to Costa.     

Performance-Complexity Tradeoffs of Raptor Codes over Gaussian Channels

We investigate the performance-complexity tradeoffs of Raptor codes over Gaussian channels. Two different implementations of the belief-propagation (BP) decoding algorithm are considered, which we respectively refer to as "message-reset decoding" and "incremental decoding". We show that incremental decoding offers great advantages over message-reset decoding in terms of this tradeoff     

Asynchronous Iterative Water-Filling for Gaussian Frequency-Selective Interference Channels

This paper considers the maximization of information rates for the Gaussian frequency-selective interference channel, subject to power and spectral mask constraints on each link. To derive decentralized solutions that do not require any cooperation among the users, the optimization problem is formulated as a static noncooperative game of complete information. To achieve the so-called Nash equilibria of the game, we propose a new distributed algorithm called asynchronous iterative water-filling algorithm. In this algorithm, the users update their power spectral density (PSD) in a completely distributed and asynchronous way: some users may update their power allocation more frequently than others and they may even use outdated measurements of the received interference. The proposed algorithm represents a unified framework that encompasses and generalizes all known iterative water-filling algorithms, e.g., sequential and simultaneous versions. The main result of the paper consists of a unified set of conditions that guarantee the global converge of the proposed algorithm to the (unique) Nash equilibrium of the game.     

高斯干扰信道中基于速率分裂的译码次序算法

针对高斯干扰信道,该文提出一种基于最大最小公平性的译码次序新算法.该算法通过采用速率分裂技术来提高系统和速率.基于该算法,推导出和速率近似最大的速率分裂层数表达式.数值结果表明,在一定干扰强度范围内的两用户对称高斯干扰信道中,采用该译码次序新算法得到的和速率较已有的贪婪算法得到的和速率有明显提高,并随着干扰强度的增加,其和速率逼近 Sason 给出的和速率内界.     

QoS‐Guaranteed Multiuser Scheduling in MIMO Broadcast Channels

This paper proposes a new multiuser scheduling algorithm that can simultaneously support a variety of different quality‐of‐service (QoS) user groups while satisfying fairness among users in the same QoS group in MIMO broadcast channels. Toward this goal, the proposed algorithm consists of two parts: a QoS‐aware fair (QF) scheduling within a QoS group and an antenna trade‐off scheme between different QoS groups. The proposed QF scheduling algorithm finds a user set from a certain QoS group which can satisfy the fairness among users in terms of throughput or delay. The antenna trade‐off scheme can minimize the QoS violations of a higher priority user group by trading off the number of transmit antennas allocated to different QoS groups. Numerical results demonstrate that the proposed QF scheduling method satisfies different types of fairness among users and can adjust the degree of fairness among them. The antenna trade‐off scheme combined with QF scheduling can improve the probability of QoS‐guaranteed transmission when supporting different QoS groups.