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Journal ArticleDOI

Predictive dynamic channel allocation scheme for improving power saving and mobility in BWA networks

Jenhui Chen, +1 more
- 01 Jan 2007 - 
- Vol. 12, Iss: 1, pp 15-30
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TLDR
A new concept of channel allocation model for BWA system is proposed and the relations between the signal propagation and the distance is investigated as well as a signal-aware dynamic channel allocation (SDCA) scheme for dynamicChannel allocation (DCA) in BWA networks (BWANs).
Abstract
The radio spectrum of IEEE 802.16 medium access control (MAC) protocol ranges from 2-66 GHz, which is one of potential solutions for broadband wireless access (BWA) or beyond third generation (B3G)/ 4G networks. The maximum transmission range can reach about 48 km. However, with the property of radio propagation, the maximum transmission distance is proportioned inversely to the frequency the mobile subscriber station (MSS) carries. According to this property, the channel allocation can be based on how far the distance between the MSS and the base station (BS) in a macrocell. Therefore, this paper first proposes a new concept of channel allocation model for BWA system and investigates the relations between the signal propagation and the distance as well as propose a signal-aware dynamic channel allocation (SDCA) scheme for dynamic channel allocation (DCA) in BWA networks (BWANs). The SDCA enables the BS to allocate appropriate channels to MSSs according to the received signal-to-noise ratio (SNR) value from the MSSs. Besides, according to the frequency, the SDCA can estimate a minimum power for MSS to communicate. The SDCA not only increases the capacity of the system but saves the overall power consumption of the system well. We also present a new out-of-service prevention scheme for supporting mobility in the system. Simulation results show that the proposed SDCA can achieve the channel utilization (throughput) by up to 94.4% when the spectrum ranges from 2-11 GHz.

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References
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TL;DR: A statistical path loss model derived from 1.9 GHz experimental data collected across the United States in 95 existing macrocells is presented, and it distinguishes between different terrain categories.
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