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This paper proposes a cross-layer optimization framework for the wireless sensor networks. In a wireless sensor network, each sensor makes a local observation of the underlying physical phenomenon and sends a quantized version of the observation to a central location via wireless links. As the sensor observations are often partial and correlated, the network performance is a complicated and nonseparable function of individual data rates at each sensor. In addition, due to the shared nature of wireless medium, nearby transmissions often interfere with each other. Thus, the traditional "bit-pipe" model for network link capacity no longer holds. This paper deals with the joint optimization of source quantization, routing, and power control in a wireless sensor network. We follow a separate source and channel coding approach and show that the overall network optimization problem can be naturally decomposed into a source coding subproblem at the application layer and a wireless power control subproblem at the physical layer. The interfaces between the layers are precisely the dual optimization variables. In addition, we introduce a novel source coding model at the application layer, which allows the efficient design of practical source quantization schemes at each sensor. Finally, we propose a dual algorithm for the overall network optimization problem. The dual algorithm, when combined with a column-generation method, allows an efficient solution for the overall network optimization problem. [ABSTRACT FROM AUTHOR]

Iterative channel estimation can improve the channel-state information (CSI) with respect to noniterative estimation. New iterative channel estimators based on the expectation-maximization (EM) algorithm are proposed in this paper. A first estimator, called the unbiased EM (UEM), is designed to unbias the EM estimates. A second estimator is then put forward, which is based on the expectation-conditional-maximization (ECM) algorithm, and its complexity is lower than that of the EM. An unbiased ECM (UECM) estimator is also proposed. Although the unbiasedness of the UEM and UECM estimators is not rigorously proved, the use of these names is explained in the paper. The new estimators are compared with well-known ones, such as the EM, the decision-directed (DD), and the data-aided (DA) estimators. Simulations are reported for a turbo receiver operating over frequency-selective multiple-input multiple-output channels. It is shown that the UEM channel estimator outperforms the EM, and that the ECM-based estimators are very close to the EM-based ones. [ABSTRACT FROM AUTHOR]

Intra-session network coding has been shown to offer significant gains in terms of achievable throughput and delay in settings where one source multicasts data to several clients. In this paper, we consider a more general scenario where multiple sources transmit data to sets of clients over a wireline overlay network. We propose a novel framework for efficient rate allocation in networks where intermediate network nodes have the opportunity to combine packets from different sources using randomized network coding. We formulate the problem as the minimization of the average decoding delay in the client population and solve it with a gradient-based stochastic algorithm. Our optimized inter-session network coding solution is evaluated in different network topologies and is compared with basic intra-session network coding solutions. Our results show the benefits of proper coding decisions and effective rate allocation for lowering the decoding delay when the network is used by concurrent multicast sessions. [ABSTRACT FROM AUTHOR]

It is well known that communication systems are susceptible to strong impulsive noises. To combat this, convolutional coding has long served as a cost-efficient tool against moderately frequent memoryless impulses with given statistics. Nevertheless, impulsive noise statistics are difficult to model accurately and are typically not time-invariant, making the system design challenging. In this paper, because of the lack of knowledge regarding the probability density function of impulsive noises, an efficient decoding scheme was devised for single-carrier narrowband communication systems; a design parameter was incorporated into recently introduced joint erasure marking and Viterbi decoding algorithm, dubbed the metric erasure Viterbi algorithm (MEVA). The proposed scheme involves incorporating a well-designed clipping operation into a Viterbi algorithm, in which the clipping threshold must be appropriately set. In contrast to previous publications that have resorted to extensive simulations, in the proposed scheme, the bit error probability performance associated with the clipping threshold was characterized by deriving its Chernoff bound. The results indicated that when the clipping threshold was judiciously selected, the MEVA can be on par with its optimal maximum-likelihood decoding counterpart under fairly general circumstances. [ABSTRACT FROM AUTHOR]

In this paper, we propose a resource allocation scheme to increase the effective capacity subject to the queue-overflow statistical Quality-of-Service (QoS) requirement for a multi-relay cooperative wireless network. Firstly, we consider the block fading channels and derive an algorithm in which each relay is allocated a time slot of optimal length during the cooperation phase, based on the channel statistics. Our analysis indicates that when the QoS requirement is loose, only the relay with the best average channel condition should be selected for cooperation. On the other hand, when the QoS requirement becomes more stringent, more relays should participate in cooperation. The asymptotic case when either the transmit power or the number of relays goes to infinity is discussed, and we shall reveal a tradeoff between the transmit power and the number of relays, given a target effective capacity. By modeling the channel correlation by a two-state Markov model, we will develop two sub-optimal time-slot allocation algorithms which can substantially increase the effective capacity compared with the opportunistic and equal allocation schemes. Our results will show that the channel correlation can sharply decrease the effective capacity and that applying the optimal time-slot allocation result obtained in block fading channels directly to correlated fading channels is no longer optimal. [ABSTRACT FROM AUTHOR]

This paper develops a Nash game towards optimizing optical signal-to-noise ratio (OSNR) in the presence of link capacity constraint. In optical wavelength-division multiplexing (WDM) networks, all wavelength-multiplexed channels in a link share the optical fiber. In order to limit nonlinear effects, the total power launched into a fiber has to be below a nonlinearity threshold. This can be regarded as the optical link capacity constraint. We formulate an extended OSNR Nash game that incorporates this underlying system constraint. The status of an optical link is considered directly in the cost function. Sufficient conditions for existence and uniqueness of the Nash equilibrium (NE) solution are given. Two iterative algorithms for channel power control are proposed to compute the NE solution: a parallel update algorithm (PUA) and a relaxed PUA (r-PUA). Their convergence is studied under different conditions, both theoretically and numerically. [ABSTRACT FROM AUTHOR]

The jamming robustness of frequency hopping (FH) systems with M-ary frequency shift keying (MFSK) modulation may be potentially neutralized by a follower partial-band jammer. In this paper, a maximum likelihood (ML)-based algorithm that uses a two-element array is proposed for joint follower jamming rejection and symbol detection in slow FHJMFSK systems over quasi-static flat Rayleigh fading channels. The algorithm is derived by treating both the received jamming components and the unknown data symbols as deterministic quantities to be jointly estimated in an integrated ML operation. In addition, an approximate expression for the symbol error rate (SER) of the proposed scheme is derived when BFSK signaling is employed in a jamming dominant scenario. Analytical and simulated results show that the proposed approach is able to remove jamming and outperform the conventional and sample matrix inversion (SMI)-based beam-formers in the presence of a follower partial-band jammer. [ABSTRACT FROM AUTHOR]

In this paper, adaptive sectoring of a CDMA cellular network is investigated, and the aim is to maximize the uplink capacity by utilizing mobiles' spatial information. One important feature of the algorithm developed is that it does not depend on tracking individual mobile, but rather on the statistics of mobiles. The distribution of mobiles is modeled as a spatial Poisson process, whose rate function quantizes mobile concentration and is inferred with a Bayesian estimator based on the statistics of network traffic. In addition, the time dynamics of the rate function is assumed to evolve according to mobiles' mobility pattern and it is formulated using the Influence model. With the knowledge of mobiles' spatial distribution, the interference and thus the outage probability of different sector partitions of a cell can be computed. The adaptive sectoring problem is formulated as a shortest path problem, where each path corresponds to a particular sector partition, and the partition is weighted by its outage probability. In simulation examples, a hot spot scenario is simulated with the adaptive sectoring mechanism, and it is observed that load balancing between sectors is achieved and which greatly reduces the effect of hot spot. [ABSTRACT FROM AUTHOR]

In this paper, we present an algorithm for joint carrier phase estimation and turbo decoding for the case of rapidly varying carrier phase during the transmitted block. The proposed algorithm shows improved performance over previously proposed communication schemes, both coherent and noncoherent, for channels with additive white Gaussian noise and high carrier phase noise. The novel algorithm utilizes a modified ‘two dimensional’ bit carrier phase a posteriori probability (BCAPP) decoder containing additional states representing the received carrier phase. The BCAPP decoder calculates two extrinsic metrics: one representing the bit soft value and the other representing the received carrier phase probability density function approximation. A modified structure of the turbo code iterations is suggested, implementing separate propagation of the two metrics between the BCAPP decoders. One additional attractive property of the suggested algorithm is its robustness against phase noise model mismatch. [ABSTRACT FROM AUTHOR]

For conventional cyclic prefix (CP)-assisted single-carrier/frequency-domain equalization (SC/FDE) implementations, as well as for orthogonal frequency-division multiplexing (OFDM) implementations, the CP length is known to be selected on the basis of the expected maximum delay spread. Next, the data block size can be chosen to be large enough to minimize the CP overhead, yet small enough to make the channel variation over the block negligible. This paper considers the possibility of reducing the overall CP assistance, when transmitting sequences of SC blocks, while avoiding an excessively long fast Fourier transform window for FDE purposes and keeping good FDE performances through low-complexity, noniterative receiver techniques. These techniques, which take advantage of specially designed frame structures, rely on a basic algorithm for decision-directed correction (DDC) of the FDE inputs when the CP is not long enough to cope with the time-dispersive channel effects. More specifically, we present and evaluate a novel class of reduced-CP SCIFDE schemes, which takes advantage of a special frame structure for replacing ‘useless’ CP redundancy by fully useful channel coding redundancy, with the help of the DDC algorithm. When using the DDC-FDE technique with these especially designed frame structures, the impact of previous decisions, which are not error-free, is shown to be rather small, thereby allowing a power-efficiency advantage (in addition to the obvious bandwidth-efficiency advantage) over conventional block transmission implementations under full-length CP. Additionally, the DDC algorithm is also shown to be useful to improve the power efficiency of these conventional implementations. [ABSTRACT FROM AUTHOR]

In many problems in wireline networks, it is known that achieving capacity on each link or subnetwork is optimal for the entire network operation. In this paper, we present examples of wireless networks in which decoding and achieving capacity on certain links or subnetworks gives us lower rates than other simple schemes, like forwarding. This implies that the separation of channel and network coding that holds for many classes of wireline networks does not, in general, hold for wireless networks. Next, we consider Gaussian and erasure wireless networks where nodes are permitted only two possible operations: nodes can either decode what they receive (and then re-encode and transmit the message) or simply forward it. We present a simple greedy algorithm that returns the optimal scheme from the exponential-sized set of possible schemes. This algorithm will go over each node at most once to determine its operation, and hence, is very efficient. We also present a decentralized algorithm whose performance can approach the optimum arbitrarily closely in an iterative fashion. [ABSTRACT FROM AUTHOR]

This paper presents a reduced-complexity soft-input soft-output detection scheme, called iterative tree search detection for multiple-input multiple-output wireless communication systems employing turbo processing at the receiver. In this scheme, a reduced search space is selected with the aid of the M-algorithm, and QAM signal constellations with block partitionable labels are independent of the modulation order, as well as asymptotically linear in the number of transmit antennas. Results from computer simulations are presented which demonstrate the capability of the scheme to approach optimal performance at considerable reduced complexity. [ABSTRACT FROM AUTHOR]

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. In this paper, 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 non-adaptive systems. It is also demonstrated that the MIMO system is able to multiplex several users without sacrificing antenna diversity by using the proposed algorithm. [ABSTRACT FROM AUTHOR]

Recent theoretical results describing the sum capacity when using multiple antennas to communicate with multiple users in a known rich scattering environment have not yet been followed with practical transmission schemes that achieve, this capacity. We introduce a simple encoding algorithm that achieves near-capacity at sum rates of tens of bits/channel use. The algorithm is a variation on channel inversion that regularizes the inverse and uses a "sphere encoder" to perturb the data to reduce the power of the transmitted signal. This paper is comprised of two parts. In this first part, we show that while the sum capacity grows linearly with the minimum of the number of antennas and users, the sum rate of channel inversion does not. This poor performance is due to the large spread in the singular values of the channel matrix. We introduce regularization to improve the condition of the inverse and maximize the signal-to-interference-plus-noise ratio at the receivers. Regularization enables linear growth and works especially well at low signal-to-noise ratios (SNRs), but as we show in the second part, an additional step is needed to achieve near-capacity performance at all SNRs. [ABSTRACT FROM AUTHOR]

The puncturing technique allows obtaining high-rate convolutional codes from low-rate convolutional codes used as mother codes. This technique has been successfully applied to generate good high-rate convolutional codes which are suitable for Viterbi and sequential decoding. In this paper, we investigate the puncturing technique for convolutional self-doubly orthogonal codes (CSO²C) which are decoded using an iterative threshold-decoding algorithm. Based on an analysis of iterative threshold decoding of the rate-R = b/(b + 1) punctured systematic CSO²C, the required properties of the rate-R = 1/2 systematic convolutional codes (SCCs) used as mother codes are derived. From this analysis, it is shown that there is no need for the punctured mother codes to respect all the required conditions, in order to maintain the double orthogonality at the second iteration step of the iterative threshold-decoding algorithm. The results of the search for the appropriate rate-R = 1/2 SCCs used. as mother codes to yield a large number of punctured codes of rates 2/3 ⩽ R ⩽ 6/7 are presented, and some of their error performances evaluated. [ABSTRACT FROM AUTHOR]

Recently, a class of real-number Bose-Chaud- huri-Hocquengem codes known as discrete Fourier transform (DFT) codes have been considered as joint source and channel codes for providing robustness to erasures and errors over wireless networks. In this paper, we propose three subspace algorithms for error localization with quantized DFT codes. The algorithms are similar to the MUSIC, the minimum-norm, and the ESPRIT algorithms used in array signal processing for direction-of-arrival estimation. They provide different but related formulations of the error localizations by first partitioning a vector space into the channel error subspace and its orthogonal complement, the noise subspace. The locations of the errors are determined from either the error subspace eigenvectors or the noise subspace eigenvectors. We also present a brief performance analysis of the localization error in terms of the perturbation of the error subspace due to quantization. Simulation results show that their localization performances are similar, and they perform better than the coding-theoretic approach over a broad range of channel-error-to-quantization-noise ratios. [ABSTRACT FROM AUTHOR]

In a general wireless system, cells are loosely defined and user signals appear at multiple antennas with various powers and delays. Despite the enormous performance benefits of system-wide maximum-likelihood multiuser detection (ML MUD), its application to such systems is hampered by the lack of a regular structure. Prior work usually dismisses the possibility on computational grounds as exponential in the total number of users, at least. This paper is the first to address efficient computation of system-wide ML MUD. We present a computational organization that achieves dramatic reduction in complexity through exploitation of the partial overlap of user sets at different antennas. This algorithm, which applies to code-division multiple access or narrowband systems, can be viewed as a spatiotemporal extension of the well-known Viterbi algorithm (VA), and, like the VA, it is derived from dynamic programming principles. [ABSTRACT FROM AUTHOR]

In orthogonal frequency-division multiple access (OFDMA), closely spaced multiple subcarriers are assigned to different users for parallel signal transmission. An interleaved subcarrier-assignment scheme is preferred because it provides maximum frequency diversity and increases the capacity in frequency-selective fading channels. The subcarriers are overlapping, but orthogonal to each other such that there is no intercarrier interference (ICI). Carrier-frequency offsets (CFOs) between the transmitter and the receiver destroy the orthogonality and introduces ICI, resulting in multiple-access interference. This paper exploits the inner structure of the signals for CFO estimation in the uplink of interleaved OFDMA systems. A new uplink signal model is presented, and an estimation algorithm based on the signal structure is proposed for estimating the CFOs of all users using only one OFDMA block. Diversity schemes are also presented to improve the estimation performance. Simulation results illustrate the high accuracy and efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

It is well known that multiuser detection can obtain significant performance advantages over the conventional matched filter receiver in code division multiple access systems. Further, since optimal multiuser detection is exponentially complex, the majority of research has focused on suboptimal approaches such as successive interference cancellation (SIC). SIC has been shown to require a geometric distribution of received powers to achieve equal performance for all received signals. In this paper we propose a power control scheme for SIC to achieve this profile (or the profile corresponding to any desired and achievable set of error rates) based on frame-error rate (FER) or bit-error rate (BER). Specifically, we derive the relationship between received power and BER for linear SIC and show that for unlimited mobile powers, a deterministic distributed BER-based outer-loop power control will drive the received powers to the optimal power profile. The convergence of the deterministic BER-based algorithm is examined in the absence of inner loop power control errors. The simulated performance of a stochastic version of this algorithm is examined using instantaneous FER measurements. The stochastic algorithm is shown to provide unbiased estimates of the true power updates and converge to the optimal power vector provided the mobiles have unlimited power. Further, we consider power limits for specific mobiles and find that individual mobile limits do not affect the performance of other signals. Further, we examine the impact of system loading, multiple FER targets, error correction, and inner loop power control error on the performance of the algorithm. [ABSTRACT FROM AUTHOR]