Principles of mobile communication (2nd ed.)
Principles of mobile communication (2nd ed.)
The predictive user mobility profile framework for wireless multimedia networks
IEEE/ACM Transactions on Networking (TON)
A discrete-time model for triply selective MIMO Rayleigh fading channels
IEEE Transactions on Wireless Communications
VEPSD: a novel velocity estimation algorithm for next-generation wireless systems
IEEE Transactions on Wireless Communications
Novel Sum-of-Sinusoids Simulation Models for Rayleigh and Rician Fading Channels
IEEE Transactions on Wireless Communications
A position-based QoS routing scheme for UWB mobile ad hoc networks
IEEE Journal on Selected Areas in Communications - Part 1
Vehicular speed estimation using received signal strength from mobile phones
Proceedings of the 12th ACM international conference on Ubiquitous computing
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In this paper, a new algorithm is proposed to estimate mobile speed for broadband wireless communications, which often encounter large number of fading channel taps causing severe intersymbol interference. Different from existing algorithms, which commonly assume that the fading channel coefficients are available for the speed estimators, the proposed algorithm is based on the received signals which contain unknown transmitted data, unknown frequency selective fading channel coefficients possibly including line-of-sight (LOS) components, and random receiver noise. Theoretical analysis is first carried out from the received signals, and a practical algorithm is proposed based on the analytical results. The algorithm employs a modified normalized auto-covariance of received signal power to estimate the speed of mobiles. The algorithm works well for frequency selective Rayleigh and Rician channels. The algorithm is very resistant to noise, it provides accurate speed estimation even if the signal-to-noise ratio (SNR) is as low as 0 dB. Simulation results indicate that the new algorithm is very reliable and effective to estimate mobile speed corresponding to a maximum Doppler up to 500 Hz. The algorithm has high computational efficiency and low estimation latency, with results being available within one second after communication is established.