Performance evaluation of non-prefiltering vs. time reversal prefiltering in distributed and uncoordinated IR-UWB ad-hoc networks

Time Reversal (TR) is a prefiltering scheme mostly analyzed in the context of centralized and synchronous IR-UWB networks, in order to leverage the trade-off between communication performance and device complexity, in particular in presence of multiuser interference. Several strong assumptions have been typically adopted in the analysis of TR, such as the absence of Inter-Symbol / Inter-Frame Interference (ISI/IFI) and multipath dispersion due to complex signal propagation. This work has the main goal of comparing the performance of TR-based systems with traditional non-prefiltered schemes, in the novel context of a distributed and uncoordinated IR-UWB network, under more realistic assumptions including the presence of ISI/IFI and multipath dispersion. Results show that, lack of power control and imperfect channel knowledge affect the performance of both non-prefiltered and TR systems; in these conditions, TR prefiltering still guarantees a performance improvement in sparse/low-loaded and overloaded network scenarios, while the opposite is true for less extreme scenarios, calling for the developement of an adaptive scheme that enables/disables TR prefiltering depending on network conditions

Deep Learning-aided TR-UWB MIMO System

This paper presents a novel deep learning-aided scheme dubbed PRρ-net for improving the bit error rate (BER) of the Time Reversal (TR) Ultra-Wideband (UWB) Multiple Input Multiple Output (MIMO) system with imperfect Channel State Information (CSI). The designed system employs Frequency Division Duplexing (FDD) with explicit feedback in a scenario where the CSI is subject to estimation and quantization errors. Imperfect CSI causes a drastic increase in BER of the FDD-based TR-UWB MIMO system, and we tackle this problem by proposing a novel neural network-aided design for the conventional precoder at the transmitter and equalizer at the receiver. A closed-form expression for the initial estimation of the channel correlation is derived by utilizing transmitted data in time-varying channel conditions modeled as a Markov process. Subsequently, a neural network-aided design is proposed to improve the initial estimate of channel correlation. An adaptive pilot transmission strategy for a more efficient data transmission is proposed that uses channel correlation information. The theoretical analysis of the model under the Gaussian assumptions is presented, and the results agree with the Monte-Carlo simulations. The simulation results indicate high performance gains when the suggested neural networks are used to combat the effect of channel imperfections

Performance Enhancement of Multiuser Time Reversal UWB Communication System

UWB communication is a recent research area for indoor propagation channels. Time Reversal (TR) communication in UWB has shown promising results for improving the system performance. In multiuser environment, the system performance is significantly degraded due to the interference among different users. TR reduces the interference caused by multiusers due to its spatial focusing property. The performance of a multiuser TR communication system is further improved if the TR filter is modified. In this paper, multiuser TR in UWB communication is investigated using simple TR filter and a modified TR filter with circular shift operation. The concept of circular shift in TR is analytically studied. Thereafter, the channel impulse responses (CIR) of a typical indoor laboratory environment are measured. The measured CIRs are used to analyze the received signal peak power and signal to interference ratio (SIR) with and without performing the circular shift operation in a multiuser environment

Time Domain Measurements for a Time Reversal SIMO System in Reverberation Chamber and in an Indoor Environment

International audienceTime domain measurements are conducted for ultra-wideband (UWB) signals in a reverberation chamber (RC) and in a typical indoor environment for a single input multiple output (SIMO) time reversal (TR) system. Different TR characteristics i.e. TR peak performance, TR focusing gain, average power increase, signal to side lobe ratio (SSR) and delay spread are analyzed and compared to that of a single input single output (SISO) TR system

Closed-Form Derivations of ISI and MUI for Time-Reversed Ultra Wideband

Through transmitter pre-filtering, a time reversed UWB system is capable if harnessing a multipath channel to achieve temporal and spatial focusing. Unfortunately, large RMS channel delay spread leads to significant intersymbol and multiuser interference. This paper presents closed-form expressions for self and multi-user interference for a UWB system utilizing a time-reversed approach. The influence of user multiplexing codes is taken to account through incorporation of a ‘separation probability’, which characterizes a family of hopping sequences. The standardized IEEE 802.15.3a channel model is applied, and the derived performances are compared with that of a simulated time hopped time-reversed UWB system

Multiuser Time Reversal UWB Communication System: A Modified Transmission Approach

International audienceIn this paper, ultra-wideband (UWB), time reversal (TR) communication is investigated by modifying the transmission prefilter. Mathematical expressions for received signal and the interference in the modified transmission scheme are derived. It is shown that the modified transmission approach reduces multi-user interference which eventually translates into a better bit error rate (BER) performance than simple TR multiuser scheme. Channel impulse responses (CIR) of a typical indoor channel are measured. In a multi-user scenario, both TR and the modified TR schemes are studied using the measured CIRs. It is shown that the proposed modified TR scheme outperforms the original TR scheme