A non-cooperative game-theoretic approach to channel assignment in multi-channel multi-radio wireless networks

Channel assignment in multi-channel multi-radio wireless networks poses a significant challenge due to scarcity of number of channels available in the wireless spectrum. Further, additional care has to be taken to consider the interference characteristics of the nodes in the network especially when nodes are in different collision domains. This work views the problem of channel assignment in multi-channel multi-radio networks with multiple collision domains as a non-cooperative game where the objective of the players is to maximize their individual utility by minimizing its interference. Necessary and sufficient conditions are derived for the channel assignment to be a Nash Equilibrium (NE) and efficiency of the NE is analyzed by deriving the lower bound of the price of anarchy of this game. A new fairness measure in multiple collision domain context is proposed and necessary and sufficient conditions for NE outcomes to be fair are derived. The equilibrium conditions are then applied to solve the channel assignment problem by proposing three algorithms, based on perfect/imperfect information, which rely on explicit communication between the players for arriving at an NE. A no-regret learning algorithm known as Freund and Schapire Informed algorithm, which has an additional advantage of low overhead in terms of information exchange, is proposed and its convergence to the stabilizing outcomes is studied. New performance metrics are proposed and extensive simulations are done using Matlab to obtain a thorough understanding of the performance of these algorithms on various topologies with respect to these metrics. It was observed that the algorithms proposed were able to achieve good convergence to NE resulting in efficient channel assignment strategies.

Multi-channel signal separation

The separation of independent sources from mixed observed data is a fundamental and challenging problem. In many practical situations, observations may be modelled as linear mixtures of a number of source signals, i.e. a linear multi-input multi-output system. A typical example is speech recordings made in an acoustic environment in the presence of background noise and/or competing speakers. Other examples include EEG signals, passive sonar applications and cross-talk in data communications. In this paper, we propose iterative algorithms to solve the n × n linear time invariant system under two different constraints. Some existing solutions for 2 × 2 systems are reviewed and compared.

Multi-channel 2-D pattern transfer model based on imaging optics for submarine laser uplink communication

An optical communication scheme of 2-D pattern transfer based on imaging optics for submarine laser uplink communication (SLUC) is suggested. Unlike the methods aiming at avoiding neighboring crosstalk used in traditional multi-channel optical beam transferring, we make full use of the overlapping of each spreading beam other than controlling divergence effect of each beam to avoid interference noise. The apparent parameters have been introduced to simplify theoretical analysis of optical pattern transfer problem involving underwater condition, with the help of which the complex beam propagation inside two kinds of mediums can be easily reduced to brief beam transfer only inside air medium. In this paper, optical transmission path and receiver terminal optics geometry have been described in detail. The link range equation and system uplink performance analysis have also been given. At last, results of a proof-of-concept experiment indicate good feasibility of the proposed SLUC model. © 2007 Elsevier GmbH. All rights reserved.

Developing ISO 14649-based conversational programming system for multi-channel complex machine tools

A multi-channel complex machine tool (MCCM) is a versatile machining system equipped with more than two spindles and turrets for both turning and milling operations. Despite the potential of such a tool, the value of the hardware is largely dependent on how the machine tools are effectively programmed for machining. In this paper we consider a shop-floor programming system based on ISO 14649 (called e-CAM), the international standard for the interface between computer-aided manufacture (CAM) and computer numerical control (CNC). To be deployed in practical industrial usage a great deal of research has to be carried out. In this paper we present: 1) Design consideration for an e-CAM system, 2) The architecture design of e-CAM, 3) Major algorithms to fulfill the modules defined in the architecture, and 4) Implementation details.

Multi-channel micro neural probe fabricated with SOI

Silicon-on-insulator (SOI) substrate is widely used in micro-electro-mechanical systems (MEMS). With the buried oxide layer of SOI acting as an etching stop, silicon based micro neural probe can be fabricated with improved uniformity and manufacturability. A seven-record-site neural probe was formed by inductive-coupled plasma (ICP) dry etching of an SOI substrate. The thickness of the probe is 15 mu m. The shaft of the probe has dimensions of 3 mmx100 mu mx15 mu m with typical area of the record site of 78.5 mu m(2). The impedance of the record site was measured in-vitro. The typical impedance characteristics of the record sites are around 2 M Omega at 1 kHz. The performance of the neural probe in-vivo was tested on anesthetic rat. The recorded neural spike was typically around 140 mu V. Spike from individual site could exceed 700 mu V. The average signal noise ratio was 7 or more.

Multi channel micro neural probe fabricated with SOI

Extracellular neural recording requires neural probes having more recording sites as well as limited volumes. With its mechanical characteristic and abundant process method, Silicon is a kind of material fit for producing neural probe. Silicon on insulator (SOI) is adopted in this paper to fabricate neural probes. The uniformity and manufacturability are improved. The fabricating process and testing results of a series of Multi channel micro neural probes were reported. The thickness of the probe is 15 mu m-30 mu m. The typical impedance characteristics of the record sites are around 2M Omega at 1k Hz. The performance of the neural probe in-vivo was tested on anesthetic rat. The recorded neural spike was typically around 140 mu V. Spike recorded from individual site could exceed 700 mu V. The average signal noise ratio was 7 or more.