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.

Stacked intelligent metasurfaces (SIM) transceiver design enables precoding in the wave domain while enjoying reduced energy consumption and hardware cost. On this ground and contrary to previous works studying various achievable rates, we derive the ergodic mutual information (EMI) at the large system region in closed form for SIM-assisted multiple-input-multiple-output (MIMO) systems based on statistical channel state information (CSI). Next, by applying a gradient ascent algorithm, we maximize the EMI with respect to the phase shifts of the two SIMs of the transceiver simultaneously, which saves significant overhead compared to a traditional alternating optimization (AO) approach. Simulations shed light in the performance of the proposed system at the large system limit and provide a comparison under different CSI conditions.

Although reconfigurable intelligent surface (RIS) is a promising technology for shaping the propagation environment, it consists of a single-layer structure within inherent limitations regarding the number of beam steering patterns. Based on the recently revolutionary technology, denoted as stacked intelligent metasurface (SIM), we propose its implementation not only on the base station (BS) side in a massive multiple-input multiple-output (mMIMO) setup but also in the intermediate space between the base station and the users to adjust the environment further as needed. For the sake of convenience, we call the former BS SIM (BSIM), and the latter channel SIM (CSIM). To this end, we achieve hybrid wave-based combining at the BS and wave-based configuration at the intermediate space. Specifically, we propose a channel estimation method with reduced overhead, being crucial for SIM-assisted communications. Next, we derive the uplink sum spectral efficiency (SE) in closed form in terms of statistical channel state information (CSI). Notably, we optimize the phase shifts of both BSIM and CSIM simultaneously by using the projected gradient ascent method (PGAM). Compared to previous works on SIMs, we study the uplink transmission in a mMIMO setup, channel estimation in a single phase, a second SIM at the intermediate space, and simultaneous optimization of the two SIMs. Simulation results show the impact of various parameters on the sum SE, and demonstrate the superiority of our optimization approach compared to the alternating optimization (AO) method.

Stacked intelligent metasurfaces (SIM) is a revolutionary technology, which can outperform its single-layer counterparts by performing advanced signal processing relying on wave propagation. In this work, we exploit SIM to enable transmit precoding and receiver combining in holographic multiple-input multiple-output (HMIMO) communications, and we study the achievable rate by formulating a joint optimization problem of the SIM phase shifts at both sides of the transceiver and the covariance matrix of the transmitted signal. Notably, we propose its solution by means of an iterative optimization algorithm that relies on the projected gradient method, and accounts for all optimization parameters simultaneously. We also obtain the step size guaranteeing the convergence of the proposed algorithm. Simulation results provide fundamental insights such the performance improvements compared to the single-RIS counterpart and conventional MIMO system. Remarkably, the proposed algorithm results in the same achievable rate as the alternating optimization (AO) benchmark but with a less number of iterations.

Reconfigurable intelligent surface (RIS) has emerged as a cost-effective solution to improve wireless communication performance through just passive reflection. Recently, the concept of simultaneously transmitting and reflecting RIS (STAR-RIS) has appeared but the study of minimum signal-to-interference-plus-noise ratio (SINR) and the impact of hardware impairments (HWIs) remain open. In addition to previous works on STAR-RIS, we consider a massive multiple-input multiple-output (mMIMO) base station (BS) serving multiple user equipments (UEs) at both sides of the RIS. Specifically, in this work, focusing on the downlink of a single cell, we derive the minimum SINR obtained by the optimal linear precoder (OLP) with HWIs in closed form. The OLP maximises the minimum SINR subject to a given power constraint for any given passive beamforming matrix (PBM). Next, we obtain deterministic equivalents (DEs) for the OLP and the minimum SINR, which are then used to optimise the PBM. Notably, based on the DEs and statistical channel state information (CSI), we optimise simultaneously the amplitude and phase shift by using a projected gradient ascent algorithm (PGAM) for both energy splitting (ES) and mode switching (MS) STAR-RIS operation protocols with reduced feedback, which is quite crucial for STAR-RIS systems that include the double number or variables compared to reflecting only RIS. Simulations verify the analytical results, shed light on the impact of HWIs, and demonstrate the better performance of STAR-RIS compared to conventional RIS. Also, a benchmark full instantaneous CSI (I-CSI) based design is provided and shown to result in higher SINR but lower net achievable sum-rate than the statistical CSI based design because of large overhead associated with the acquisition of full I-CSI acquisition. Thus, not only do we evaluate the impact of HWIs but we also propose a statistical CSI based design that provides higher net sum-rate with low overhead and complexity.

Reconfigurable intelligent surfaces (RIS)-assisted massive multiple-input multiple-output (mMIMO) is a promising technology for applications in next-generation networks. However, reflecting-only RIS provides limited coverage compared to a simultaneously transmitting and reflecting RIS (STAR-RIS). Hence, in this paper, we focus on the downlink achievable rate and its optimization of a STAR-RIS-assisted mMIMO system. Contrary to previous works on STAR-RIS, we consider mMIMO, correlated fading, and multiple user equipments (UEs) at both sides of the RIS. In particular, we introduce an estimation approach of the aggregated channel with the main benefit of reduced overhead links instead of estimating the individual channels. Next, leveraging channel hardening in mMIMO and the use-and-forget bounding technique, we obtain an achievable rate in closed-form that only depends on statistical channel state information (CSI). To optimize the amplitudes and phase shifts of the STAR-RIS, we employ a projected gradient ascent method (PGAM) that simultaneously adjusts the amplitudes and phase shifts for both energy splitting (ES) and mode switching (MS) STAR-RIS operation protocols. By considering large-scale fading, the proposed optimization can be performed every several coherence intervals, which can significantly reduce overhead. Considering that STAR-RIS has twice the number of controllable parameters compared to conventional reflecting-only RIS, this accomplishment offers substantial practical benefits. Simulations are carried out to verify the analytical results, reveal the interplay of the achievable rate with fundamental parameters, and show the superiority of STAR-RIS regarding its achievable rate compared to its reflecting-only counterpart.

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.

We describe the application of subcarrier multiplexing (SCM) to enable broadband transmission beyond the modal bandwidth of multimode fiber (MMF) optical links. The application of a quadrature phase-shift keying modem featuring novel carrier and symbol-timing recovery circuits, demonstrates significant enhancement in channel capacity. By using a 2.7-GHz pilot-tone-injected phase-locked loop (PLL) and referencing subscriber data to a prescaled version of the subcarrier, zero-latency carrier and data synchronization has been achieved exhibiting 675 Mb/s bit-oriented clock extraction in network terminal equipments. The novel scheme is scalable to higher aggregate rates and upgrades to existing installed-base 50 mum MMF infrastructure to provide low-cost, high-capacity interconnects for storage area and campus network applications