Channel Occupancy Measurements in 868 MHz ISM Band in Residential Areas

The rapid development of Internet of Things (IoT) has led to more and more devices using ISM frequency bands. Because they are not time synchronized, medium access collisions are unavoidable. The probability of such a collision is usually reasonably low; however, it increases with the number of transmitters competing for the same frequency channel. For this reason, ISM bands’ occupancy is regularly monitored by researchers. This paper presents the results of the measurement campaign during which a selected part of the 868 MHz ISM frequency band was monitored for the presence of transmissions in six locations in various residential areas in Warsaw, Poland. For the purpose of the campaign, a dedicated measurement set-up comprising a software-defined radio (SDR) module was assembled. The measurements results showed that the channel occupancy is in most cases lower than 1% with a maximum observed value of 2%. The paper presents selected characteristics of the detected signals. Additionally, distribution over time of the detected signals was used together with the Monte Carlo simulations to analyze how long idle time blocks are available for new transmitters that could be deployed in the band under testing.

Channel Occupancy Ratio Based TCP Congestion Control in Adhoc Networks

Wireless Network is been used widely in the recent years due to its low-cost nature. More number of real time applications have been used by varied segments of users across the world. The advancements in the mobile technology have made ad hoc networks as important and active field of communication and networks. Most of the time the network cannot handle the traffic in the network which ultimately affects the Quality of Service (QoS). The conventional Transmission Control Protocol (TCP) cannot handle this huge volume of traffic and control the congestion in the network. This issue in the wireless network is been addressed by various researchers in the world but still the scope and need for improvements are more. This paper analyzes many TCP congestion control mechanisms and proposes an efficient approach for congestion control by estimating Channel Occupancy Ratio (COR). The COR is estimated based on machine learning algorithm which is trained using the historical data extracted from MAC layer. This cross layer based approach is found to be more efficient when compared to other methods proposed in the literature.