Low Earth orbit (LEO) satellite constellations are a key enabler for non-terrestrial networks (NTNs) in sixth-generation (6G) systems. However, achieving high reliability over NTN links for mission-critical applications remains challenging, particularly for high-mobility terminals. Existing transmission diversity techniques based on selection combining or maximal ratio combining (MRC) provide no guaranteed recovery under simultaneous channel outages. Moreover, conventional retransmission schemes in the NTN are incompatible with strict latency constraints in 6G. This paper introduces a diversity transform that integrates forward error correction (FEC) coding with transmission diversity to improve the reliability of orthogonal time frequency space (OTFS)-modulated LEO NTN downlinks. It guarantees block-erasure recovery up to a prescribed number of subchannels, with residual errors corrected by the outer FEC, thereby eliminating retransmissions. The transform is inserted between the FEC encoder and the modulator, enabling compatibility with various coding schemes and channel models. In this system, a data word is first partitioned into subwords, each independently FEC encoded. A diversity mapper then distributes these encoded subwords across the available subchannels using a binary transform matrix derived from a Reed–Solomon code. This structure guarantees block-erasure recovery whenever a sufficient number of subchannels survive, with residual errors corrected by the outer FEC. An ephemeris-driven reliability prediction framework is developed, combining orbital mechanics, atmospheric models, and a finite-blocklength error probability analysis derived for OTFS transmission over transparent satellite relays. The framework enables proactive outage prediction without channel state information feedback. Simulation results show that the proposed diversity transform provides lower block error rate and reduced latency compared to standalone FEC and retransmission schemes, especially under blockage and high-Doppler conditions characteristic of LEO NTN links.

Intelligent reflecting surface (IRS), consisting of low-cost passive elements, is a promising technology for improving the spectral and energy efficiency of the fifth-generation (5G) and beyond networks. It is also noteworthy that an IRS can shape the reflected signal propagation. Most works in IRS-assisted systems have ignored the impact of the inevitable residual hardware impairments (HWIs) at both the transceiver hardware and the IRS while any relevant works have addressed only simple scenarios, e.g., with single-antenna network nodes and/or without taking the randomness of phase noise at the IRS into account. In this work, we aim at filling up this gap by considering a general IRS-assisted multi-user (MU) multiple-input single-output (MISO) system with imperfect channel state information (CSI) and correlated Rayleigh fading. In parallel, we present a general computationally efficient methodology for IRS reflecting beamforming (RB) optimization. Specifically, we introduce an advantageous channel estimation (CE) method for such systems accounting for the HWIs. Moreover, we derive the uplink achievable spectral efficiency (SE) with maximal-ratio combining (MRC) receiver, displaying three significant advantages being: 1) its closed-form expression, 2) its dependence only on large-scale statistics, and 3) its low training overhead. Notably, by exploiting the first two benefits, we achieve to perform optimization with respect to the RB that can take place only per several coherence intervals, and thus, reduces significantly the computational cost compared to other methods based on instantaneous CSI which require frequent phase optimization. Among the insightful observations, we highlight that the unrealistic assumption of uncorrelated Rayleigh fading does not allow optimization of the SE, which makes the application of an IRS ineffective. Also, in the case that the phase drifts, describing the distortion of the phases in the RBM, are uniformly distributed, the presence of an IRS provides no advantage. The analytical results outperform previous works and are verified by Monte-Carlo (MC) simulations.

Although the intelligent reflecting surface (IRS) has attracted significant interest, existing works have not addressed adequately the impact of its inevitable phase errors by taking into account their randomness. In this work, we focus on covering this gap by considering a general large IRS-assisted multi-user (MU) multiple-input single-output (MISO) system with imperfect CSI and correlated Rayleigh fading. On this ground, we perform a beneficial channel estimation (CE), and we obtain the achievable sum spectral efficiency (SE) in closed-form in terms of the large-scale channel statistics. The whole approach suggests a novel computationally efficient method for reflect beamforming matrix (RBM) optimization of IRS-assisted large multi-antenna systems that can take place at every several coherence intervals. Monte-Carlo simulations verify the analytical insightful results. Among the observations, we highlight that if the IRS phase noise follows the uniform distribution or if independent Rayleigh fading is assumed, the use of the IRS has no benefit.

Abstract Hybrid processing in millimeter wave (mmWave) communication has been proposed as a solution to reduce the cost and energy consumption by reducing the number of radio‐frequency (RF) chains. However, the impact of the inevitable residual transceiver hardware impairments (RTHIs), including the residual additive transceiver hardware impairments (RATHIs) and the amplified thermal noise (ATN), has not been sufficiently studied in mmWave hybrid processing. In this work, the hybrid precoder and combiner are designed, which include both digital and analog processing by taking into account the RATHIs and the ATN. In particular, a thorough study is provided to shed light on the degradation of the spectral efficiency (SE) of the practical system. The outcomes show the steady degradation of the performance by the ATN across all SNR values, which becomes increasingly critical for higher values of its variance. Furthermore, it is shown that RATHIs result in degradation of the system only in the high SNR regime. Hence, their impact in mmWave system operating at low SNRs might be negligible. Moreover, an increase concerning the number of streams differentiates the impact between the transmit and receive RATHIs with the latter having a more severe effect.

Despite the deleterious effect of hardware impairments (HWIs) on wireless systems, most prior works in cell-free (CF) massive multiple-input-multiple-output (mMIMO) systems have not accounted for their impact. In particular, the effect of phase noise (PN) has not been investigated at all in CF systems. Moreover, there is no work investigating HWIs in scalable CF (SCF) mMIMO systems, encountering the prohibitively demanding fronthaul requirements of large networks with many users. Hence, we derive the uplink spectral efficiency (SE) under HWIs with minimum mean-squared error (MMSE) combining in closed-form by means of the deterministic equivalent (DE) analysis. Notably, previous works, accounted for MMSE decoding, studied the corresponding SE only by means of simulations. Numerical results illustrate the performance loss due to HWIs and result in insightful conclusions.

The increasing demand for green wireless communications and the benefits of the promising cell-free (CF) massive multiple-input-multiple-output (mMIMO) systems towards their optimal energy efficiency (EE) are the focal points of this work. Specifically, despite previous works assuming a uniform placement for the access points (APs), we consider that their locations follow a Poisson point process (PPP) which approaches their opportunistic spatial randomness. Based on stochastic geometry, we derive a lower bound on the average spectral efficiency, and under a realistic power consumption model for CF mMIMO systems, we formulate an EE maximization problem achieving to obtain in closed form the optimal EE per unit area in terms of the pilot reuse factor and the AP density. Note that we have defined the EE per unit area and not just the EE to characterize the energy in systems with multi-point transmission. Thus, we provide important design insights for energy-efficient CF mMIMO systems.

Small-cell densification is a strategy enabling the offloading of users from macro base stations (MBSs), in order to alleviate their load and increase the coverage, especially, for cell-edge users. In parallel, as the network increases in density, the BS cooperation emerges as an efficient design method towards the demands for drastic improvement of the system performance against the detrimental overall interference. We, therefore, model and scrutinize a heterogeneous network (HetNet) of two tiers (macro and small cells) with multiple-antenna BSs serving a multitude of users, which differ with respect to their basic design parameters, e.g., the deployment density, the number of transmit antennas, and transmit power. In addition, the tiers are enhanced with cell association policies by introducing the concept of the association probability. Above this and motivated by the advantages of cooperation among BSs, the small base stations (SBSs) are enriched with this property in their design. The SBS cooperation allows shedding light into its impact on the cell selection rules in multi-antenna HetNets. Under these settings, software-defined networking (SDN) is introduced smoothly to play the leading role in the orchestration of the network. In particular, heavy operations such as the coordination and the cell association are undertaken by virtue of an SDN controller performing and managing efficiently the corresponding computations due to its centralized adaptability and dynamicity towards the enhancement and potential scalability of the network. In this context, we derive the coverage probability and the mean achievable rate. Not only we show the outperformance of BS cooperation over uncoordinated BSs, but we also demonstrate that the SBS cooperation enables the admittance of more users from the macro-cell BSs (MBSs). Furthermore, we show that by increasing the number of BS antennas, the system performance is improved as the metrics under study reveal. Moreover, we investigate the performance of different transmission techniques, and we identify the optimal bias in each case when SBSs cooperate. Finally, we depict that the SBS densification is beneficial until a specific density value since a further increase does not increase the coverage probability.

A new advanced medium access control protocol is described to support 100 km reach access networks, exhibiting the required quality-of-service for next generation passive optical networks based on orthogonal frequency division multiple access. The protocol enables the optical network units (ONUs) to utilize the idle period in each packet transmission time based on their originally granted bandwidth, using the same subcarriers but different time slots to increase the effective transmission bandwidth. The network throughput, end-to-end packet delay and packet loss rate are evaluated by means of both service level agreement and class-of-service differentiation. As a result the packet delay at 80% ONU offered load is less than 3 ms even for the lowest service level ONUs. In addition, the throughput efficiency is 94% of the total network capacity of 40 Gbps, for 100 km long-reach links.

Due to the large number of wireless cells that are required for accurately evaluating inter-site interference in cellular networks, computational resources often pose a considerable limitation. In this paper, a novel method for modeling interference at the edges of the region of interest (ROI) of the cellular topology is proposed. While it shares conceptual ground with previous wrap-around techniques, the proposed method can still be applied over existing solutions without distorting their topology, as conventional toroid shaping is not required. Thus, it allows platforms to retain forward compatibility with network planning tools. System level simulations of a one-tier long term evolution (LTE) network have clearly demonstrated uniform interference across the ROI while achieving an almost three-fold increase in computational efficiency over existing platforms.

The authors briefly describe the Radon transform and the computational considerations necessary to enhance linear features in noisy images. The implementation of the transform a multitransputer network is discussed, and results are presented to demonstrate the performance of the network topology. Feature identification in synthetic aperture radar (SAR) images is considered as an example. The multitransputer network described performs Radon transforms within a few seconds, and linear features in noisy images can be rapidly enhanced. The transputer network architecture can easily be reconfigured to suit various processing algorithms, and the system therefore provides versatile high-speed image processing facilities for a number of computationally intensive applications.>