Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

   

2010 Research Summary

Dynamic Spectrum Management in Unlicensed Bands

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Ahmad Bahai and Ali Motamedi

Due to the rapid deployment of wireless devices, the spectrum for wireless communication is getting crowded. With the rapid deployment of wireless LANs and other devices operating in the ISM band, the interference between adjacent wireless networks has become the main technical challenge for dense deployment scenarios. The advent of the 802.11n standard with higher transmission range will exacerbate the interference problem in the near future. Although the 802.11n standard is designed to provide 300 Mb/s data rate, the potential interference limits the data rate. More importantly, the unpredictability of interference limits the possibility of using the 802.11n standard for providing real-time applications such as video/audio distribution and IPTV distribution. In this research, we will investigate different techniques to combat the interference problem in order to provide a reliable communication channel for home networking in dense deployment scenarios.

For the 802.11n standard, there have been numerous efforts to improve the physical layer (PHY), such as employing multiple input multiple output (MIMO) and beam forming techniques. However, the media access layer (MAC) remains rudimentary. Several studies have been performed that show the detrimental effect of the interference on the throughput and quality of service (QoS) of 802.11 based home gateways.

Without an intelligence spectrum management layer on top of the standard to combat the interference, 802.11n will face serious problems and will not be able to provide satisfactory improvements over the previous standards in terms of throughput and QoS. In this proposal, we plan to tackle this problem by first understanding the nature of interference more accurately through modeling of shadowing, path loss, and traffic patterns. Utilizing this knowledge, spectrum management algorithms that reduce the effect of interference in dense deployment scenarios will be investigated. The dynamic spectrum management algorithm is formulated as a stochastic control problem. Each station measures the success or failure of transmission and maximum possible transmission rate in each channel to determine the optimal transmission parameters. These parameters include the operating channel, transmission power, modulation scheme and coding. Finally, the effectiveness of our algorithms will be tested using simulation and prototype development via mad-wifi and ath9k.