Abstract
This paper investigated the throughput performance of a secondary user (SU) for a random primary user (PU) activity in a realistic experimental model. This paper proposed a sensing and frame duration of the SU to maximize the SU throughput under the collision probability constraint. The throughput of the SU and the probability of collisions depend on the pattern of PU activities. The pattern of PU activity was obtained and modelled from the experimental data that measure the wireless local area network (WLAN) environment. The WLAN signal has detected the transmission opportunity length (TOL) which was analyzed and clustered into large and small durations in the CTOL model. The performance of the SU is then analyzed and compared with static and dynamic PU models. The results showed that the SU throughput in the CTOL model was higher than the static and dynamic models by almost 45% and 12.2% respectively. Furthermore, the probability of collisions in the network and the SU throughput were influenced by the value of the minimum contention window and the maximum back-off stage. The simulation results revealed that the higher contention window had worsened the SU throughput even though the channel has a higher number of TOLs.
Highlights
Dynamic spectrum access (DSA) is one of the cognitive radio (CR) technologies, and it is used to utilise the spectrum proficiently
This study intended to investigate the compromise between the increment of secondary users (SU) throughput and the reduction of the interference to understand the fundamental performance of the CR network
These figures show the effect of the various sensing durations on the SU throughput
Summary
Dynamic spectrum access (DSA) is one of the cognitive radio (CR) technologies, and it is used to utilise the spectrum proficiently. The strategy that is used to access the channel should consider analyzing the length of TOL from the PU activity patterns to obtain a better SU performance. The TOL is clustered into two categories which are small and large, and the first order of the Markov model is used to obtain the PU activity pattern based on the clustering of the TOL. EM-PuO model: The PU activity traffic pattern model is designed based on a realistic (i.e., real-time) wireless environment which is WLAN. TOL which approaching the real situation as it was constructed by the experiment in a wireless environment This empirical model will be used to demonstrate the SU access strategy in the CTOL model. The probability of collision and the SU throughput were investigated using CTOL model by considering the dynamic PU traffic
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