Smart Frames Deciphering Algorithm For Hydro Computer Science Essay

Published Date: 02 Nov 2017

Mr. Sumedh S Gawande 1, Miss Nidhi Malviya 2

[email protected] 1, [email protected]

Trinity Institute of Technology & Research, Bhopal, Madhya Pradesh

Abstract- The electromagnetic wave propagation is very poor in water. Therefore it cannot be used for under water applications. Hence the ultimate solution is acoustic communication. In the acoustic communication we are using the acoustic waves for communication. The hydro acoustic modulator will be used at physical layer. But to increase the security we are proposing the smart deciphering algorithm at the receiver end to avoid the unwanted listeners. By using this smart deciphering the only the required node will be able to decipher the frames and unwanted listeners will be avoided. The proposed algorithm will be designed using MATLAB.

Keywords- Booth multiplier, Low power, modified booth multiplier, VHDL, partial product generation (PPG).

INTRODUCTION

As electromagnetic waves propagate poorly in sea water, acoustics provides the most obvious medium to enable underwater communications. High-speed communication in the underwater acoustic channel is challenging due to extended multi-path, refractive properties of the medium, severe fading, rapid time-variation and large Doppler shifts. Communication techniques originally developed for terrestrial wired and wireless channels need significant modifications to suit underwater channels.

The development of digital communications for undersea applications dates back to simple ping-based use of sonar that operates in the audible band. The use of "one ping only" in the fictional Hunt for Red October that was used to communicate from submarine to submarine is an example of digital communications, which while primitive, certainly is sufficient when only one bit is necessary.

High-speed communication in the underwater acoustic channel has been challenging due to a number of reasons. Extended multi-path, rapid time-variation and severe fading are also common in many underwater channels. The relatively slow signal propagation speed in water implies large Doppler shifts at moderate speeds of communicating platforms.

The multipath and time-varying are the two key characters of underwater acoustic channel, and the major obstacle of high-speed and reliable transmission of underwater acoustic channel is narrow band and serious signal fading. In order to transmit data high-speedily and more reliably in such harsh and complex underwater acoustic channel, a good error correction code requires be adopted to improve the reliability of transmission. And Turbo code is one of the best error correction channel code in the world nowadays, therefore, it is applied as channel coding of coherent communication on "JiaoLong" manned submersible.

At the MAC layer Long-baseline (LBL) acoustic positioning systems, widely covered in various scientific publications, are based on specific protocols and were designed to solve one particular task, namely the positioning of remote targets. The proposed algorithm is solutions which extend the application range of such systems by combining them with underwater acoustic communication systems. Both systems can share the same electro-acoustic circuit for transmitting and receiving signals and the same signal processing module. The same acoustic signal can be used for both transmission of digital information and estimation of its source position.

Hence, the algorithm is proposed that will decipher the data frames efficiently or at minimum error rate at receiving node end. Therefore in this manner the network reliability will be enhanced.

LITERATURE REVIEW

The wireless communications field started with the discovery of the long range propagation characteristics of radio waves. Based on sonar development, underwater acoustic communications was then developed [1].Acoustic signal is the only physical feasible tool that works in underwater environment. Compared with it, electromagnetic wave can only travel in water with short distance due to the high attenuation and absorption effect in underwater environment. It is found that the absorption of electromagnetic energy in sea water is about 45× f dB per kilometer, where f is frequency in Hertz; In contrast, the absorption of acoustic signal over most frequencies of interest is about three orders of magnitude lower [2]. As electromagnetic waves propagate poorly in sea water, acoustics provides the most obvious medium to enable underwater communications. High-speed communication in the underwater acoustic channel is challenging due to limited bandwidth, extended multi-path, refractive properties of the medium, severe fading, rapid time-variation and large Doppler shifts. The capability to communicate efficiently underwater has important applications including oceanographic studies, offshore oil prospection and extraction, and defense operations. As electromagnetic waves cannot propagate over long distances underwater, acoustic communication assumes an important role for such applications [3].

Multicarrier modulation in the form of orthogonal frequency division multiplexing (OFDM) has been shown feasible for underwater acoustic communications via effective algorithms to handle the channel time-variability. New method to construct non-binary regular and irregular LDPC codes that achieve excellent performance, match well with the underlying modulation, and can be encoded in linear time and in a parallel fashion. Based on the fact that the generator matrix of LDPC codes has high density, we further show how to reduce the PAPR considerably with minimal overhead [4].

The propagation medium of underwater acoustic channel exhibits distinct characteristics when contrasted with other common propagation media such as copper, fiber, and radio. In particular there is the extremely slow propagation speed of sound in water, high signal attenuation due to absorption, significant delay spreads and inter symbol interference, and range-dependent transmission bandwidth. These features make the delay reliability tradeoff for underwater acoustic channels fundamentally different from other channels [5]. Long baseline (LBL) acoustic positioning systems are widely covered in scientific publications and are available as commercial solutions. The task of acoustic positioning basically comes down to precise measurement of the signals arrival time and its propagation velocity. Acoustic positioning is thus affected by in homogeneity of the propagating signal’s environment, variability of environmental parameters, multipath propagation of the signal, movements of positioning targets and the antenna’s baseline nodes along with other challenges, common for acoustic communication [6].

For divergence of the adaptive DFE leading to loss of data frames and affecting the performance of Turbo decoding in harsh UAC (Underwater Acoustic Communication) channel, inter-frame interleaved Bi-SOVA decoding algorithm was proposed. Inter-frame interleaved Bi-SOVA algorithm encodes and decodes the whole data packet (28 frames) to correct the lost frames, since it can distribute error bits randomly [7].

METHODOLOGY

The underwater network using acoustic communication is versatile for the military & research applications. Hence, these networks like other networks must be secured & efficient enough to locate the destination & retrieve the data packets without error. This method can improve & solve the problem of accessing the wireless network in hydro acoustic communication. The acoustic communication best suited to the underwater implication for network. But the issues are same for this communication system to like the other networks using electromagnetic communication. The retrieval of the data packets in network is one of big issue to avoid data loss. The solution required for efficient communication & retrieval of packets without loss should be accomplished. This requirement is fulfilled by advanced MAC layer algorithm for locating & deciphering data packets for implication in the underwater acoustic networks.

The proposed algorithm will decipher the data packets in the network at destination node. The proposed MAC layer algorithm combines the merits of LBL (LONG BASELINE) positioning with Bi-SOVA algorithm to locate & retrieve the data packets. Long baseline (LBL) acoustic positioning systems are widely covered in scientific publications and are available as commercial solutions.

In this paper we are explaining the dual encryption transmission of spread spectrum. And then decrypt that encrypted data without any prior knowledge of encrypting PN sequence. First data sequence is directly encrypted by PN sequence in direct sequence spread spectrum (DSSS). Then this encrypted data is modulated & its modulation is again encrypted by PN sequence in frequency hopping spread spectrum (FHSS). As data is encrypted two times the data is more secure from the unwanted user. To describe in details the operations of spread spectrum detection & PN sequence retrieval, the simplified block diagram of a transmitter & receiver for spread spectrum multiple access system is illustrated in Fig. 1 & Fig. 2.

Fig.1. Transmitter block diagram

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Fig.2. Receiver block diagram

Here, in this block diagram of transmitter first we the data sequence b(n) is directly multiplied with the PN sequence c(t) in product modulator or modulator. The output of the modulator is wide spectrum signal m(N). The spectrum of this signal is quite high compared to that of narrow band data signal b(n).

Then, this signal m(N) is applied to the M-ary FSK modulator. The modulator output is particular frequency depending upon the input symbol. The output of the modulator is applied to mixer. The other input of the mixer is the particular frequency from frequency synthesizer. The output of the frequency synthesizer at particular instant is frequency slot or ‘hop’. The output of the mixer is DS/FH/M-ary FSK signal & is transmitted over the wideband channel.

The frequency hops given to mixer are generated by the frequency synthesizer. The input of the frequency synthesizer is controlled by the pseudo-noise (PN) sequence generator. The‘t’ successive bits of PN sequence generator control the frequency hops generated by synthesizer. Since the bits of the PN sequence generator change randomly, the frequency hops generated also change randomly. Since ‘t’ bits PN sequence controls frequency hops, there will be distinct ‘2 t’ frequency hops generated. The total bandwidth of the output signal is very high.

The received DS/FH/ MFSK signal is applied to hopping pattern recognition (HPR) block. This block consists of the functional stages initial frequency detection (IFD), remaining frequency detection (RFD), compute hopping pattern (CHP). The goal of the detection device is to detect the HP (hopping pattern) without any prior knowledge about the HP used by the sender at the receiver. The HP of wireless network will be known using this block without any prior knowledge, about the HP used by the sender at the receiver.

Hopping pattern (HP) may consist of two to m random frequencies. Each frequency may exist only once. Assume H.P is F with frequencies F0, F1, F2,….., Fx. To detect that a frequency being transmitted clear channel assessment is required. It requires 50 µs to indicate busy. To recognize Hopping Pattern formula is expressed as:

Here dx is the dwell time of frequency Fx. Only one frequency will be detected by detection device at a time. This detection occurs by calling the CCA procedure. To detect the specific frequency transmitted currently by clear channel assessment transmission should be of complete test period. When on transmission stops on the detected frequency before test period then, the correct frequency may not be available. This failure when the frequency hop is less than 50 µs can overcome in stage six. The output of the third stage is then given to the decision device, then to the fourth stage M-ary FSK detector. The detector detects the particular symbol transmitted. In the FH/M-ary FSK the individual frequency of smallest duration is called ‘chip’. Now, at the output of the M-ary FSK detector we get the ‘N’ bit symbol in parallel. From these ‘N’ bits ’t’ bit LSB’s are then transferred to the PN sequence register r(t). These are the PN sequence for that ‘N’ bit symbol. Then the ‘N’ bit symbol is converted to the serial bit stream by parallel to serial converter. Then this ‘N’ serial bits are applied to the mixer with the‘t’ bit LSB’s. The output of the mixer is the data signal b(n). This‘t’ bit LSB’s are then used to generate the frequency hops by frequency synthesizer. This is fed to the mixer with the input signal & compared with the output of HPR algorithm in decision block. The output of the both HPR algorithm & the mixer should be same. If the frequency hop is lesser than the 50 µs than HPR algorithm fails. Then the output of the mixer is passed to the M-ary FSK detector.

CONCLUSION

This method can improve & solve the problem of accessing the wireless network in hydro acoustic communication. As the error rate decreases the network will be more reliable. The data frames will be retrieved with very less error & secured way. The destination nodes will be accessed reliably. The proposed algorithm will allow implementing custom media access schemes that require precise synchronization of network nodes. The hydro acoustic network will be more reliable.