Abstract

This paper considers beamforming for a reconfigurable intelligent surface (RIS)-aided multiple input single output (MISO) communication system in the presence of Rician multipath fading. Our aim is to jointly optimize the transmit beamformer and RIS phase shift matrix for maximizing the mean signal-to-noise (SNR) of the combined signal received over direct and indirect links. While numerical solutions are known for such optimization problems, this is the first paper to derive closedform expressions for the optimal beamformer and the phase shifter for a closely related problem. In particular, we maximize a carefully constructed lower bound of the mean SNR, which is more conducive to analytical treatment. Further, we show that effective channel gain under optimal beamforming follows Rice distribution. Next, we use these results to characterize a closedform expression for the outage probability under the proposed beamforming scheme, which is subsequently employed to derive an analytical expression for the ergodic capacity. Finally, we numerically demonstrate the efficacy of the proposed beamformer solution in comparison with the existing algorithmically obtained optimal solution for the exact mean SNR maximization. Index Terms—RIS, Optimal Beamforming, Rician Channel, Outage Analysis, Ergodic Capacity, and Maximum Mean SNR.

Abstract

This article proposes Convolutional Neural Network based Auto Encoder (CNN-AE) to predict location dependent rate and coverage probability of a network from its topology. We train the CNN utilising BS location data of India, Brazil, Germany and the USA and compare its performance with stochastic geometry (SG) based analytical models. In comparison to the best-fitted SGbased model, CNN-AE improves the coverage and rate prediction errors by a margin of as large as 40% and 25% respectively. As an application, we propose a low complexity, provably convergent algorithm that, using trained CNN-AE, can compute locations of new BSs that need to be deployed in a network in order to satisfy pre-defined spatially heterogeneous performance goals. Index Terms—Network Performance Prediction, Convolutional Neural Network, Stochastic Geometry, Network Design

Abstract

The unmanned aerial vehicle (UAV) based communication is expected to play an important role in enabling a variety of applications in future cellular networks. However, because of the mobility of the UAVs, the communications links involving UAVs undergo large-scale temporal variations in the received signal quality, which may affect the quality-of-service of the underlying application. Therefore, it is crucial to characterize the time-varying process of signal quality observed by the UAVs. In this paper, we consider a scenario in which a cellular-connected UAV acts as a user equipment (UAV-UE), where the locations of base stations (BSs) follow a Poisson point process (PPP) and the UAV-UE is moving along a 3GPP-inspired straight-line trajectory. For this setting, we study the properties of the time-varying successful transmission process that is defined in terms of the time-varying signal-to-noise ratio (SNR) observed at the UAV. In particular, we show that this process is a wide sense stationary (WSS) process and derive its first- and second-order statistics. Finally, we establish an equivalence between the successful transmission processes observed by a UAV-UE served by terrestrial BSs and a terrestrial user served by UAV mounted BSs (UAV-BSs) each moving along an independent straight-line trajectory.

Abstract

We have analyzed the thermal blooming effect on laser beam propagation under atmospheric turbulence in different environments. It is observed that the laser source having an input power of less than 4 kW is less affected by thermal blooming and more appropriate for incoherent beam combinations in any environmental conditions.

Abstract

This paper demonstrates radio frequency (RF) sens- ing of saccharides such as glucose, fructose and sucrose based on Complementary Split Ring Resonator (CSRR). The CSRR based planar sensor is designed and fabricated over FR4 substrate of thickness 1.6 mm and with copper on both sides of thickness 0.035 mm. The fabricated sensor is connected to the Vector Network Analyzer (VNA) to study the electromagnetic interac- tions behavior between the designed sensor and saccharides. The quantitative and qualitative analysis is conducted by changing the concentration of saccharides in aqueous solution from 10 mg/ml to 50 mg/ml in steps of 10 mg/ml and then by changing the overall sample volume from 1 μl to 100 μl in variable step sizes. The resonant frequency property is utilized for detecting small changes in saccharides concentration of up to 10 mg/ml and overall sample volume change of 1 μl. The proposed RF sensor is highly robust, reliable, cost-effective and easy to use over other existing methodologies. Index Terms—Radio Frequency, Mic

Abstract

This paper reports solvent based optimization of radio frequency (RF) sensors for detecting ethanol mixtures in petrol using complementary split ring resonators (CSRR). The optimization is carried out using binary particle swarm optimization (BPSO) in presence of mask by placing the sample under test (SUT) above the highly sensitive CSRR region. The motivation behind this work has been to detect miniscule changes of ethanol in the dielectric constant of the petrol. The RF sensors designed using BPSO enables faster convergence providing more efficient designs offering enhanced sensitivity at a normalized frequency of 2.66% and 1.81% when compared to 1.02% of conventional CSRR as presented in the simulation results. Index Terms

Abstract

This paper discusses the phenomena of proteresis, commonly known as inverse hysteresis, and the various methods to implement it. Proteresis generates an advanced response when compared to hysteresis, which improves the system's speed, maintaining the noise immunity intact. This feature of proteresis is seen in multiple naturally occurring phenomena. The paper implements proteresis in domains of electronics and optics, keeping in view essential constraints like area, power, throughput, and speed. The electronic domain consists of two models, one using CMOS circuits and the other using discrete components. The transistor-level design of a proteretic device is on 180 nm CMOS technology, and proof of concept is demonstrated using post-layout simulations. This design is operated on a supply voltage of 1.8 V and consumes significantly less power of 633 µW at a moderate frequency of 10 MHz. The …

Abstract

Increasing demands of wearable health monitoring seek dedicated spectrum for short range wireless communication of biosignals, for which frequency band near 400 MHz has been utilized recently. While using the dedicated spectrum, biosignal communication must not cause any out of band radiations and interference, for which there is a strong need to develop spur- free, low phase noise and energy efficient wireless transmitters (TX). In this research, for the first time we present design and implementation of a reference-spur-free, low phase noise, sub-mW dual modulation mode (frequency shift keying (FSK) and on-off keying (OOK)) 400 MHz TX for wearable health monitoring, where RF synthesis depends solely on an extremely low phase noise oscillator, which uses a 400 MHz surface acoustic wave resonator and does not include any power hungry, spur- generating frequency multiplier or phase/frequency lock loop. The proposed TX has been designed and fabricated in 180 nm CMOS technology. Measurement results show that the energy efficiencies of the proposed TX in FSK and OOK mode are 1.8 nJ/bit at 250 kb/s and 0.23 nJ/bit at 2 Mb/s, respectively. To prove the utility of the proposed TX, biosignal communication is also demonstrated with the help of a commercial receiver in actual operating scenarios, where the measured bit error rate in FSK mode was < 10−5 for range of 2 m. Index Terms—Health-monitoring, wearable, spur-free, trans- mitter, FSK, OOK, 400 MHz, MedRadio

Abstract

A Novel Smart Belt for Anxiety Detection, Classification, and Reduction Using IIoMT on Students’ Cardiac Signal and MSY

Abstract

This index covers all technical items—papers, correspondence, reviews, etc.—that appeared in this periodical during 2022, and items from previous years that were commented upon or corrected in 2022. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author’s name. The primary entry includes the coauthors’ names, the title of the paper or other item, and its location, specified by the publication abbrevia- tion, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author’s name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index.