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We analyze the asymptotic behavior of compute-and-forward relay networks in the regime of high signal-to-noise ratios. We consider a section of such a network consisting of K transmitters and K relays. The aim of the relays is to reliably decode an invertible function of the messages sent by the transmitters. An upper bound on the capacity of this system can be obtained by allowing full cooperation among the transmitters and among the relays, transforming the network into a K\times K multiple-input multiple-output (MIMO) channel. The number of degrees of freedom of compute-and-forward is hence at most K. In this paper, we analyze the degrees of freedom achieved by the lattice coding implementation of compute-and-forward proposed recently by Nazer and Gastpar. We show that this lattice implementation achieves at most 2/(1+1/K)\leq 2 degrees of freedom, thus exhibiting a very different asymptotic behavior than the MIMO upper bound. This raises the question if this gap of the lattice implementation to the MIMO upper bound is inherent to compute-and-forward in general. We answer this question in the negative by proposing a novel compute-and-forward implementation achieving K degrees of freedom. [ABSTRACT FROM PUBLISHER]

We analyze the reverse link of a single wireless cell in which mobile phones simultaneously transmit to the base station using code division multiple access (CDMA). The mobiles are transmitting data which is delay intolerant, so that scheduling cannot be employed. There is a finite number of data classes, and the users transmit either data or a lower rate synchronizing signal. To overcome the near-far problem, received power control is used, which has a log-normal error. For each class there is an outage probability that the user's signal-to-noise ratio (SNR) will be met (when active and when idle). Refinements of the central limit theorem are used to determine the number of users of each class that can be supported, i.e., the capacity. The approximation can also be used to determine the minimal target powers necessary to meet the outage requirements. Comparison with simulation shows these approximations to be accurate. [ABSTRACT FROM AUTHOR]

Presents a study which proposed dynamic channel-sensitive scheduling algorithms for wireless data throughput optimization. Model description; Development of adaptive online algorithms for determining the optimal-revenue vector in an iterative fashion; Results and conclusion.

Presents information on a study which introduced a reward paradigm to derive novel bounds for the performance of dynamic channel assignment schemes. Approaches to increase efficiency in the use of wireless services; Illustration on how the revenue-based bounds may be used to improve upon the Erlang bound approach; Numerical results for scenarios with uniform and varying reuse; Investigation on the tradeoff between efficiency and fairness that arises in the case of varying use.

Consider several source nodes communicating across a wireless network to a destination node with the help of several layers of relay nodes. Recent work by Avestimehr has approximated the capacity of this network up to an additive gap. The communication scheme achieving this capacity approximation is based on compress-and-forward, resulting in noise accumulation as the messages traverse the network. As a consequence, the approximation gap increases linearly with the network depth. This paper develops a computation alignment strategy that can approach the capacity of a class of layered, time-varying wireless relay networks up to an approximation gap that is independent of the network depth. This strategy is based on the compute-and-forward framework, which enables relays to decode deterministic functions of the transmitted messages. Alone, compute-and-forward is insufficient to approach the capacity as it incurs a penalty for approximating the wireless channel with complex-valued coefficients by a channel with integer coefficients. Here, this penalty is circumvented by carefully matching channel realizations across time slots to create integer-valued effective channels that are well suited to compute-and-forward. Unlike prior constant gap results, the approximation gap obtained in this paper also depends closely on the fading statistics, which are assumed to be i.i.d. Rayleigh. [ABSTRACT FROM PUBLISHER]

Traditional approaches in the analysis of downlink systems decouple the precoding and the channel estimation problems. However, in cellular systems with mobile users, these two problems are, in fact, tightly coupled. In this paper, this coupling is explicitly studied by accounting for the channel training overhead and estimation error while determining the overall system throughput. This paper studies the problem of utilizing imperfect channel estimates for efficient linear precoding and user selection. It presents precoding methods that take into account the degree of channel estimation error. Information-theoretic lower and upper bounds are derived to evaluate the performance of these precoding methods. In typical scenarios, these bounds are close. [ABSTRACT FROM PUBLISHER]

We examine threshold-based transmission strategies for distributed opportunistic medium access in a scenario with fairly general probabilistic interference conditions. Specifically, collisions between concurrent transmissions are governed by arbitrary probabilities, allowing for a form of channel capture and covering binary interference constraints as an important special case. We address the problem of setting the threshold values so as to optimize the aggregate throughput utility of the various users, and particularly focus on a weighted logarithmic throughput utility function (Proportional Fairness). We provide an adaptive algorithm for finding the optimal threshold values in a distributed fashion, and rigorously establish the convergence of the proposed algorithm under mild statistical assumptions. Moreover, we discuss how the algorithm may be adapted to achieve packet-level stability with only limited exchange of queue length information among the various users. We also conduct extensive numerical experiments to corroborate the theoretical convergence results. [ABSTRACT FROM AUTHOR]

Downstream (DS) crosstalk channels of digital subscriber line systems can be estimated based on the reported signal-to-noise ratio (SNR). In the case of an already active victim line (VL) impacted by the joining of a new disturber line (DL), sending perturbing signals on the VL and reporting the SNRs allow the estimation of the crosstalk channel from the DL to the VL. This paper generalizes that concept to include full startup, tracking and joining scenarios as well as the impact of different perturbation signal choices. Additionally, the sensitivity of the algorithm to different sources of imperfection is analyzed. Simulation results reveal that starting without precoding, and updating the precoder matrix based on the DS crosstalk channel estimates, the far-end crosstalk-free SNR can be reached in a limited number of iterations (e.g., 36 SNR measurements are needed for the four lines case). The SNR-assisted method is documented in an informative appendix of the draft G.vector recommendation as a backward compatible method for very high speed digital subscriber lines (VDSL2) and, hence, can be used for channel acquisition today. [ABSTRACT FROM AUTHOR]

Results for optical switch dimensioning are obtained by analysing an urn occupancy problem in which a random number of balls is used. This analysis is applied to a high speed bufferless optical switch which uses tuneable wavelength converters to resolve contention between packets at the output fibres. Under symmetric packet routing the urn problem reduces to the classical occupancy problem. Since the problem is large scale and the loss probabilities are small, exact analysis by combinatorial methods is problematic. As an alternative, we outline a large deviations approximation which may be generalised in various ways. Copyright © 2002 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]