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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]

It is challenging to design effective scheduling algorithms for multimedia transmissions over wireless channels that employ adaptive modulation and coding (AMC). On the one hand, it is desirable for the overall system throughput to be enhanced by taking advantage of multi-user diversity. On the other hand, fairness or QoS guarantees need to be maintained for individual users, especially in the case of multimedia applications that have strict delay requirements. In this paper, we propose a novel scheduling algorithm called QoS-based cross-layer scheduling (QoS-CLS) to achieve a good design tradeoff. To maximize the system throughput, the algorithm takes into account the information on both the physical layer and the data link layer to schedule user transmissions. Using cross-layer information, the scheduling problem is formulated as a Markov Decision Process and the optimal decision policy (based on the channel status, traffic state, and buffer status of each traffic flow) is pre-calculated by linear programming. This policy is then stored in the system for scheduling in real-time. Simulation results show that QoS-CLS can greatly enhance the channel throughput compared to existing algorithms because of its cross-layer QoS consideration and the optimization method. Moreover, it can provide QoS guarantees while achieving efficient resource sharing among different traffic flows. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel pragmatic approach, referred to as detection b multiple trellises, to perform trellis-based detection over realistic channels. More precisely, we consider channels with unknown parameters and apply the concept of detection by multiple trellises to forward-backward (FB) algorithms. The key idea of our approach consists, first, of property quantizing the channel parameters and, then, considering replication of coherent FB algorithms operating on parallel trellises, one per hypothetical quantized value. In order to make the receiver robust against a possibly time-varying channel parameters, the proposed soft-output algorithms perform a proper "manipulation" of the forward sod backward metrics computed by the parallel FB algorithms at regularly spaced trellis steps. We consider two significant examples of application: detection over (i) phase-uncertain channels and (ii) fading channels. The performance of the proposed algorithm is investigated considering differentially encoded (DE) quaternary phase shift keying (QPSK) and iterative detection schemes based on tow-density parity-check (LDPC) codes. Besides having a too complexity, the proposed soft-output algorithms turn out to be robust, flexible, blind, in the sense that no knowledge of the channel parameter statistics is required, and highly parallelizable, as it is desirable in high-throughput future wireless communication systems. [ABSTRACT FROM AUTHOR]

Can conventional differential unitary space time modulation (DUSTM) be applied when there is an unknown carrier frequency offset (CFO)? This paper answers this question affirmatively and derives the necessary maximum likelihood (ML) detection rule. The asymptotic performance of the proposed ML rule is analyzed, leading to a code design criterion for DUSTM by using the modified diversity product. The resulting proposed decision rule is a new differential modulation scheme in both the temporal and spatial domains. Two sub-optimal multiple-symbol decision rules with improved performance are also proposed. For the efficient implementation of these, we derive a modified bound intersection detector (BID), a generalization of the previously derived optimal BID for the conventional DUSTM. The simulation results show that the proposed differential modulation scheme is more robust against CFO drifting than the existing double temporal differential modulation. [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, we analyze the sequential message-passing decoding algorithm of low-density parity-check (LDPC) codes by partitioning check nodes. This decoding algorithm shows better bit error rate (BER) performance than the conventional message-passing decoding algorithm, especially for the small number of iterations. Analytical results indicate that as the number of partitioned subsets of check nodes increases, the BER performance is improved. We also derive the recursive equations for mean values of messages at check and variable nodes by using density evolution with a Gaussian approximation. From these equations, the mean values are obtained at each iteration of the sequential decoding algorithm and the corresponding BER values are calculated. They show that the sequential decoding algorithm converges faster than the conventional one. Finally, the analytical results are confirmed by the simulation results. [ABSTRACT FROM AUTHOR]

Iterative turbo processing between detection and decoding shows near-capacity performance on a multiple-antenna system. Combining iterative processing with optimum front- end detection is particularly challenging because the front-end maximum a posteriori (MAP) algorithm has a computational complexity that is exponential. Sub-optimum detector such as the soft interference cancellation linear minimum mean square error (SIC-LMMSE) detector with near front-end MAP performance has been proposed in the literature. The asymptotic computational complexity of SIC-LMMSE is O(n²tnr + ntn²r + ntMc2Mc) per detection-decoding cycle where nt is number of transmit antenna, nr is number of receive antenna, and Mc is modulation size. A lower complexity detector is the hard interference cancellation LMMSE (HIC-LMMSE) detector. HIC-LMMSE has asymptotic complexity of O(n²tnr + ntMc2Mc) but suffers extra performance degradation. In this paper, two front-end detection algorithms are introduced that not only achieve asymptotic computational complexity of O(n²tnr + ntn²r [Γ (β) + 1] + ntMc2Mc) where Γ (β) is a function with discrete output {-1, 2,3, …, nt} and O(ntMc2Mc) respectively. Simulation results demonstrate that the proposed low complexity detection algorithms offer exactly same performance as their full complexity counterpart in an iterative receiver while being computational more efficient. [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]

Efficient soft-decision decoding of Reed-Solomon (RS) codes is made possible by the Koetter-Vardy (KV) algorithm which consists of a front-end to the interpolation-based Guruswami-Sudan (GS) list decoding algorithm. This paper approaches the soft-decision KV algorithm from the point of view of a communications systems designer who wants to know what benefits the algorithm can give, and how the extra complexity introduced by soft decoding can be managed at the systems level. We show how to reduce the computational complexity and memory requirements of the soft-decision front-end. Applications to wireless communications over Rayleigh fading channels and magnetic recording channels are proposed. For a high-rate RS(255,239) code, 2-3 dB of soft-decision gain is possible over a Rayleigh fading channel using 16-quadrature amplitude modulation. For shorter codes and at lower rates, the gain can be as large as 9 dB. To lower the complexity of decoding on the systems level, the redecoding architecture is explored, which uses only the appropriate amount of complexity to decode each packet. An error-detection criterion based on the properties of the KV decoder is proposed for the redecoding architecture. Queueing analysis verifies the practicality of the redecoding architecture by showing that only a modestly sized RAM buffer is required. [ABSTRACT FROM AUTHOR]

Previous work introduced the idea of matching network codes with network graphs to handle the network dynamics. This paper further integrates channel coding in the adaptive network coding framework through an elegant treatment of circulant shifting. Several code constructions are developed. Theoretical analysis and simulations show that the resultant generalized adaptive network coded cooperation (GANCC) is simple, adaptive, distributive, and capable of remarkable coding gains even with a very small number of cooperating users. [ABSTRACT FROM AUTHOR]

Cooperative communications have received considerable attention for wireless multimedia applications as a technique to improve reliability and service coverage. To apply such cooperation over slow fading channels, we consider exploiting the spatial diversity in multiple relay networks. In this paper, we focus on amplify-and-forward relaying schemes, namely, orthogonal amplify-and-forward, selective relaying, and distributed beamforming, for the cooperative wireless multimedia transmission. Furthermore, the successive refinement source coding is exploited such that the multimedia signal is encoded into multiple layers and the quality of its reconstruction at the receiver is improved when more layers are received correctly. We study two strategies for the layered source transmission, namely, progressive transmission and superposition coding. With our developed framework, we propose suboptimal resource allocation algorithms to efficiently assign rate, power, and channel uses to different layers so as to maximize the quality of the multimedia signal reconstructed at the receiver. The proposed optimization methodology is simple and only requires the knowledge of the channel statistics compared to the existing algorithms. As a result, the receiver only requires to feedback the determined rate, power, and channel uses to the transmitter whenever the channel statistics or the layered source transmission strategy changes. [ABSTRACT FROM PUBLISHER]