Wireless Communications

A stylized compressed sensing radar is proposed in which the time-frequency plane is discretized into an N times N grid. Assuming the number of targets K is small (i.e., K Lt N2), then we can transmit a sufficiently ldquoincoherentrdquo pulse and employ the techniques of compressed sensing to reconstruct the target scene. A theoretical upper bound on the sparsity K is presented. Numerical simulations verify that even better performance can be achieved in practice. This novel-compressed sensing approach offers great potential for better resolution over classical radar.

High-Resolution Radar via Compressed Sensing

High-rate data communication over a multipath wireless channel often requires that the channel response be known at the receiver. Training-based methods, which probe the channel in time, frequency, and space with known signals and reconstruct the channel response from the output signals, are most commonly used to accomplish this task. Traditional training-based channel estimation methods, typically comprising linear reconstruction techniques, are known to be optimal for rich multipath channels. However, physical arguments and growing experimental evidence suggest that many wireless channels encountered in practice tend to exhibit a sparse multipath structure that gets pronounced as the signal space dimension gets large (e.g., due to large bandwidth or large number of antennas). In this paper, we formalize the notion of multipath sparsity and present a new approach to estimating sparse (or effectively sparse) multipath channels that is based on some of the recent advances in the theory of compressed sensing. In particular, it is shown in the paper that the proposed approach, which is termed as compressed channel sensing (CCS), can potentially achieve a target reconstruction error using far less energy and, in many instances, latency and bandwidth than that dictated by the traditional least-squares-based training methods.

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Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels

This paper presents an overview of ultrawideband (UWB) propagation channels. It first demonstrates how the frequency selectivity of propagation processes causes fundamental differences between UWB channels and "conventional" (narrowband) channels. The concept of pathloss has to be modified, and the well-known WSSUS model is not applicable anymore. The paper also describes deterministic and stochastic models for UWB channels, identifies the key parameters for the description of delay dispersion, attenuation, and directional characterization, and surveys the typical parameter values that have been measured. Measurement techniques and methods for extracting model parameters are also different in UWB channels; for example, the concepts of narrowband channel parameter estimation (e.g., maximum-likelihood estimation) have to be modified. Finally, channel models also have an important impact on the performance evaluation of various UWB systems.

Ultrawideband propagation channels-theory, measurement, and modeling

A comprehensive statistical model is described for ultrawideband (UWB) propagation channels that is valid for a frequency range from 3-10 GHz. It is based on measurements and simulations in the following environments: residential indoor, office indoor, builtup outdoor, industrial indoor, farm environments, and body area networks. The model is independent of the used antennas. It includes the frequency dependence of the path gain as well as several generalizations of the Saleh-Valenzuela model, like mixed Poisson times of arrival and delay-dependent cluster decay constants. A separate model is specified for the frequency range below 1 GHz. The model can thus be used for realistic performance assessment of UWB systems. It was accepted by the IEEE 802.15.4a Task Group as standard model for evaluation of UWB system proposals. This paper also presents a critical assessment of the applicability of the model and possible generalizations and improvements

/pdf/a-comprehensive-standardized-model-for-ultrawideband-5f122zska0.pdf

A Comprehensive Standardized Model for Ultrawideband Propagation Channels

The results of indoor multipath propagation measurements using 10 ns, 1.5 GHz, radarlike pulses are presented for a medium-size office building. The observed channel was very slowly time varying, with the delay spread extending over a range up to about 200 ns and rms values of up to about 50 ns. The attenuation varied over a 60 dB dynamic range. A simple statistical multipath model of the indoor radio channel is also presented, which fits our measurements well, and more importantly, appears to be extendable to other buildings. With this model, the received signal rays arrive in clusters. The rays have independent uniform phases, and independent Rayleigh amplitudes with variances that decay exponentially with cluster and ray delays. The clusters, and the rays within the cluster, form Poisson arrival processes with different, but fixed, rates. The clusters are formed by the building superstructure, while the individual rays are formed by objects in the vicinities of the transmitter and the receiver.

A Statistical Model for Indoor Multipath Propagation

The Fourier transform data communication system is a realization of frequency-division multiplexing (FDM) in which discrete Fourier transforms are computed as part of the modulation and demodulation processes. In addition to eliminating the banks of subcarrier oscillators and coherent demodulators usually required in FDM systems, a completely digital implementation can be built around a special-purpose computer performing the fast Fourier transform. In this paper, the system is described and the effects of linear channel distortion are investigated. Signal design criteria and equalization algorithms are derived and explained. A differential phase modulation scheme is presented that obviates any equalization.

Data Transmission by FrequencyDivision Multiplexing Using the Discrete Fourier Transform

On the SelfSimilar Nature of Ethernet Traffic (Extended Version)

This paper presents a new family of convolutional codes, nicknamed turbo-codes, built from a particular concatenation of two recursive systematic codes, linked together by nonuniform interleaving. Decoding calls on iterative processing in which each component decoder takes advantage of the work of the other at the previous step, with the aid of the original concept of extrinsic information. For sufficiently large interleaving sizes, the correcting performance of turbo-codes, investigated by simulation, appears to be close to the theoretical limit predicted by Shannon.

Near Optimum Error Correcting Coding and Decoding: TurboCodes

The problem of allocating network resources to the users of an integrated services network is investigated in the context of rate-based flow control. The network is assumed to be a virtual circuit, connection-based packet network. We show that the use of Generalized Processor Sharing (GPS), when combined with Leaky Bucket admission control, allows the network to make a wide range of worst-case performance guarantees on throughput and delay. The scheme is flexible in that different users may be given widely different performance guarantees, and is efficient in that each of the servers is work conserving. We present a practical packet-by-packet service discipline, PGPS (first proposed by Deniers, Shenker, and Keshav [7] under the name of Weighted Fair Queueing), that closely approximates GPS. This allows us to relate results for GPS to the packet-by-packet scheme in a precise manner. In this paper, the performance of a single-server GPS system is analyzed exactly from the standpoint of worst-case packet delay and burstiness when the sources are constrained by leaky buckets. The worst-case session backlogs are also determined. In the sequel to this paper, these results are extended to arbitrary topology networks with multiple nodes.

/pdf/a-generalized-processor-sharing-approach-to-flow-control-in-3jec8inwfn.pdf

Jon W. Mark

Papers

A Statistical Model for Indoor Multipath Propagation

Data Transmission by FrequencyDivision Multiplexing Using the Discrete Fourier Transform

On the SelfSimilar Nature of Ethernet Traffic (Extended Version)

Near Optimum Error Correcting Coding and Decoding: TurboCodes

A Generalized Processor Sharing Approach to Flow Control in Integrated Services Networks: The SingleNode Case