In this paper, we design a mathematical model for performance and reliability evaluation of the IEEE 802.11p Enhanced Distributed Channel Access (EDCA) broadcast scheme in Dedicated Short-Range Communication (DSRC) with the presence of hidden terminals. Specifically, we first introduce a more accurate semi-Markov process (SMP) model to portray the channel contention among multiple types of safety messages and their backoff behavior in DSRC based vehicular ad hoc networks (VANETs) with the influence of hidden terminals. Each type of safety message's generation and service in an individual vehicular node is modeled leveraging a unique M/G/1/K queue. For the channel contention, the SMP model interrelates with the M/G/1/K queue via fixed-point iteration. Additionally, grounded on the solution of fixed-point iteration, we acquire the performance indices such as packet delay (PD), packet delivery rate (PDR), and packet reception rate (PRR). The new SMP model considers the IEEE 802.11p EDCA backoff counter process, unsaturated packet arrivals, limited MAC queue length, hidden terminals, Nakagami-m fading channel with distance-related path loss, and distinct transmission, carrier sensing and interference ranges. Eventually, we validate the correctness of the model through the comparison between the numerical and simulation results under different network parameters and prove that the proposed model has an advantage over the existing models in analyzing the impact of hidden terminals on PDR and PRR.

Purpose – The purpose of this paper is to present a model calibration technique for modulated wideband converter (MWC) with non-ideal lowpass filter. Without making any change to the system architecture, at the cost of a moderate oversampling, the calibrated system can perform as the system with ideal lowpass filter. Design/methodology/approach – A known test sparse signal is used to approximate the finite impulse response (FIR) of the practical non-ideal lowpass filter. Based on the approximated FIR filter, a digital compensation filter is designed to calibrate the practical filter. The calibrated filter can meet the perfect reconstruction condition. The non-ideal sub-Nyquist samples are filtered by a compensation filter. Findings – Experimental results indicate that, by calibrating the MWC with the proposed algorithm, the impaction of non-ideal lowpass filter could be avoided. The performance of signal reconstruction could be improved significantly. Originality/value – Without making any change to the MWC architecture, the proposed algorithm can calibrated the non-ideal lowpass filter. By filtering the non-ideal sub-Nyquist samples with the designed compensation filter, the original signal could be reconstructed with high accuracy.

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An improved random equivalent sampling (RES) approach based on compressed sensing (CS) for repetitive ultrasonic signal detection is presented. The proposed system considers recovering ultrasonic signal with high equivalent sampling frequency from samples captured using analogue-to-digital converter (ADC) clocked at a rate much lower than Nyquist rate. A basis function is constructed to realise the ultrasonic signal sparse representation, which paves the way for applying CS theory to ultrasonic signal sub-Nyquist sampling. A sampling architecture is developed, which is applicable for ultrasonic compressive detection. The CS measurement matrix is constructed in the context of RES. Experimental results indicate that, with this sampling system, an ultrasonic signal sampled at ultra-low rate, but still can be recovered with overwhelming probability.