Title :
Decentralized Wireless Networks With Asynchronous Users and Burst Transmissions
Author :
Moshksar, Kamyar ; Khandani, Amir K.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada
Abstract :
This paper studies a decentralized wireless network of asynchronous transmitter-receiver pairs with burst transmissions. Each receiver learns about the number of active users, channel coefficients, and mutual delays based on locally available measurements. The estimates for the mutual delays are not perfect, however, they are reliable enough to guarantee successful decoding. Two signalling schemes are addressed, namely, randomized masking (RM) and reduced cycle transmission (RCT). Under RM, the n symbols of a codeword are generated according to a Bernoulli-Gaussian distribution with activity factor 0 <; θ ≤ 1. This is in contrast to RCT where each codeword consists of ⌈θn⌉ Gaussian symbols followed by n-⌈θn⌉ zeros. Assuming the transmitters are unaware of the number of users, channel coefficients, and mutual delays, the probability of outage under RM is considerably lower compared with RCT if the signal-to-noise ratio (SNR) is sufficiently large. A generalized RCT scheme is also examined where the n - ⌈θn⌉ zero symbols are not necessarily located at the end of a codeword. In the asymptote of large SNR, the outage probability becomes vanishingly small under RM, however, it is bounded away from zero for generalized RCT regardless of the value of SNR.
Keywords :
Gaussian channels; Gaussian distribution; radiofrequency interference; wireless channels; Bernoulli-Gaussian distribution; Gaussian interference channels; Gaussian symbols; RCT; RM; SNR; active users; asynchronous transmitter-receiver; asynchronous users; burst transmissions; channel coefficients; decentralized wireless networks; generalized RCT scheme; mutual delays; randomized masking; reduced cycle transmission; signal-to-noise ratio; Delays; Random variables; Receivers; Signal to noise ratio; Synchronization; Transmitters; Wireless networks; Asynchrony; Channel Learning; Decentralized Networks; Outage Analysis; Randomized Masking; Reduced Cycle Transmission; channel learning; decentralized networks; outage analysis; randomized masking; reduced cycle transmission;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2015.2439269