Seung-Woo Ko

Cognitive Random Access for Internet-of-Things Networks

This paper focuses on cognitive radio (CR) internet- of-things (IoT) networks where spectrum sensors are deployed for IoT CR devices, which do not have enough hardware capability to identify an unoccupied spectrum by themselves. In this sensor- enabled IoT CR network, the CR devices and the sensors are separated. It induces that spectrum occupancies at locations of CR devices and sensors could be different. To handle this difference, we investigate a conditional interference distribution (CID) at the CR device for a given measured interference at the sensor. We can observe a spatial correlation of the aggregate interference distribution through the CID. Reflecting the CID, we devise a cognitive random access scheme which adaptively adjusts transmission probability with respect to the interference measurement of the sensor. Our scheme improves area spectral efficiency (ASE) compared to conventional ALOHA and an adaptive transmission scheme which attempts to send data when the sensor measurement is lower than an interference threshold.

Network Coding for Bidirectional Traffic in IEEE 802.16 Systems

In this paper, we investigate how the IEEE 802.16 based wireless system can adopt the network coding. To avoid the problem of overhearing, we focus on the bidirectional traffic, where each end node exchanges network coded data over a relay node. The bidirectional traffic is usually observed in Internet, where TCP makes congestion control and error recovery based on the acknowledgement from the opposite direction. Thus, enhancing the spectral efficiency of wireless Internet through the network coding is expected. Our simulation with realistic radio characteristics and TCP-like traffic shows that the network coding improves the throughput by an average of 36 percent compared to the simple relay case.