Abstract
In this contribution, a high-resolution parameter estimation algorithm is derived based on the Space-Alternating Generalized Expectation-maximization (SAGE) principle for extracting multipath parameters from the output of sliding correlator (SC). The SC allows calculating channel impulse responses with a sampling rate less than that required by Nyquist criterion, and hence is widely used in real-time wideband (e.g., >500 MHz) channel sounding for the fifth generation wireless communication scenarios. However, since the sounding signal needs to be sent repetitively, the SC-based solution is unacceptable for time-variant channel measurements. The algorithm proposed here estimates multipath parameters by using a parametric model of both low- and high-frequency components of the SC’s output. The latter was considered as distortions and discarded in the conventional SC-based channel sounding. The new algorithm allows estimating path parameters with less repetitions of transmitting the sounding signal and still exhibits higher estimation accuracy than the conventional method. Simulations are conducted and illustrate the root mean square estimation errors and the resolution capability of the proposed algorithm with respect to the bandwidth and the length of the SC’s output. These studies pave the way for measuring time-variant wideband propagation channels using SC-based solutions.
Highlights
Measurement-based channel models are important for verifying the performance of wireless communication systems in realistic propagation scenarios [1, 2]
Yin et al EURASIP Journal on Wireless Communications and Networking (2015) 2015:165 recording the complex time-domain signals, and not suitable for investigating the wideband channel characteristics extracted from multipath parameters
Our simulation results here show that the SNR should be kept beyond 10 and 40 dB in order to obtain RMSEE(ν) less than 10 Hz when the low-pass filtering (LPF) bandwidth Bn is set with n ≥ 5 and n ≤ 3, respectively
Summary
Measurement-based channel models are important for verifying the performance of wireless communication systems in realistic propagation scenarios [1, 2]. A Space-Alternating Generalized Expectation-maximization (SAGE) estimation approach was introduced in [13] which is derived based on a parametric model characterizing the SC’s output, allowing the estimation of multipath parameters by using higherfrequency components This solution still relies on the SC’s output obtained by sending the sounding signals many times. No thorough investigation has been carried out so far for the feasibility of accurate parameter estimation based on the SC’s outputs without sending the sounding signals repetitively In this contribution, the SAGE algorithm originally derived in [13] based on a parametric model for both lowand high-frequency components of SC’s output is elaborated. Its performances in estimating multipath parameters are investigated extensively by using simulations It shows that without discarding the higher-frequency components of SC’s output, the estimation accuracy, for delay parameters, can be improved substantially. To improve the understandings of the mathematical notations adopted in this contribution, Table 1 lists all the symbols introduced and corresponding explanations
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