Abstract—Motivated by the emergence of programmable radios, we seek to understand a new class of communication system where pairs of transmitters and receivers can adapt their modulation/demodulation method in the presence of interference to achieve better performance. Using signal to interference ratio as a metric and a general signal space approach, we present a class of iterative distributed algorithms for synchronous systems which results in an ensemble of optimal waveforms for multiple users connected to a common receiver (or colocated independent receivers). That is, the waveform ensemble meets the Welch Bound with equality and, therefore, achieves minimum average interference over the ensemble of signature waveforms. We derive fixed points for a number of scenarios, provide examples, look briefly at ensemble stability under user addition and deletion as well as provide a simplistic comparison to synchronous code-division multiple-access. We close with suggestions for future work. Index Terms—Adaptive modulation, code-division multiple-access systems, codeword optimization, interference avoidance, multiuser

Motivated by the emergence of programmable radios, we seek to understand a new class of communication system where pairs of transmitters and receivers can adapt their modulation/demodulation method in the presence of interference to achieve better performance. Using signal to interference ratio as a metric and a general signal space approach, we present a class of iterative distributed algorithms for synchronous systems which results in an ensemble of optimal waveforms for multiple users connected to a common receiver (or co-located independent receivers). That is, the waveform ensemble meets the Welch Bound with equality and therefore achieves minimum average interference over the ensemble of signature waveforms. We describe fixed points for a number of scenarios. 1 Introduction Wireless system designers have always had to contend with interference from both natural sources and other users of the medium. Thus, the classical wireless communications design cycle has consisted of measu...

The study of interference avoidance for wireless communications is motivated by recent developments in telecommunications industry which demands new solutions for personal communications. Radios are becoming more sophisticated, and one can presently think of adjusting transmission/reception methods to suit the environment in which the communication system is operating. As a main application of interference avoidance techniques we see communication in unlicensed bands, where independent systems that interfere with each other will have to coexist without central control or coordination. Our purpose is to provide insight into a class of distributed iterative algorithms that produce optimal codeword ensembles which maximize sum capacity in a multiuser system and minimize interference. Also known as interference avoidance algorithms they have been introduced in the context of chip-based CDMA systems but have been subsequently framed in a general signal space formulation so as to make them applicable to a wide variety of communication scenarios. After an introduction to basic interference avoidance (IA) concepts and a review of previous work on IA, we describe how IA can be applied to codeword optimization in the uplink of a CDMA system in which the channel between each user and the basestation is assumed to be known. Each user

We investigate practical methods of distributed interference avoidance where users iteratively adapt their codewords in response to global feedback from the receiver. In turn, the receiver adaptively tracks user codewords and offers a reasonable alternative to feeding back codewords. We introduce variants of standard interference avoidance procedures which produce more easily tracked incremental codewords and study the response of the system to abrupt changes in the interference background as might be encountered in a practical system. Furthermore, the methods we propose are strongly reminiscent of adaptive equalization for which a large body of knowledge and hardware expertise exist.

The assertion that biological systems are communication networks would draw no rebuke from biologists – the terms signaling, communication, and network are deeply embedded parts of the biology parlance. However, the more profound meanings of information and communication are often overlooked when considering biological systems. Information can be quantified, its flow can be measured and tight bounds exist for its representation and conveyance between transmitters and receivers in a variety of settings. Furthermore, communications theory is about efficient communication where energy is at a premium – as is often the case in organisms. But perhaps most important, information theory allows mechanism-blind bounds on decisions and information flow. That is, the physics of a system allows determination of limits that any method of information description, delivery or processing must obey. Thus, rigorous application of communication theory to complex multi-cellular biological systems seems both attractive and obvious as an organizing principle – a way to tease order from the myriad engineering solutions that comprise biological systems. Likewise, study of biological systems – engineering solutions evolved over eons – might yield new communication and computation theory. Yet so far, a communications-theoretic approach to multi-cellular biology has