Spread spectrum

About: Spread spectrum is a research topic. Over the lifetime, 16287 publications have been published within this topic receiving 282543 citations. The topic is also known as: spread-spectrum & spread-spectrum telecommunications.

Introduction to Spread Spectrum Communications

Abstract: From the Publisher: Besides the traditional military application areas, there is a growing and intense interest in spread spectrum communications systems for evolving civil applications, e.g., cellular-mobile communications, personal communications, and satellite-mobile communications. Ideal for those who need to get up to speed or current quickly in this area, this self-contained exploration of spread spectrum system analysis and applications provides a solid theoretical background along with an abundance of examples of specific analysis/design situations, and exposes readers to the most recent research and developments in the field. Covers basic digital communication and spread spectrum concepts, and features exceptionally complete treatments of important hot topics such as spectrum spreading sequences; the code acquisition and tracking process; the effects of jamming on spread spectrum communications and the use of coding/interleaving to combat the detrimental effects of jamming; designing spread spectrum systems for low probability of the intercept; and the design of code division multiple access systems, wit h examples. Contains a complete set of technical appendices. For electrical engineers and others with a background in linear systems and probability/random processes who want a cutting-edge overview of the principles, research, and developments of spread spectrum systems.

Code Combining--A Maximum-Likelihood Decoding Approach for Combining an Arbitrary Number of Noisy Packets

Abstract: It is well known that if the data rate is chosen below the available channel capacity, error-free communication is possible. Furthermore, numerous practical error-correction coding techniques exist which can be chosen to meet the user's reliability constraints. However, a basic problem in designing a reliable digital communication system is still the choice of the actual code rate. While the popular rate-1/2 code rate is a reasonable, but not optimum, choice for additive Gaussian noise channels, its selection is far from optimum for channels where a high percentage of the transmitted bits are destroyed by interference. Code combining represents a technique of matching the code rate to the prevailing channel conditions. Information is transmitted in packet formats which are encoded with a relatively high-rate code, e.g., rate 1/2, which can be repeated to Obtain reliable communications when the redundancy in a rate-1/2 code is not sufficient to overcome the channel interference. The receiver combines noisy packets (code combining) to obtain a packet with a code rate which is low enough such that reliable communication is possible even for channels with extremely high error rates. By combining the minimum number of packets needed to overcome the channel conditions, the receiver optimizes the code rate and minimizes the delay required to decode a given packet. Thus, the receiver adapts to the actual jammer-to-signal (J/S) ratio which is critical when the level of interference J is not known a priori.

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

Abstract: 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.

Multiple access with time-hopping impulse modulation

Abstract: A time-hopping modulation format employing impulse signal technology has several features which may make it attractive for multiple-access communications. These features are outlined, an estimate of the multiple-access capability of a communication system employing this format under ideal propagation conditions is presented, and emerging design issues are described. >

Linear multiuser receivers: effective interference, effective bandwidth and user capacity

Abstract: Multiuser receivers improve the performance of spread-spectrum and antenna-array systems by exploiting the structure of the multiaccess interference when demodulating the signal of a user. Much of the previous work on the performance analysis of multiuser receivers has focused on their ability to reject worst case interference. Their performance in a power-controlled network and the resulting user capacity are less well-understood. We show that in a large system with each user using random spreading sequences, the limiting interference effects under several linear multiuser receivers can be decoupled, such that each interferer can be ascribed a level of effective interference that it provides to the user to be demodulated. Applying these results to the uplink of a single power-controlled cell, we derive an effective bandwidth characterization of the user capacity: the signal-to-interference requirements of all the users can be met if and only if the sum of the effective bandwidths of the users is less than the total number of degrees of freedom in the system. The effective bandwidth of a user depends only on its own SIR requirement, and simple expressions are derived for three linear receivers: the conventional matched filter, the decorrelator, and the MMSE receiver. The effective bandwidths under the three receivers serve as a basis for performance comparison.