Channel Parameter Estimation for Scatter Cluster Model Using Modified MUSIC Algorithm

Abstract

Recently, the scatter cluster models which precisely evaluate the performance of the wireless communication system have been proposed in the literature. However, the conventional SAGE algorithm does not work for these scatter cluster-based models because it performs poorly when the transmit signals are highly correlated. In this paper, we estimate the time of arrival (TOA), the direction of arrival (DOA), and Doppler frequency for scatter cluster model by the modified multiple signal classification (MUSIC) algorithm. Using the space-time characteristics of the multiray channel, the proposed algorithm combines the temporal filtering techniques and the spatial smoothing techniques to isolate and estimate the incoming rays. The simulation results indicated that the proposed algorithm has lower complexity and is less time-consuming in the dense multipath environment than SAGE algorithm. Furthermore, the estimations’ performance increases with elements of receive array and samples length. Thus, the problem of the channel parameter estimation of the scatter cluster model can be effectively addressed with the proposed modified MUSIC algorithm.

Direction of Arrival Estimation Based on the Multistage Nested Wiener Filter

“…The performance of array processing algorithms is improved by the sensor array location error calibration, which made the algorithms insensitive to the model uncertainties and deterministic signals with unknown waveforms [8]. The performance of the wireless communication system is evaluated based on scatter cluster models by estimating the corresponding parameters [9]. Array sensor and subarray adaptive beamforming techniques obtain the best antijamming performance widely used in GNSS receivers [10], active radar, and sonar [11].…”

“…In the last two decades, smart antenna has been widely used in many applications such as radar, sonar, and wireless communication systems [1]. It is also utilized in tracking [2, 3], localization [4, 5], intelligent transportation [6], ultra-wideband wireless sensor networks [7], array calibration [8], scatter cluster model [9], and antijamming [10]. For example, the multiple input multiple output (MIMO) radar utilizes multiple sensor array antennas to simultaneously transmit and receive diverse waveforms, which estimates the signal parameters to locate and track the target [2].…”

Efficient Neural Network Approach for 2d Doa Estimation Based on Antenna Array Measurements

“…By exploiting the users' spatial separability, this multi-user access scheme has the ability to automatically sense and suppress interference while simultaneously enhancing desired signal reception [1]. The typical procedure of SDMA includes Direction of Arrival (DOA) estimation of users' signals and adaptive beamforming.…”