Polarization-Aware Antenna Selection for Joint Radar and Communication in XL-MIMO Systems

A key challenge in dual-polarized multiplexing for joint radar and communication (JRC) systems is cross-polarization (cross-pol) leakage caused by depolarization. In conventional MIMO systems, depolarization arises solely from the channel; however, in XL-MIMO systems, non-stationary properties of the array cause additional polarization shifts at each antenna element, further degrading JRC performance. This paper introduces a channel model incorporating polarization shifts due to the propagation channel and antenna elements in the near-field. We also propose an antenna selection (AS) scheme that dynamically chooses antennas based on polarization imbalance and cross-pol leakage, enhancing spectral efficiency, symbol error rate, and radar detection probability. Simulations show that the proposed AS significantly outperforms traditional methods, providing scalable benefits for XL-MIMO JRC systems.

Single-Carrier Waveform Design for Joint Sensing and Communication

The emergence of 6G wireless networks demands solutions that seamlessly integrate communication and sensing. This letter proposes a novel waveform design for joint sensing and communication (JSAC) systems, combining single-carrier interleaved frequency division multiplexing (SC-IFDM), a 5G communication candidate signal, with frequency modulated continuous wave (FMCW), widely used for sensing. The proposed waveform leverages the sparse nature of FMCW within SC-IFDM to achieve orthogonal integration in three steps: SC-IFDM symbols are allocated alongside the sparse FMCW, followed by the SC-IFDM transform into the time domain, and a cyclic prefix (CP) is applied in which phase shifts are introduced to the FMCW. Additionally, an enhanced channel estimation method is incorporated to boost system performance. Simulation results demonstrate the proposed waveform's ability to deliver high-resolution sensing and superior communication performance, surpassing traditional multicarrier designs.

Redefining Orthogonal Co-Existence: A Mother Waveform Framework for DFT-Based Waveforms

In this paper, we introduce the concept of a mother waveform to address key challenges in 5th generation (5G) and 6th generation (6G) networks, including spectral efficiency, backward compatibility, enhanced flexibility, and the integration of joint sensing and communication (JSAC). We propose single-carrier interleaved frequency division multiplexing (SC-IFDM) as the mother waveform and demonstrate, through rigorous mathematical modeling, that it can generate all discrete Fourier transform (DFT)-based waveforms without requiring structural modifications. Specifically, by selectively configuring lattice indices and phase adjustments, SC-IFDM enables seamless adaptation to diverse waveforms, such as orthogonal frequency division multiplexing (OFDM), orthogonal chirp division multiplexing (OCDM), orthogonal time-frequency space (OTFS), affine frequency division multiplexing (AFDM), and frequency-modulated continuous wave (FMCW) within a unified framework. Critical aspects such as coexistence strategies and resource allocation are thoroughly explored. Simulation results demonstrate the proposed frameworks ability to deliver superior communication performance, robust sensing capabilities, and efficient coexistence, surpassing traditional waveform designs in scalability and adaptability.

Joint Adaptive OFDM and Reinforcement Learning Design for Autonomous Vehicles: Leveraging Age of Updates

Millimeter wave (mmWave)-based orthogonal frequency-division multiplexing (OFDM) stands out as a suitable alternative for high-resolution sensing and high-speed data transmission. To meet communication and sensing requirements, many works propose a static configuration where the wave's hyperparameters such as the number of symbols in a frame and the number of frames in a communication slot are already predefined. However, two facts oblige us to redefine the problem, (1) the environment is often dynamic and uncertain, and (2) mmWave is severely impacted by wireless environments. A striking example where this challenge is very prominent is autonomous vehicle (AV). Such a system leverages integrated sensing and communication (ISAC) using mmWave to manage data transmission and the dynamism of the environment. In this work, we consider an autonomous vehicle network where an AV utilizes its queue state information (QSI) and channel state information (CSI) in conjunction with reinforcement learning techniques to manage communication and sensing. This enables the AV to achieve two primary objectives: establishing a stable communication link with other AVs and accurately estimating the velocities of surrounding objects with high resolution. The communication performance is therefore evaluated based on the queue state, the effective data rate, and the discarded packets rate. In contrast, the effectiveness of the sensing is assessed using the velocity resolution. In addition, we exploit adaptive OFDM techniques for dynamic modulation, and we suggest a reward function that leverages the age of updates to handle the communication buffer and improve sensing. The system is validated using advantage actor-critic (A2C) and proximal policy optimization (PPO). Furthermore, we compare our solution with the existing design and demonstrate its superior performance by computer simulations.

A High Altitude Platform-Based 3D Geometrical Channel Model for Beamforming Characterization in Future 6G Flying Ad-Hoc Networks

Growing requirements of future wireless communication systems, such as high data rates, high reliability, and low latency, make the active usage of Non-Terrestrial Networks (NTN) an inevitable necessity. In this regard, High Altitude Platforms (HAPs) have drawn great attention in recent years due to their unique characteristics such as high coverage, long operational durability, and ad-hoc movement. However, for the active usage of HAPs, channel models for their various usage scenarios must be well-defined, especially in those cases where the sophisticated multiple-input multiple-output (MIMO) techniques, such as beamforming, are utilized to increase the data rate. Therefore, in this study, an air-to-air (A2A) three dimensional (3D) geometrical channel model is proposed to characterize the beamforming capabilities of non-stationary HAP networks operating at millimeter wave (mmWave) frequency band. In this regard, the 3D geometry of the two HAPs in the air is analyzed, and the effect of Doppler due to the movement of HAPs is interrogated as well as its effect on the signal-to-noise ratio (SNR). The final outputs of this study show that the proposed A2A channel model is applicable to characterize the future sixth generation (6G) HAP networks when the mmWave is used to utilize beamforming with a large number of antennas.

Fast Network Recovery from Large-Scale Disasters: A Resilient and Self-Organizing RAN Framework

Extreme natural phenomena are occurring more frequently everyday in the world, challenging, among others, the infrastructure of communication networks. For instance, the devastating earthquakes in Turkiye in early 2023 showcased that, although communications became an imminent priority, existing mobile communication systems fell short with the operational requirements of harsh disaster environments. In this article, we present a novel framework for robust, resilient, adaptive, and open source sixth generation (6G) radio access networks (Open6GRAN) that can provide uninterrupted communication services in the face of natural disasters and other disruptions. Advanced 6G technologies, such as reconfigurable intelligent surfaces (RISs), cell-free multiple-input-multiple-output, and joint communications and sensing with increasingly heterogeneous deployment, consisting of terrestrial and non-terrestrial nodes, are robustly integrated. We advocate that a key enabler to develop service and management orchestration with fast recovery capabilities will rely on an artificial-intelligence-based radio access network (RAN) controller. To support the emergency use case spanning a larger area, the integration of aerial and space segments with the terrestrial network promises a rapid and reliable response in the case of any disaster. A proof-of-concept that rapidly reconfigures an RIS for performance enhancement under an emergency scenario is presented and discussed.

OFDM-RSMA: Robust Transmission under Inter-Carrier Interference

Rate-splitting multiple access (RSMA) is a multiple access scheme to mitigate the effects of the multi-user interference (MUI) in multi-antenna systems. In this study, we leverage the interference management capabilities of RSMA to tackle the issue of inter-carrier interference (ICI) in orthogonal frequency division multiplexing (OFDM) waveform. We formulate a sum-rate maximization problem to find the optimal subcarrier and power allocation for downlink transmission in a two-user system using RSMA and OFDM. A weighted minimum mean-square error (WMMSE)-based algorithm is proposed to obtain a solution for the formulated non-convex problem. We show that the marriage of rate-splitting (RS) with OFDM provides complementary strengths to cope with peculiar characteristic of wireless medium and its performance-limiting challenges including inter-symbol interference (ISI), MUI, ICI, and inter-numerology interference (INI). The sum-rate performance of the proposed OFDM-RSMA scheme is numerically compared with that of conventional orthogonal frequency division multiple access (OFDMA) and OFDM-non-orthogonal multiple access (NOMA). It is shown that the proposed OFDM-RSMA outperforms OFDM-NOMA and OFDMA in diverse propagation channel conditions owing to its flexible structure and robust interference management capabilities.

Performance Analysis of OTSM under Hardware Impairments in Millimeter-Wave Vehicular Communication Networks

Orthogonal time sequency multiplexing (OTSM) has been recently proposed as a single-carrier (SC) waveform offering similar bit error rate (BER) to multi-carrier orthogonal time frequency space (OTFS) modulation in doubly-spread channels under high mobilities; however, with much lower complexity making OTSM a promising candidate for low-power millimeter-wave (mmWave) vehicular communications in 6G wireless networks. In this paper, the performance of OTSM-based homodyne transceiver is explored under hardware impairments (HIs) including in-phase and quadrature imbalance (IQI), direct current offset (DCO), phase noise, power amplifier non-linearity, carrier frequency offset, and synchronization timing offset. First, the discrete-time baseband signal model is obtained in vector form under the mentioned HIs. Then, the system input-output relations are derived in time, delay-time, and delay-sequency (DS) domains in which the parameters of HIs are incorporated. Analytical studies demonstrate that noise stays white Gaussian and effective channel matrix is sparse in the DS domain under HIs. Also, DCO appears as a DC signal at receiver interfering with only the zero sequency over all delay taps in the DS domain; however, IQI redounds to self-conjugated fully-overlapping sequency interference. Simulation results reveal the fact that with no HI compensation (HIC), not only OTSM outperforms plain SC waveform but it performs close to uncompensated OTFS system; however, HIC is essentially needed for OTSM systems operating in mmWave and beyond frequency bands.

Network-Independent and User-Controlled RIS: An Experimental Perspective

The march towards 6G is accelerating and future wireless network architectures require enhanced performance along with significant coverage especially, to combat impairments on account of the wireless channel. Reconfigurable intelligent surface (RIS) technology is a promising solution, that has recently been considered as a research topic in standards, to help manipulate the channel in favor of users needs. Generally, in experimental RIS systems, the RIS is either connected to the transmitter (Tx) or receiver (Rx) through a physical backhaul link and it is controlled by the network and requires significant computation at the RIS for codebook (CB) designs. In this paper, we propose a practical user-controlled RIS system that is isolated from the network to enhance communication performance and provide coverage to the user based on its location and preference. Furthermore, a low-complexity algorithm is proposed to aid in CB selection for the user, which is performed through the wireless cloud to enable a passive and energy efficient RIS. Extensive experimental test-bed measurements demonstrate the enhanced performance of the proposed system while both results match and validate each other.

Quasisynchronous LoRa for LEO Nanosatellite Communications

Perfect synchronization in LoRa communications between Low Earth Orbit (LEO) satellites and ground base stations is still challenging, despite the potential use of atomic clocks in LEO satellites, which offer high precision. Even by incorporating atomic clocks in LEO satellites, their inherent precision can be leveraged to enhance the overall synchronization process, perfect synchronization is infeasible due to a combination of factors such as signal propagation delay, Doppler effects, clock drift and atmospheric effects. These challenges require the development of advanced synchronization techniques and algorithms to mitigate their effects and ensure reliable communication from / to LEO satellites. However, maintaining acceptable levels of synchronization rather than striving for perfection, quasisynchronous (QS) communication can be adopted which maintains communication reliability, improves resource utilization, reduces power consumption, and ensures scalability as more devices join the communication. Overall, QS communication offers a practical, adaptive, and robust solution that enables LEO satellite communications to support the growing demands of IoT applications and global connectivity. In our investigation, we explore different chip waveforms such as rectangular and raised cosine. Furthermore, for the first time, we study the Symbol Error Rate (SER) performance of QS LoRa communication, for different spreading factors (SF), over Additive White Gaussian Noise (AWGN) channels.