Raptor Code for Energy-Efficient Wireless Body Area Network Data Transmission

Abstract

IntroductionWireless Body Area Network (WBAN) is a cluster of wireless sensors worn by humans mainly for the purpose of medical condition monitoring. The human physiological data such as blood pressure or body temperature are monitored by the sensors and sent to a data processor regardless of the location or the activity of the subject [1]. WBAN is a structure which contains a short-range communication system based on IEEE 802.15.6. The standard allows for lowpower and small-sized devices and includes characterization of electromagnetic wave propagation transmitted by a device located on or in the human body.Aside from being able to send information using a small-sized antenna and limited power, a WBAN device must also be able to send information reliably over a long term. Reliability and durability can be achieved through appropriate modulation and coding schemes. The modulation scheme choice will affect the transmitter and receiver power required by WBAN device, which will subsequently affect the device lifetime. However to achieve high reliability, the coding scheme will play the more important part compared to that of the modulation scheme. An ideal coding scheme for WBAN is one that ensures reliable transmission of information in a rapidly changing wireless channel.Raptor codes, an extension of Luby-Transform (LT) codes with linear time encoding and decoding have been shown to attain good upper-bound on overall error probability when used in binary erasure channel [2]. Several channel model for WBAN has been proposed based on numerical simulations and/or measurements. A mathematical model using dyadic Green function to model the human body as a simplified cylinder has been proposed and used to show the receive signal variations around the human body [3]. Another research proposes the use of pathloss channel model based on measurement [4]- [5]. The pathloss channel is stated as a function of distance and frequency, and the fluctuating power is shown to match lognormal distribution. As the wearer of a WBAN device moves around, the wireless channel is subject to fading. Objects around the human body will also reflect and scatter the signal, contributing to a multipath fading of a Rice distribution [6]. A more general fading model form WBAN is Rayleighdistributed. Another possibility that can be taken into consideration is the Nakagami-m distributed fading channel, as this is the model which provides indoor-mobile multipath propagation in addition to ionospheric radio link [6]. Various researches have shown that Raptor codes provide a robust data transmission even in noisy channels. The performance of an optimized Raptor code in quasi-static Rayleigh fading channel has been analyzed and shown to

Towards Efficient Wireless Body Area Network Using Two-Way Relay Cooperation

“…The raptor code showed greater efficiency over uncoded FSK and LDPC coded link [ 14 ]. The comparison result of raptor code and bose-chaudhuri-hocquenghem (BCH) code in a fading environment showed that the BCH coded data achieves higher energy efficiency for a link length of 10 m or less [ 15 ].…”

Signal Processing in Telecommunications with Forward Correction of Errors

“…The research results of noise immunity signals of frequency shift keying indicate that the best features has the coherent reception of FSK signals . Thus, at the BER level of 10-5 the energy gain of MSK (coherent acceptance) before DQPSK is 1.5 dB, and before non -coherent reception -4 dB [9], [11][12][13].…”

“…Each of the hypotheses, which is remained for the next measure is complemented by zero and one, and two new hypotheses are being formed. The reference signals 1 Xr U and 2 Xr U are generated for each hypothesis to implement the formula (12). As the initial value, the last k-th bit estimate isn't used and the bit offset to the depth of the given scenario, i.e. )…”

Data analysis for image transmitted using Discrete Wavelet Transform and Vector Quantization compression

“…In recent years lot of research has been done to enhance the quality of received image after transmission in noisy channel, this problem can be solved using different techniques (source coding, channel coding , joint source channel coding or by optimize in restoration filters) as shown in articles [1][2][3].…”