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Orthogonal frequency division multiplexing (OFDM) system suffers extra performance degradation in fast fading channels due to intercarrier interference (Id). Combining frequency domain equalization and bit-interleaved coded modulation (BICM), the iterative receiver is able to harvest both temporal and frequency diversity. Realizing that ICI channels are intrinsically IS! channels, this paper proposes a soft-in soft-out (SISO) maximum a posteriori (MAP) equalizer by extending Ungerboeck's maximum likelihood sequence estimator (MLSE) formulation to ICI channels. The SISO MAP equalizer employs BCJR algorithm and computes the bit log-likelihood ratios (LLR) for the entire received sequence by efficiently constructing a trellis that takes into account of the ICI channel structure. A reduced state (RS) formulation of the SISO MAP equalizer which provides good performance/complexity tradeoff is also described. Utilizing the fact that ICI energy is clustered in adjacent subcarriers, frequency domain equalization is made localized. This paper further proposes two computational efficient linear minimum mean square error (LMMSE) based equalization methods: recursive q-tap SIC-LMMSE equalizer and recursive Sliding-Window (SW) SIC-LMMSE equalizer respectively. Simulations results demonstrate that the iterative SISO RS-MAP equalizer achieves the performance of no ICI with normalized Doppler frequency fdTs up to 20.46% in realistic mobile WiMAX environment. [ABSTRACT FROM AUTHOR]

In this paper, we consider the downlink of a multiuser wireless communication system with multiple antennas at the base station and users each with a single receive antenna. It is known that when channel state information (CSI) is available at the transmitter a large performance gain can be achieved. In a system employing time-division duplexing (TDD), CSI can be obtained at the base station if there is reciprocity between the forward and reverse channels. CSI can also be conveyed from the users to the base station via a limited-rate feedback channel in a frequency-division duplexing (FDD) system. !n any case, channel estimation errors are inevitable due to the presence of background noise in the estimated signal and due to the finite number of feedback bits used in a limited-rate feedback system model. In this paper, we first consider the general case when partial CSI is available at the transmitter. We derive an MMSE based precoding technique that considers channel estimation errors as an integral part of the system design. Using rate-distortion theory and the generalized Lloyd vector quantization algorithm, we then specialize our results for the more practical limited-rate feedback system model. Compared to previously proposed precoding techniques such as channel inversion and regularized channel inversion, it is shown that the proposed precoding technique significantly improves the average bit error rate (BER) in the system. Furthermore, the performance of the proposed technique is investigated in the high signal-to-noise ratio (SNR) regime, and similar to [1], [21, it is shown that the proposed technique suffers from a ceiling effect that asymptotically limits the system performance. [ABSTRACT FROM AUTHOR]

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]

In this paper, we design jointly optimum transmitter and receiver beamforming structures in correlated MIMO Rayleigh fading channels with noisy channel estimates, and evaluate their performance through a closed-form expression for the probability of error. At the receiver, an estimate of the channel is obtained based on the transmitted pilot symbols. The knowledge of the estimate is then made available to the transmitter through a feedback channel. It is assumed that spatial correlation exists, either at the transmitter or at the receiver. A new exact closed-form expression for the probability of error is derived and the joint effects of diversity order and channel estimation accuracy on system performance are analyzed. [ABSTRACT FROM AUTHOR]

In this paper, a new information theoretic algorithm is proposed for signal enumeration in DS-CDMA networks. The approach is based on the predictive description length (PDL) of the observation vector. The PDL is the length of a predictive code of observations. For signal detection, the PDL criterion is computed for the candidate models and is minimized to determine the number of signals. The proposed technique uses the maximum likelihood (ML) estimate of the correlation matrix. The only information used in the ML estimation of the correlation matrix is the multiplicity of the smallest eigenvalue. The PDL algorithm has a signal-to-noise ratio resolution threshold that is smaller than that of the minimum description length (MDL). The proposed method can be used on-line and can be applied to time-varying and non-stationary systems. [ABSTRACT FROM AUTHOR]

In this paper, we develop optimization techniques for linear zero-forcing (ZF) multiple-input, multiple-output (MIMO) broadcast (BC) precoders. A computationally efficient technique based on QR-update algorithms for implementing this optimization is then proposed. The application of the proposed ZF precoders and decoders to systems with both large and small numbers of users is considered. The proposed optimization technique is also shown to perform very well in conjunction with nonlinear Tomlinson- Harashima precoding. Both coded and uncoded performances are considered. [ABSTRACT FROM AUTHOR]

The paper deals with design and performance analysis of orthogonal frequency-division multiple-access (OFDMA)- based downlink cellular wireless communications. Due to a high degree of user mobility, the base station is assumed to have only a statistical knowledge of the users' channels. Relying on the ergodic capacities connected to the user rates, a subcarrier and power allocation that minimizes the total transmitted power is proposed. The allocation strategy requires only the knowledge of the channel statistics and the rate requirements for all users. An extension and a performance analysis of this allocation algorithm in a multicell environment working with a frequency reuse factor equal to one is also conducted. A condition for the multicell network to be able to satisfy all rate requirements is derived. [ABSTRACT FROM AUTHOR]

This paper analyzes the multiuser capacity of Gaussian frequency-selective wireline multiaccess channels. Both the uplink (multiple-access channel) and downlink (broadcast channel) capacity regions are considered. The concept of balanced capacity is introduced to characterize the multiuser channel performance. Algorithms for the computation of the balanced multiuser capacity (and the associated power allocations) are proposed for an arbitrary number of users. The optimal power allocation in a K-user memoryless Gaussian channel is analyzed in detail, and an extension to intersymbol interference channels is given with various kinds of power constraints. Results are provided for a wireline access network with 20 users. [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]

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]

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]