This paper presents a wireless data collection frame-work that employs an unmanned aerial vehicle (UAV) to efficiently gather data from distributed IoT sensors deployed in a large area. Our approach takes into account the non-zero communication ranges of the sensors to optimize the flight path of the UAV, resulting in a variation of the Traveling Salesman Problem (TSP). We prove mathematically that the optimal waypoints for this TSP-variant problem are restricted to the boundaries of the sensor communication ranges, greatly reducing the solution space. Building on this finding, we develop a low-complexity UAV-assisted sensor data collection algorithm, and demonstrate its effectiveness in a selected use case where we minimize the total energy consumption of the UAV and sensors by jointly optimizing the UAV's travel distance and the sensors' communication ranges.

Vector Quantized Variational Autoencoder (VQ-VAE) has shown promise in representing diverse and complex data distributions in deep learning, making it a potential solution for various applications including wireless communications. In this paper, we propose a joint source-channel coding scheme based on VQ-VAE for point-to-point wireless communication. Our approach leverages the dependence of the encoder and decoder on a given dataset and channel conditions to develop efficient encoding and decoding schemes, leading to improved reliability and efficiency even in the presence of noisy wireless channels. We demonstrate the effectiveness of our proposed approach through extensive simulations in handling realistic wireless communication scenarios. In addition, we discuss potential connections to semantic communication and highlight the secure and energy-efficient nature of our approach.

Recently, large intelligent surfaces/antennas (LISA) have been widely studied as an emerging technology for future wireless networks. In general, LISA contains a large number of passive sensors that are able to adjust a phase-shift on impinging signals. To this end, an intelligent module can control this phase-shift resulting in controlling the wireless multipath channel phase-distortion which is random in nature. In this work, we study on how a LISA can serve multiple device-to-device (D2D) communications. Here, LISA sensors are scarce resources which should be allocated among the D2D communications optimally. For this purpose, we propose a Genetic algorithm-based optimization to maximize the spectral efficiency and minimize the interference. Our approach has been evaluated with extensive simulations, thus providing new observations and findings.

In this paper, we discuss two different designs of network coding (NC) for ultra-reliable low latency communication (URLLC) over fading channels. It is shown that a conventional design has the error floor as the error rate does not go to 0 although the erasure probability approaches 0. The other design does not have this problem. By deriving an asymptotic expression for a low erasure probability, we show that how the key factors of NC designs play a role in lowering the error rate in URLLC.

In pursuit of advanced wireless communications, demands for higher capacity and maximum possible efficiency have been a continuous desire since the beginning of the first generation of mobile communications. In 1948, Claude Shannon found that by controlling the wireless channels, the signal strength can be improved at the receiver side and a higher capacity can be obtained. However, controlling the signal propagation over noisy and random wireless channels had not been a convenient task so far. Nevertheless, nowadays, a revolution has been beginning in the smart world where advanced intelligent meta-surfaces (IMSs) are to support a pioneering degree of freedom in engineering wave-matter interactions across a wide range of operating frequencies, from microwave to Terahertz bands. This article presents an overview of the “Advanced Intelligent Meta-surfaces” to Various Scenarios in a comprehensive style. At a high level, we investigate the state-of-the-art of IMS for 6G where a new notion of prefabricated IMS-empowered wall assists the outdoor-to-indoor communication in high frequencies.

Enabling ultrareliable low-latency communication (URLLC) with stringent requirements for transmitting data packets (e.g., 99.999% reliability and 1-ms latency) presents considerable uplink transmission challenges. For each packet transmission over dynamically allocated network radio resources, the conventional random access protocols are based on a request-grant scheme. This induces excessive latency and necessitates reliable control signaling, resulting in overhead. To address these problems, grant-free (GF) solutions are proposed in the fifth-generation (5G) new radio (NR). In this article, an overview and vision of the state of the art in enabling GF URLLC are presented. In particular, we first provide a comprehensive review of NR specifications and techniques for URLLC, discuss underlying principles, and highlight impeding issues of enabling GF URLLC. Furthermore, we briefly explain two key phenomena of massive multiple-input–multiple-output (mMIMO) (i.e., channel hardening and favorable propagation) and build several deep insights into how celebrated mMIMO features can be exploited to address the issues and enhance the performance of GF URLLC. Moving further ahead, we examine the potential of cell-free (CF) mMIMO and analyze its distinctive features and benefits over mMIMO to resolve GF URLLC issues. Finally, we identify future research directions and challenges in enabling GF URLLC with CF mMIMO.

Massive multiple input multiple output (mMIMO) assisted grant-free random access (RA) (mGFRA) has been considered a promising RA scheme for future machine-type communication (MTC). In mGFRA, the nature that RA user equipments (UEs) blindly interplay each other in the presence of preamble collision degrades the performance of RA UEs. To address the issue, a mMIMO assisted semi-grant-free RA (mSGFRA) scheme is considered in this paper, where a downlink feedback based on the preamble detection after the preamble phase is introduced. With such a feedback, RA UEs experiencing preamble collision are enforced to keep silent in data-transmission phase, which in turn enhances the performance of RA UEs without experiencing preamble collision. To understand the performance behaviours of mSGFRA, we first analyse the preamble detection performance in mSGFRA and reveal that accurate collided-preamble detection can be achieved with the assistance of mMIMO. Then, we analyse and compare the performance of mSGFRA and mGFRA in terms of success probability. Simulation results validate theoretical analysis and confirm the potential superiority of mSGFRA to mGFRA.

With the increasing adoption of millimeter-waves (mmWave) over cellular networks, outdoor-to-indoor (O2I) communication has been one of the challenging research problems due to high penetration loss of buildings. To address this, we investigate the practicability of utilizing reconfigurable intelligent surfaces (RISs) for assisting such O2I communication. We propose a new notion of prefabricated RIS-empowered wall consisting of a large number of chipless radio frequency identification (RFID) sensors. Each sensor maintains its own bank of delay lines. These sensors which are built within the building walls can potentially be controlled by a main integrated circuit (IC) to regulate the phase of impinging signals. To evaluate our idea, we develop a thorough performance analysis of the RIS-based O2I communication in the mmWave network using stochastic-geometry tools for blockage models. Our analysis facilitates two closed-form approximations of the downlink signal-to-noise ratio (SNR) coverage probability for RIS-based O2I communication. We perform extensive simulations to evaluate the accuracy of the derived expressions, thus providing new observations and findings.

Ambient backscatter communication (AmBC) has been introduced to address communication and power efficiency issues for short-range and low-power Internet-of-Things (IoT) applications. On the other hand, reconfigurable intelligent surface (RIS) has been recently proposed as a promising approach that can control the propagation environment especially in indoor communication environments. In this paper, we propose a new AmBC model over ambient orthogonal-frequency-division-multiplexing (OFDM) subcarriers in the frequency domain in conjunction with RIS for short-range communication scenarios. A tag transmits one bit per each OFDM subcarrier broadcasted from a WiFi access point. Then, RIS augments the signal quality at a reader by compensating the phase distortion effect of multipath channel on the incident signal. We also exploit the special spectrum structure of OFDM to transmit more data over its squeezed orthogonal subcarriers in the frequency domain. Consequently, the proposed method improves the bit-error-rate (BER) performance and provides a higher data rate compared to existing AmBC methods. Analytical and numerical evaluations show the superior performance of the proposed approach in terms of BER and data rate.