In this paper, we propose the method to standardize acoustic frequencies for underwater wireless acoustic sensor networks (UWASNs) by applying the channel raster used in the terrestrial mobile communications. The standardization process includes: (1) Setting the available acoustic frequency band where a channel raster is employed via the frequency specification analysis of the state-of-the art underwater acoustic communication modems. (2) Defining the center frequencies and the channel numbers as a function of channel raster, and the upper limit of the value of channel raster. (3) Determining the value of the channel raster suitable for the available acoustic frequency band via simulations. To set the value, three performance metrics are considered: the collision rate, the idle spectrum rate, and the receiver computational complexity. The simulation results show that the collision rate and the idle spectrum rate according to the value of channel raster have a trade-off relationship, but the influence of channel raster on the two performance metrics is insignificant. However, the receiver computational complexity is enhanced remarkably as the value of channel raster increases. Therefore, setting the value of channel raster close to its upper limit is the most adequate in respect of mitigating the occurrence of a collision and enhancing the reception performance. The standardized frequencies based on channel raster can guarantee the frequency compatibility required for the emerging technologies like the Internet of Underwater Things (IoUT) or the underwater cognitive radio, but also improves the network performance by avoiding the arbitrary use of frequencies.
In this paper we consider the communication problem that involves transmission of correlated sources over broadcast channels. We consider a graph-based framework for this information transmission problem. The system involves a source coding module and a channel coding module. In the source coding module, the sources are efficiently mapped into a nearly semi-regular bipartite graph, and in the channel coding module, the edges of this graph are reliably transmitted over a broadcast channel. We consider nearly semi-regular bipartite graphs as discrete interface between source coding and channel coding in this multiterminal setting. We provide an information-theoretic characterization of (1) the rate of exponential growth (as a function of the number of channel uses) of the size of the bipartite graphs whose edges can be reliably transmitted over a broadcast channel and (2) the rate of exponential growth (as a function of the number of source samples) of the size of the bipartite graphs which can reliably represent a pair of correlated sources to be transmitted over a broadcast channel.
IntroductionWith the emergence of new set of applications such as wireless sensor networks, the problem of transmission of correlated information sources over multiterminal channels has received a renewed attention. In this problem, many correlated information sources are accessed by a set of transmitter terminals, and they wish to simultaneously transmit some subset of them to another set of receiver terminals over a channel. In this paper we address the one-to-many communication system, where one transmitter terminal has access to all the information sources, and wish to transmit them to many receiver terminals. One such model involving two receiver terminals was considered by Han and Costa in [1], and is described in the following. Consider a pair of correlated discrete memoryless sources (S, T ) with some generic joint distribution p(s, t) and a pair of finite alphabets S and T , respectively. The encoder observes long sequences of realizations of these sources (of length say n), and wishes to transmit them over a broadcast channel which has one input X and two outputs Y 1 and Y 2 , and Receiver i has access to Y i . The channel behavior is governed by a generic conditional distribution p(y 1 , y 2 |x). The channel is assumed to be discrete memoryless and is used without feedback. The encoder maps n-length source sequence pairs into n-length channel input sequences. Each receiver maps its corresponding n-length channel output sequences into its corresponding n-length source reconstruction sequences. The receivers would like to produce a reconstruction sequence pair such *
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