Non-stationary Multipath Fading Channel Research Articles

Modelling and Analysis of Nonstationary Vehicle‐to‐Infrastructure Channels with Time‐Variant Angles of Arrival

In mobile radio channel modelling, it is generally assumed that the angles of arrival (AOAs) are independent of time. This assumption does not in general agree with real‐world channels in which the AOAs vary with the position of a moving receiver. In this paper, we first present a mathematical model for the time‐variant AOAs. This model serves as the basis for the development of two nonstationary multipath fading channels models for vehicle‐to‐infrastructure communications. The statistical properties of both channel models are analysed with emphasis on the time‐dependent autocorrelation function (ACF), time‐dependent mean Doppler shift, time‐dependent Doppler spread, and the Wigner‐Ville spectrum. It is shown that these characteristic quantities are greatly influenced by time‐variant AOAs. The presented analytical framework provides a new view on the channel characteristics that goes well beyond ultra‐short observation intervals over which the channel can be considered as wide‐sense stationary.

A Novel Non-Stationary Multipath Fading Channel Model Based on Propagation Measurements Using SDR and FPGA

A Novel Non-Stationary Multipath Fading Channel Model Based on Propagation Measurements Using SDR and FPGA

A Novel Non-Stationary Multipath Fading Channel Model Based on Propagation Measurements Using SDR and FPGA

A Novel Non-Stationary Multipath Fading Channel Model Based on Propagation Measurements Using SDR and FPGA

Advanced blind adaptive multi-user detector for communications in nonstationary multipath fading channel

This paper deals with an adaptive multi-user detector for direct sequence code division multiple access (DS/CDMA) wireless communication systems, named advanced blind adaptive multi-user detector (ABA-MUD), whose main features are low complexity and joint utilization of time diversity and adaptive blind processing techniques. Differently from known blind adaptive detectors, the proposed scheme achieves remarkable performance even in critical time-varying environments by means of a suitable window reprocessing technique. The ABA-MUD avoids the use of training sequences and only needs knowledge of timing and signature waveform of the desired user, number of active users and a rough evaluation of the signal-to-interference ratio (SIR) for a proper setting of the detection algorithm. Numerical results, shown here in terms of bit error rate (BER), highlight good behavior and remarkable near-far resistance of the proposed ABA-MUD receiver with respect to different alternatives, in particular, in the case of worst fading environments.