Abstract
Current wireless systems offer various use-cases where conventional channel capacity focused performance criteria might not apply. Following the similar perspective, convolutional encoding can find more room due to its low complexity and low decoding delay. Besides, it has been also shown that error performance of a convolutional encoder can be improved further by using adaptive irregular constellations. A new performance measure, data-oriented approach, was recently proposed for the transmission of small data packets, i.e. mission-critical IoT applications, over fading channels. In this letter, delay performance gain resulting from convolution coding optimized irregular constellations is investigated. Then, we derive a new performance criterion based on delay and finite block length constraints. Based on this criterion, we design irregular constellations together with convolutional coding for short packet transmission.
Highlights
T RADITIONAL broadband wireless systems have been designed for large packet sizes without imposing delay constraints [1]
Channel coding techniques utilizing the iterative decoding process; such as turbo and low-density parity check (LDPC) codes, gained considerable popularity for decades and there was a tense competition in channel code design for reaching Shannon channel capacity
The simulation results show that the irregular constellations based on individual data transmission yields considerable gain for a given block length and target error probability
Summary
T RADITIONAL broadband wireless systems have been designed for large packet sizes without imposing delay constraints [1]. Terminated and tail-biting convolutional encoders might be promising for short packet transmission over sensor networks. The former one is more preferable due to having less data rate loss [8]. Capacity formula assuming cannot be adopted since it lacks of characterizing the reliability and latency In those cases, [17] proposed a more refined analysis of the maximum achievable rate as a function of the block length and target decoding error probability. Data-oriented approach in constellation design is introduced for convolutional coded finite block length transmission. The simulation results show that the irregular constellations based on individual data transmission yields considerable gain for a given block length and target error probability
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