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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]

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]

Blind channel-estimation algorithms return phase-ambiguous estimates. From a receiver design point of view, the phase-ambiguity problem can be by-passed by differential modulation and detection at the expense of a well-known performance loss, in comparison with direct modulation and coherent detection schemes. An alternative approach is followed in this paper. A theoretical minimum mean-square error phase-estimation criterion leads to a supervised phase-recovery procedure that directly corrects the phase of arbitrary linear filter receivers through a simple closed-form projection operation. Conveniently, any known blind channel-estimation algorithm can be used to provide the initial phase-ambiguous estimate. The presentation is given in the context of adaptive space-time receiver designs for binary phase-shift keying direct-sequence code-division-multiple-access antenna array systems. Numerical and simulation studies support the theoretical developments and show that effective phase correction and multiple-access interference suppression can be achieved with about 2% pilot signaling. [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]

In this paper, novel equalization algorithms for continuous phase modulations (CPMs) are illustrated. Both conventional (linear and decision-feedback) and turbo equalization techniques are derived using the Laurent decomposition of CPM signals. All of them operate in the frequency domain and process two samples of the received signal per channel symbol. Numerical results show that on one hand, conventional equalization strategies offer good performance for binary partial response signaling over severely frequency-selective wireless channels at a moderate complexity. On the other hand, there is evidence that turbo techniques provide a small energy saving at the price of a substantial computational burden. [ABSTRACT FROM AUTHOR]

In this paper, we present a new analytical model that captures link dependencies in all-optical wavelength-division multiplexing (WDM) networks under uniform traffic and enables the estimation of connection-blocking probabilities more accurately than previously possible. The basic formula of the dependency between two links in this model reflects their degree of adjacency, the degree of connectivity of the nodes composing them, and their carried traffic. Our validation tests have shown that the analytical dependency model gives accurate results and successfully captures the main dependency characteristics observed in the simulation measurements. The usefulness of the model is illustrated by showing how to use it in enhancing a simulation-based algorithm that we recently proposed for the sparse placement of full wavelength converters in WDM networks. To analytically handle the presence of wavelength converters, a lightpath containing converters is divided into smaller subpaths, such that each subpath is a wavelength-continuous path, and the nodes shared between these subpaths are full wavelength-conversion-capable. The blocking probability of the entire path is obtained by computing the probabilities in the individual subpaths. We validate the analytically-based sparse placement algorithm by comparing it with its simulation-based counterpart using a number of network topologies. [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]

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]