An adaptive FEC code control algorithm for mobile wireless sensor networks

Abstract

For better performance over a noisy channel, mobile wireless networks transmit packets with forward error correction (FEC) code to recover corrupt bits without retransmission. The static determination of the FEC code size, however, degrades their performance since the evaluation of the underlying channel state is hardly accurate and even widely varied. Our measurements over a wireless sensor network, for example, show that the average bit error rate (BER) per second or per minute continuously changes from 0 up to 10 −3 . Under this environment, wireless networks waste their bandwidth since they can't deterministically select the appropriate size of FEC code matching to the fluctuating channel BER.This paper proposes an adaptive FEC technique called adaptive FEC code control (AFECCC), which dynamically tunes the amount of FEC code per packet based on the arrival of acknowledgement packets without any specific information such as signal to noise ratio (SNR) or BER from receivers. Our simulation experiments indicate that AFECCC performs better than any static FEC algorithm and some conventional dynamic hybrid FEC/ARQ algorithms when wireless channels are modeled with two-state Markov chain, chaotic map, and traces collected from real sensor networks. Finally, AFECCC implemented in sensor motes achieves better performance than any static FEC algorithm.Index Terms: Adaptive forward error correction (FEC) algorithm, wireless mobile sensor networks.

Error resilient data transport in sensor network applications: A generic perspective

“…Channel conditions: Firstly, the channels in WSNs are highly unreliable with high probability of introducing burst of errors at certain instants [4,8]. The behavior of the channel depends not only on the specific communication scheme employed in the applications [8] but also on deployment conditions [9,10].…”

“…A conventional approach of designing an RS codec for 176 bits of information (Example 1) is to design (a) one RS (30,22,8) code in F 2 8 or (b) perform two transmissions of RS (15,11,4) codes in F 2 8 (data length = 2×8×15 = 240 bits). It is clear that reducing the length of the code (from 30 to 15 in this example) would be highly advantageous in terms of performance.…”

“…Based on MCRS scheme, we wish to design an MCRS (15,11,4) codec over F 2 8 corresponding to the F 2 16 codec in Example 1. Given 15 symbols of 16 bits each (equivalent to F 2 16 shortened codec), first eight bits of each symbol will be in the first instance of MCRS codec and last eight bits in the second.…”

“…We call it a dual codec ( = 2 instances of encoder/decoder over F 2 16/2 ). Similarly, a quad-codec MCRS (15,11,4) can be designed over F 2 4 , which is shown by third stage in Figure 1(A). The value of for this codec is given by four since there are four parallel instances of the encoder/decoder.…”

“…In general, the efficiency is lower than that of conventional networks due to frequent propagation errors. Their average BER is known to be in the range from 10 −6 to 10 −3 [4], implying that many packets would be corrupted and thus dropped over wireless channels without some appropriate error prevention or recovery mechanisms. Hence, it becomes an important issue to choose an energy efficient error recovery protocol, especially for applications such as medical, multimedia and image transport, and surveillance, which require high reliability in data transfer.…”