Most Integrated Sensing and Communications (ISAC) systems require dividing airtime across their two modes. However, the specific impact of this decision on sensing performance remains unclear and underexplored. In this paper, we therefore investigate the impact on a gesture recognition system using a Millimeter-Wave (mmWave) ISAC system. With our dataset of power per beam pair gathered with two mmWave devices performing constant beam sweeps while test subjects performed distinct gestures, we train a gesture classifier using Convolutional Neural Networks. We then subsample these measurements, emulating reduced sensing airtime, showing that a sensing airtime of 25 % only reduces classification accuracy by 0.15 percentage points from full-time sensing. Alongside this high-quality sensing at low airtime, mmWave systems are known to provide extremely high data throughputs, making mmWave ISAC a prime enabler for applications such as truly wireless Extended Reality.

Hardware impairments in general and amplifier nonlinearity in particular severely limit the performance of communication links. This paper analytically provides statistical results on how a nonlinear amplifier affects the quality of signals in communication systems. In particular, we propose a statistical model that describes the nonlinear distortion as a function of the input signal’s average and instantaneous power and captures the pulse-shaping and matched filters’ effects. We show through simulations and complementary measurements that the proposed model can provide an authentic connection between the communication system parameters, power amplifier nonlinearity characteristics, and the communication system performance. It serves not only as a reliable model for nonlinear distortion analysis but also as a design tool that allows optimization of signal and filter characteristics with respect to nonlinear distortion.

In this research work, a novel framework is proposed as an efficient successor to traditional imaging methods for breast cancer detection in order to decrease the computational complexity. In this framework, the breast is divided into segments in an iterative process and in each iteration, the one having the most probability of containing tumor with lowest possible resolution is selected by using suitable decision metrics. After finding the smallest tumor-containing segment, the resolution is increased in the detected tumor-containing segment, leaving the other parts of the breast image with low resolution. Our framework is applied on the most common used beamforming techniques, such as delay and sum (DAS) and delay multiply and sum (DMAS) and according to simulation results, our framework can decrease the computational complexity significantly for both DAS and DMAS without imposing any degradation on accuracy of basic algorithms. The amount of complexity reduction can be determined manually or automatically based on two proposed methods that are described in this framework.

This study addresses resource allocation problem with partial fairness, considering weighted sum throughput maximisation for an orthogonal frequency‐division multiple access system with half‐duplex decode‐and‐forward relaying. In the system formulation, multi‐cell co‐channel interference as one of the critical factors in multi‐cell processing has been taken into account and its effect on system performance is evaluated. It has been shown that the problem is in the form of combinatorial non‐convex optimisation problems (NP‐hard). Avoiding to solve NP‐hard problem, the authors have made suboptimal solutions according to iterative methods to satisfy the system requirements in the best way. In this way, the resulting non‐convex optimisation problem has been solved by dual Lagrangian decomposition, and iterative resource allocation algorithms are proposed to find solutions which satisfy Karush–Kuhn–Tucker conditions. Two resource allocation strategies based on centralised and distributed scenarios are derived to maximise the average system throughput (bit/s/Hz) considering partial fairness. Simulation results indicate that the authors’ proposed methods work better than interference threshold methods and other conventional algorithms such as single cell methods which use local information processing.