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Exploiting cognitive radios for reliable satellite communications
Author(s) -
AbdelRahman Mohammad J.,
Krunz Marwan,
Erwin Richard
Publication year - 2014
Publication title -
international journal of satellite communications and networking
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.388
H-Index - 39
eISSN - 1542-0981
pISSN - 1542-0973
DOI - 10.1002/sat.1083
Subject(s) - computer science , cognitive radio , markov chain , interference (communication) , channel (broadcasting) , communications satellite , network packet , markov process , metric (unit) , markov model , frequency hopping spread spectrum , satellite , real time computing , computer network , telecommunications , wireless , mathematics , statistics , machine learning , operations management , engineering , economics , aerospace engineering
Summary Satellite transmissions are prone to both unintentional and intentional RF interference. Such interference has significant impact on the reliability of packet transmissions. In this paper, we make preliminary steps at exploiting the sensing capabilities of cognitive radios for reliable satellite communications. We propose the use of dynamically adjusted frequency hopping (FH) sequences for satellite transmissions. Such sequences are more robust against targeted interference than fixed FH sequences. In our design, the FH sequence is adjusted according to the outcome of out‐of‐band proactive sensing, carried out by a cognitive radio module that resides in the receiver of the satellite link. Our design, called out‐of‐band sensing‐based dynamic FH, is first analyzed using a discrete‐time Markov chain (DTMC) framework. The transition probabilities of the DTMC are then used to measure the ‘channel stability’, a metric that reflects the freshness of sensed channel interference. Next, out‐of‐band sensing‐based dynamic FH is analyzed following a continuous‐time Markov chain model, and a numerical procedure for determining the ‘optimal’ total sensing time that minimizes the probability of ‘black holes’ is provided. DTMC is appropriate for systems with continuously adjustable power levels; otherwise, continuous‐time Markov chain is the suitable model. We use simulations to study the effects of different system parameters on the performance of our proposed design. Copyright © 2014 John Wiley & Sons, Ltd.