This paper presents an analytical framework for evaluating beam misalignment in 3GPP mmWave NR systems implementing analog beamforming. Our approach captures the interaction between user mobility, beam sweeping mechanisms, and deployment configurations, focusing on long-term average performance metrics. Specifically, we model the beam misalignment rates at both the base station (BS) and user equipment (UE) as Poisson processes and derive expressions for the expected misalignment duration, misalignment fraction, and overall beamforming gain. The framework accounts for practical constraints in NR such as Synchronization Signal Blocks (SSB) periodicity, TDD frame structures, and SSB overhead. Through numerical evaluation based on 3GPP mmWave parameters, we identify key trade-offs between beam counts, user mobility, and SSB timing, providing actionable design insights for robust and efficient beam management in future high-frequency networks.

Reliable wireless communication is crucial for the interconnected manufacturing systems of Industry 4.0. However, the dense distribution of stations (STAs) and obstacles such as concrete walls and machinery can adversely affect radio performance. Our study investigates the performance of Legacy Wi-Fi and Wi-Fi 6 in a factory through simulations. A ray-tracing-based propagation model is used to account for the challenging radio environment. Based on this, we apply Access Point (AP) grouping strategies to assign the constrained Wi-Fi spectrum in the factory. Multiple traffic types are simulated within the digital twin factory model to evaluate the key performance indicators (KPIs). Our findings show that Wi-Fi 6 significantly reduces Round Trip Time (RTT) compared to Legacy Wi-Fi, though increased bandwidth can lead to higher co-channel interference. The analysis also indicates the difficulty of optimizing Wi-Fi performance in industrial scenarios due to the multiplicity of influencing factors and the complexity of their correlation.

With the advent of 5G, communication in the mmW ave band (24-100 GHz) became one of the cornerstones of wireless communication research in the last years due to the large amount of available spectrum in said band, enabling the usage of bandwidths of up to 400 MHz [1]. Notably, operation in such bands entails a cell coverage shrinkage due to the worsening of the propagation conditions, partially compensated via beamforming techniques. Now, in advancing beyond 5G (B5G), the shift towards subTHz (90-300 GHz) and THz(0.3-10 THz) bands seems inevitable in order to harvest even broader bandwidths. This transition will further worsen channel conditions and shrink cell coverage, calling for Ultra-Dense Cell (UDC) deployments. In this work, we forecast frequency bands, communication bandwidths, antenna array sizes, and spatial multiplexing capabilities for B5G deployments to assess their impact on cell range and fronthaul (FH) capacity. Our work advances the state of the art in that it analyzes potential B5G configurations in terms of bandwidth, antenna, and layer numbers, as well as exploring non-standard functional splits (e.g., splits 7a, 7c, 7e). Fig. 1 shows the achievable signal-to-noise-ratio (SNR) against the cell coverage range for the downlink (DL) of a cellular system operating at bands 3.5-90 GHz, with path-loss model in [2]. By example, to ensure a target SNR=10 dB, densification requirements increase from a cell range (distance between base station, BS, and user equipment, UE) of 800 m(3.5 GHz) to 150 m(90 GHz).

This paper studies integrated sensing and communication (ISAC) in the downlink of a cell-free massive multiple-input multiple-output (MIMO) system with multi-static sensing and ultra-reliable low-latency communication (URLLC) users. We propose a successive convex approximation-based power allocation algorithm that maximizes energy efficiency while satisfying the sensing and URLLC requirements. In addition, we provide a new definition for network availability, which accounts for both sensing and URLLC requirements. The impact of blocklength, sensing requirement, and required reliability as a function of decoding error probability on network availability and energy ef-ficiency is investigated. The proposed power allocation algorithm is compared to a communication-centric approach where only the URLLC requirement is considered. It is shown that the URLLC-only approach is incapable of meeting sensing requirements, while the proposed ISAC algorithm fulfills both sensing and URLLC requirements, albeit with an associated increase in energy consumption. This increment can be reduced up to 75% by utilizing additional symbols for sensing. It is also demonstrated that larger blocklengths enhance network availability and offer greater robustness against stringent reliability requirements.

This paper studies an integrated sensing and communication (ISAC) system within a centralized cell-free massive MIMO (multiple-input multiple-output) network for target detection. ISAC transmit access points serve the user equipments in the downlink and optionally steer a beam toward the target in a multi-static sensing framework. A maximum a posteriori ratio test detector is developed for target detection in the presence of clutter, so-called target-free signals. Additionally, sensing spectral efficiency (SE) is introduced as a key metric, capturing the impact of resource utilization in ISAC. A power allocation algorithm is proposed to maximize the sensing signal-to-interference-plus-noise ratio while ensuring minimum communication requirements. Two ISAC configurations are studied: utilizing existing communication beams for sensing and using additional sensing beams. The proposed algorithm’s efficiency is investigated in realistic and idealistic scenarios, corresponding to the presence and absence of the target-free channels, respectively. Despite performance degradation in the presence of target-free channels, the proposed algorithm outperforms the interference-unaware benchmark, leveraging clutter statistics. Comparisons with a fully communication-centric algorithm reveal superior performance in both cluttered and clutter-free environments. The incorporation of an extra sensing beam enhances detection performance for lower radar cross-section variances. Moreover, the results demonstrate the effectiveness of the integrated operation of sensing and communication compared to an orthogonal resource-sharing approach.

Feasibility of using unlicensed spectrum for ultra reliable low latency communications (URLLC) is still a question for beyond 5G wireless networks. Low latency access to the channel and efficiently sharing spectrum among the multiple users are the main requirements for exploiting unlicensed spectrum for URLLC. Listen before talk and back-off procedures implemented to avoid the collisions in channel access hinder the low latency communication. In this paper, we propose a novel low-latency medium access control (MAC) scheme based on the collision resolution for a pairwise random wireless network. We use geometric sequence decomposition for collision resolution among the competing users. This enables the system to tackle collisions and thus removing the need for carrier sensing and back-off procedures. This saves time in obtaining access to the channel and improves the efficiency of the system. We implement our approach in the synchronized time slotted system and show that it yields significant improvement over existing MAC schemes.

This paper studies a joint communication and sensing (JCAS) system with downlink communication and multi-static sensing for single-target detection in a cloud radio access network architecture. A centralized operation of cell-free massive MIMO is considered for communication and sensing purposes. The JCAS transmit access points (APs) jointly serve the user equipments (UEs) and optionally steer a beam towards the target. A maximum a posteriori ratio test detector is derived to detect the target using signals received at distributed APs. We propose a power allocation algorithm to maximize the sensing signal-to-noise ratio under the condition that a minimal signal-to-interference-plus-noise ratio value for each UE is guaranteed. Numerical results show that, compared to the fully communication-centric power allocation, the detection probability under a certain false alarm probability can be increased significantly by the proposed algorithm for both JCAS setups: i) using additional sensing symbols or ii) using only existing communication symbols.

The sparsity of multipaths in the wideband channel has motivated the use of compressed sensing for channel estimation. In this letter, we propose a different approach to sparse channel estimation. We exploit the fact that L taps of channel impulse response in time domain constitute a non-orthogonal superposition of L geometric sequences in frequency domain. This converts the channel estimation problem into the extraction of the parameters of geometric sequences. Numerical results show that the proposed scheme is superior to existing algorithms in high signal-to-noise ratio (SNR) and large bandwidth conditions.

This paper presents a computationally efficient technique for decomposing non-orthogonally superposed k geometric sequences. The method, which is named as geometric sequence decomposition with k-simplexes transform (GSD-ST), is based on the concept of transforming an observed sequence to multiple k-simplexes in a virtual k-dimensional space and correlating the volumes of the transformed simplexes. Hence, GSD-ST turns the problem of decomposing k geometric sequences into one of solving a k-th order polynomial equation. Our technique has significance for wireless communications because sampled points of a radio wave comprise a geometric sequence. This implies that GSD-ST is capable of demodulating randomly combined radio waves, thereby eliminating the effect of interference. To exemplify the potential of GSD-ST, we propose a new radio access scheme, namely non-orthogonal interference-free radio access (No-INFRA). Herein, GSD-ST enables the collision-free reception of uncoordinated access requests. Numerical results show that No-INFRA effectively resolves the colliding access requests when the interference is dominant.