There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

Underwater sensor nodes will find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications. Moreover, unmanned or autonomous underwater vehicles (UUVs, AUVs), equipped with sensors, will enable the exploration of natural undersea resources and gathering of scientific data in collaborative monitoring missions. Underwater acoustic networking is the enabling technology for these applications. Underwater networks consist of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area. In this paper, several fundamental key aspects of underwater acoustic communications are investigated. Different architectures for two-dimensional and three-dimensional underwater sensor networks are discussed, and the characteristics of the underwater channel are detailed. The main challenges for the development of efficient networking solutions posed by the underwater environment are detailed and a cross-layer approach to the integration of all communication functionalities is suggested. Furthermore, open research issues are discussed and possible solution approaches are outlined. � 2005 Published by Elsevier B.V.

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Underwater acoustic sensor networks: research challenges

Information Theory and Reliable Communication

In this paper we review the most peculiar and interesting information-theoretic and communications features of fading channels. We first describe the statistical models of fading channels which are frequently used in the analysis and design of communication systems. Next, we focus on the information theory of fading channels, by emphasizing capacity as the most important performance measure. Both single-user and multiuser transmission are examined. Further, we describe how the structure of fading channels impacts code design, and finally overview equalization of fading multipath channels.

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Fading channels: information-theoretic and communications aspects

Spread spectrum methods are used in communication systems to provide low probability of intercept in hostile environments, to provide multiple access capability in systems shared by many users, and to provide processing gain in channels where the transmitted signal is distorted by multipath propagation. All three of these scenarios are of interest to underwater acoustic communication systems. In this paper we consider spread spectrum modulation and demodulation methods for low rate transmission in underwater acoustic communication channels. Two types of spread spectrum systems are considered: direct-sequence spread spectrum (DS-SS) systems that employ digital phase modulation with coding, and frequency-hopping spread spectrum (FHSS) systems that employ coded MFSK modulation and noncoherent demodulation. These methods are investigated for application in fading multipath channels typical of underwater propagation. System design examples are given and performance estimates are made.

Spread spectrum underwater acoustic telemetry

Preface. 1. High-Speed Unterwater Acoustic Communications M. Stojanovic. 2. Synthetic Aperture Mapping and Imaging M.E. Zakharia, J. Chatillon. 3. Integrated Programmable Underwater Acoustic Biotelemetry System R.S.H. Istepanian. 4. Digital Underwater Voice Communications H. Sari, B. Woodward. 5. Applications of Neural Networks in Underwater Acoustic Signal Processing Z. Zhaoning, P.R. Nanjing. 6. Statistical Signal Processing of Echo Ensembles J. Penrose, T. Pauly. 7. Advanced Coding for Underwater Communications H. Junying, G. Haihong. Reference.

Underwater Acoustic Digital Signal Processing and Communication Systems

https://www.mit.edu/~millitsa/resources/pdfs/milica-phycomm-june08.pdf

Full length article: Efficient processing of acoustic signals for high-rate information transmission over sparse underwater channels

The design of a cellular underwater network is addressed from the viewpoint of determining the cell size and the frequency reuse pattern needed to support a desired number of users operating over a given area within a given system bandwidth. By taking into account the basic laws of underwater acoustic propagation, it is shown that unlike in the terrestrial radio systems, both the cell radius R and the reuse number N must satisfy a set of constraints to constitute an admissible solution (which sometimes may not exist). The region of admissible (R,N) , which defines the possible network topologies, is determined by the user density and the system bandwidth (rho,B) , and by the required signal-to-interference ratio and per-user bandwidth (SIR0,W 0) . The system capacity is defined as the maximal user density rhomax that can be supported within a given bandwidth, and it is derived analytically. Numerical examples are used to illustrate the results. It is shown that capacity-achieving architectures are characterized by N, which grows with rhomax. The capacity, as well as the range of admissible solutions, is heavily influenced by the choice of frequency region to which the bandwidth is allocated. Moving to a higher frequency region than that dictated by signal-to-noise ratio (SNR) maximization improves the SIR and yields a greater capacity. Although higher frequencies demand greater transmission power to span the same distance, they also imply a reduction in the cell size, which, in turn, provides an overall reduction in the transmission power. While complex relationships are involved in system optimization, the analysis presented offers a simple tool for the design of future ocean observation systems based on cellular types of network architecture for wide area coverage.

/pdf/design-and-capacity-analysis-of-cellular-type-underwater-4hxlkpe3d9.pdf

Design and Capacity Analysis of Cellular-Type Underwater Acoustic Networks

The current interest in underwater sensor networks stems from the potential to use long term sensing devices to monitor the large mass of oceans on the planet (e.g., underwater seismic event monitoring or underwater oil rig monitoring). To accomplish this, the sensor nodes must have the ability to self-configure the communication network and provide energy-efficient data transmission. To this end, researchers have begun devising MAC-layer protocols that minimize energy consumption for data transmission. Acoustic modems typically present a number of modes of operation, similar to radio interfaces (e.g., transmit, receive, sleep, etc.), each of which consumes different levels of energy. In radio communications, the cost of keeping the interfaces idle is high; therefore, a number of idle-time power management solutions have been devised (e.g., GAF [1], STEM [2], TITAN [3]) to conserve energy during times of no communication. It is natural to attempt to use these same methods for energy conservation in underwater sensor networks. However, there are significant differences between acoustic modems and radios transceivers, making it doubtful whether previous conclusions will be valid for the underwater environment. The relative costs of various interface modes are significantly different for acoustic devices than for radios. Typical radio interfaces [4] have similar costs for transmitting, receiving and idling. On the other hand, acoustic modems have very high transmission costs with respect to receive costs, and have very low idle costs.

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Milica Stojanovic

Papers

Spread spectrum underwater acoustic telemetry

Underwater Acoustic Digital Signal Processing and Communication Systems

Full length article: Efficient processing of acoustic signals for high-rate information transmission over sparse underwater channels

Design and Capacity Analysis of Cellular-Type Underwater Acoustic Networks

When underwater acoustic nodes should sleep with one eye open: idle-time power management in underwater sensor networks