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In this paper, an ultrawideband localization system to improve the cyclists’ safety is presented. The architectural solutions proposed consist of tags placed on bikes, whose positions have to be estimated, and anchors, acting as reference nodes, located at intersections and/or on vehicles. The peculiarities of the localization system in terms of accuracy and cost enable its adoption with enhanced risk assessment units situated on the infrastructure/vehicle, depending on the architecture chosen, as well as real-time warning to the road users. Experimental results reveal that the localization error, in both static and dynamic conditions, is below 50 cm in most of the cases.

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This paper proposes novel and generalized expressions to characterize the performance of modern cellular networks under realistic user mobility behavior. The η-µ distribution is employed to derive the received power probability density function, the average bit error rate for different modulation schemes, and the coverage probability assuming a Poisson point process spatial distribution of base stations in downlink. The user is assumed to experience fading with Maximum Ratio Combining (MRC) and move according to a random way-point mobility model. To get more insights on the achivable diversity order, accurate asymptotic expressions for the coverage probability and average bit error rate are derived. The derived expressions are applicable to different widely-used fading environments, such as Rayleigh and Nakagami-m as particular cases, by an appropriate selection of the η-µ parameters. Monte Carlo simulation was used to show the validity of the proposed expressions. In addition, the generalized expressions allow the system designer to quantify the effects of user mobility on the cellular network performance, in different propagation environments, and network topologies as a function of the number of base stations and MRC branches.

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<p>In intelligent reflecting surface (IRS)-assisted communications, the ultimate gain is achieved when the phases of the reflected signals are optimally selected to maximize the signal-to-noise ratio (SNR). However, practical hurdles, particularly the imperfect phase estimation and quantization can reduce the potential gain. Therefore, this work aims at evaluating the impact of applying a quantized phase in the presence of phase estimation errors. Towards this goal, we derive the probability density function (PDF) of the estimated quantized phase, then using the sinusoidal addition theorem (SAT), the PDF of the received signal envelope is derived and used to derive closed-form expressions of the symbol error rate (SER) and outage probability (OP). The obtained analytical and simulation results show that the SER and OP jointly depend on the SNR, phase estimation accuracy, number of IRS elements, and number of quantization levels. The imperfect phase and quantization demonstrated several counterintuitive results. In particular, it is shown that increasing the number of IRS elements or the number of quantization levels may degrade the system performance. Moreover, the results reveal that the impact of phase quantization increases as the phase estimation accuracy decreases. The results also show that the performance is susceptible to phase errors with an even number of reflectors and binary quantization levels.</p>

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