Direct-to-device (D2D) satellite connectivity, an exemplar of non-terrestrial network (NTN) integration with 5G and forthcoming 6G mobile ecosystem, is enjoying rapidly growing prominence. Delivering space-enabled broadband connectivity to smartphones, with their low-power, omnidirectional antennas, requires multitude of technological advancements. One innovation exploits distributed satellite systems using swarms of small regenerative satellites in low-Earth orbit (LEO) that synthesize multiple steerable beams. Another advancement optimizes efficiency of the already scarce radio-frequency (RF) spectrum with full frequency reuse, unfortunately intensifying intrabeam interference. This paper develops novel methodology for unified interference mitigation, comprised of selective precoder and high-performance receiver. Precoder is based on maximizing signal-to-leakage-and-noise ratio (SLNR), made selective about which subset of interference to leave unmitigated. It has low complexity, implemented in two stages to reduce computational requirements and alleviate user-scheduling constraints. High-performance receiver jointly processes signal and dominant interference, building on divide-and-conquer (DAC) paradigm to synergize with selective precoding. It has low complexity with computational load that does not grow exponentially with the number of dominant interferers. Extensive simulations reveal that unified interference mitigation significantly surpasses state-of-the-art schemes in sum-rate throughput, outage probability, and block error rate, also under scenarios of synchronization errors and imperfect channel state information at the transmitter (CSIT).

The increasing deployment of massive active antenna arrays in low Earth orbit (LEO) satellites necessitates computationally efficient and adaptive precoding techniques to mitigate dynamic channel variations and enhance spectral efficiency. Regularized zero-forcing (RZF) precoding is widely used in multi-user MIMO systems; however, its real-time implementation is limited by the computationally intensive inversion of the Gram matrix. In this work, we develop a low-complexity framework that integrates the Woodbury (WB) formula with adaptive randomized singular value decomposition (arSVD) to efficiently update the Gram matrix inverse as the satellite moves along its orbit. By leveraging low-rank perturbations, the WB formula reduces inversion complexity, while arSVD dynamically extracts dominant singular components, further enhancing computational efficiency. Monte Carlo simulations demonstrate that the proposed method achieves computational savings of up to 61% compared to conventional RZF precoding with full matrix inversion, while incurring only a modest degradation in sum-rate performance. These results demonstrate that WB-arSVD offers a scalable and efficient solution for next-generation satellite communications, facilitating real-time deployment in power-constrained environments.

Under the evolution of 6G, the spectrum crunch for new frequencies has introduced the discussion of the 7-24 GHz spectrum, referred to as FR3, for mobile network usage. This spectrum is traditionally known as the dedicated operating frequency for satellite communication, particularly in the Ku-Band (12-18 GHz). To date, little is known about the coexistence of these two entities within the FR3 spectrum and the propagation environment in this frequency range. This paper presents measurements in the 14-14.5GHz spectrum for an outdoor channel scenario, conducted using both a reference communication chain with a low-gain isotropic antenna and a commercially available, highly directive, electronically steerable Starlink user terminal. Evaluations were performed for the received power from the reference antenna, alongside parallel measurements of spurious emissions from the Starlink terminal. In conclusion, this work provides measurements and path loss models to support future investigations of the 14 GHz spectrum for FR3 usage.

This paper presents a master-slave architecture for time, frequency and phase synchronization, implemented in a closed-loop system with an RF inter-satellite link. This addresses the emerging need for accurate and cost-effective synchronization in swarm satellite networks. The design relies on a single reference clock, eliminating the need for unsynchronized local oscillators at secondary nodes. Moreover, it proposes an inherently relative range measurement method between the satellites based on phase unwrapping. Performance analysis, focused on phase accuracy, confirms the system's suitability for satellite swarms in applications like communications and remote sensing. A comprehensive analysis offers additional guidelines for implementation and future research.

Mobile satellite communications are gaining more and more interest in recent years, with SOS-via-satellite, location updating and satellite mobile messaging being important applications for customers. An efficient satellite waveform is the key technology to enable the mobile satellite communication service that will be provided by satellite constellations in the 5G and 6G era. In this paper, we conduct an experimental evaluation of the satellite waveform transmitted by the first satellite-enabled smartphone, the iPhone 14. We forced the device to transmit location data via L-band using the Find My application, while it had no other connectivity than the Globalstar satellites. The results show the temporal and spectral properties of the satellite waveform, and we performed a first estimate of the modulation scheme and data rate.

The growing interest in space-based broadband internet, propelled by the rapid expansion of mega-constellations, amplifies the mounting concerns about interference and spectral coexistence for both operators and users. Given the complexity of these systems, deriving reliable estimates for data rates and interference typically requires labor-intensive simulations. However, recent advancements have introduced analytical methods rooted in stochastic geometry to assess system performances. Building on these insights, our work aims to precisely evaluate interference in these systems, focusing on adjacent satellite interference and multi-beam inter-cell interference. Significantly, we introduce a more refined estimation of these effects based on the nature of highly directive antennas, an aspect missing in current literature. We, therefore, propose numerical approximations for these key values detrimental to high-speed telecommunication systems. We present simulation results to validate our analytical approach and share numerical findings from our proposal to offer deeper insight into mega-constellation systems and designs.

With the allocation of C-band frequencies for 5G networks, in-band interference caused by 5G signals on satellite ground stations operating in the same band has become a serious concern. There are several suggestions on how to deal with this problem, such as exclusion zones for affected stations, hardware modifications and baseband post processing of the received signal. This paper proposes post processing based on the use of reference antennas, which only receive the 5G interference, in combination with adaptive filters. The main limitation with such an approach is the slow convergence speed of the adaptation process in combination with the fast varying channel in 5G due to the use of beamforming. As the first step, we focus our attention on the 5G synchronization signal blocks (SSBs), which are consecutively transmitted from different basestation antennas. The paper proposes exploiting the structure of the SSBs to get channel estimates, which can be used for initializing the adaptive filter. Measurement results with real 5G base stations around Neubiberg, Germany show that the proposed approach can improve the interference cancellation significantly.

For the characterization of radiofrequency interference caused by terrestrial fixed service stations into aircraft earth stations that communicate with geostationary satellite orbit networks in the fixed-satellite service, a detailed channel model is developed. We assess the impact of coherent and non-coherent scattered components of terrestrial fixed service emissions into the aeronautical satellite communications receivers. Firstly, a line-of-sight channel model is presented, which is extended by elements accounting for specular reflection from the Earth's surface and randomly Rayleigh distributed diffuse components. Based on the surface roughness of the spherical Earth model at 18 GHz, we determine the reflection coefficient for typical surfaces. To this end, we provide insight on whether the coherent and non-coherent elements of terrestrial fixed service interference should be considered for aeronautical SATCOM receivers.

To meet the actual traffic demand, this work applies machine learning-based flexible payload power resource-allocation for non-orthogonal SATCOM. Specifically, a tailored deep neural network (DNN) architecture with a customized loss function is trained to intelligently allocate payload power resources among both the beams and users, by learning the undercover structure of its input (i.e., unsupervised learning). Since the DNN-based scheme doesn't need signaling and real-time information exchange between the gateways and the users, it can significantly decrease the implementation complexity by employing the channel statistics of users in multibeam SATCOM. Moreover, the DNN-based scheme can be trained as a universal approximator of the payload power resource-allocation agent for any unseen satellite channel and has the potential for a real-time operation with reduced implementation complexity, compared to the mathematical optimization-based scheme. Numerical results show the DNN-based scheme achieves comparable performance.

Ultra high-throughput satellite (UHTS) systems are expected to play an essential role in future beyond 5G and 6G networks. One of the main sources of degradation in such system is the phase noise. Satellite manufacturers and equipment suppliers have to resort to cumbersome and time-consuming transmission chain simulations to estimate the carrier-to-interference ratio (CIR) caused by the phase noise. Therefore, a novel mathematical CIR formula is proposed in this work for the characterization of phase noise in future UHTS systems. Not only does this expression enable an efficient and accurate assessment of the phase noise degradation, but it can be easily incorporated in the satellite link budget and simply requires a predefined phase noise mask as an input. In this context, the influence of the main phase noise variables and the behavior of typical phase noise masks are analyzed, thus, bringing valuable insights. Finally, the theoretical results are validated through numerical simulations.

In this work, the LEO Land Mobile Satellite (LMS) channel at Ka-band is studied. This work firstly reviews existing Ka-band LMS channel models and measurements, which are mostly related to model the dynamic characteristics for LEO satellite communications, specifically in a restrictive small satellite platform. Moreover, as pervasive satellite Internet of Things (IoT) networks involve on-ground users with low-gain and non-directional antennas, multipath effects cause a frequency selective fading of the received signal. Although extensive propagation experiments are carried out for Ka-band LMS systems, experimental characterizations and studies on multipath effects are lacking. Therefore, this work aims to address this limitation by considering the critical issue of the multipath effects on the Ka-band LEO propagation channel. Hence, we present the results of recent propagation experiments and investigate the multipath effects on Ka-band LEO SATCOM links. The results show comparably large values for the delay spread especially in mountainous scenarios. It is further revealed that results on the multipath propagation that are derived from terrestrial measurements may not be transformed to the LEO satellite channel without the need for adaption.

In the Internet of Remote Things (IoRT), when satellite communication (SATCOM) is the preferred or the only available connection for Internet of Things (IoT)-devices, massive machine type communication (mMTC) is enabled by upcoming and established systems using sophisticated multiple access (MA) techniques. To close the radio link between compact and battery-powered devices, very low symbol rates must be chosen in many cases, due to the constraints of the link budget. If at the same time MA interference must be tolerated, orthogonal signaling with successive interference cancellation (SIC) receivers is usually the physical layer technology of choice in many IoT solutions. While SIC has been investigated for medium and high data rates, phase noise (PN) poses additional challenges for very low data rate transmission. We derive a general performance estimation applicable to SIC-based transmission schemes under PN with different levels of orthogonality between the user signals. Realistic values for the PN are derived from a PN model that includes all relevant PN processes and is parametrized by measurements of the Allan variance of real hardware. It is shown that PN strongly limits the performance of systems with high orthogonality at symbol rates below 1 kHz, while systems with less orthogonal transmit signals and lower spreading gain are more robust.

This work studies the application of nonorthogonal transmission in beamforming (BF) based forward links for next-generation satellite communication (SATCOM) with multiple gateways. With the aim of enhancing the throughput of BF SATCOM systems, the state-of-the-art nonorthogonal multiple access (NOMA) technique is exploited by serving multiple users per beam in the same time slot. In this regard, the feeder link limitations and multibeam satellite payload constraints must be considered for BF design and power allocation (PA) optimization in nonorthogonal SATCOM. To address these challenges, distributed resource optimization strategies are investigated for BF and flexible payload power resource allocation in multigateway (multi-GW) nonorthogonal SATCOM systems. Specifically, a per-feed available power-constrained BF strategy via maximization of the worst-user signal-to-leakage-and-noise ratio (SLNR) is explored with local channel state information (CSI) for a distributed operation of GWs. As an upper-bound performance limit, a centralized multilayer BF strategy is processed in a central unit with full global CSI and data sharing. After the BF direction optimization, a weighted sum-rate maximization-based (WSRM-based) power resource optimization strategy is locally applied at each GW to efficiently use the power resources for higher performance increment. The nonconvex WSRM problem, under the constraints of the practical satellite payload power budget, successful successive interference cancellation (SIC) decoding, and minimum data rate, is recast into an equivalent weighted sum-MSE minimization (WMMSE) counterpart for a tractable solution. Finally, an efficient user scheduling is designed to enable the operator to capture a substantial system-throughput gain. Accurate simulations are conducted with the near-to-real coverage area (footprints), the random distributions of users, and interference, relying on geographical locations of users. The results over a realistic simulation environment show the efficiency of our strategies.

It has been shown that ultra-narrow-band (uNB) massive machine type communication using very compact devices with direct access to satellites is possible at ultra low rate. This enables global ubiquitous coverage for terminals without terrestrial service in the Internet of Remote Things and provides access to any satellite up to the the geostationary earth orbit. The lower data rate for waveforms providing uNB communication is set by the stability and the phase noise of the applied oscillators. In this paper we analyze the physical layer of two candidate waveforms, which are LoRa and Unipolar Coded Chirp-Spread Spectrum (UCSS) with respect to phase noise and oscillator frequency drifts. It is figured out that UCSS is more robust against linear frequency drifts, which is the main source of error for uNB transmissions.

To provide high throughput of beamforming (BF) based forward links in multi-beam satellite communication (SATCOM), the state-of-the-art non-orthogonal multiple access (NOMA) technique has been explored, by serving multiple users per beam in the same time slot. Nevertheless, the feeder link limitations and satellite payload constraints need to be considered for BF design and power allocation (PA) optimization in NOMA based transmission. To tackle these challenges, performance optimization algorithms are investigated for applying NOMABF in the upcoming multiple gateway (multi-GW) architectures. Specifically, centralized multi-layer BF is first processed in a central unit with full global channel state information (CSI) and data sharing, which is considered as an upper-bound performance. Next, per-feed available power-constrained BF via maximization of the worst-user signal-to-leakage-and-noise ratio (SLNR) is explored with local CSI for a distributed operation of GWs. Then, weighted sum-rate maximization (WSRM) based PA is applied to optimally use the power resources for more performance increment, where the non-convex WSRM problem is recast into an equivalent weighted sum mean square error minimization (WMMSE) problem for a tractable solution. Simulation results reveal the efficiency of our proposal.

To meet the target requirements of 5G and 6G systems in terms of throughput and global connectivity, the upcoming Low Earth Orbit (LEO) mega-constellations are set to seamlessly integrate into terrestrial communication networks. Although extensively utilized in terrestrial systems, multi-user multiple-input multiple-output (MU-MIMO) transmission has not yet been implemented in LEO mega-constellation communication systems. In this work, we compare the throughput performance of a MU-MIMO downlink transmission and full frequency reuse (FFR) with the throughput of a multibeam LEO system with conventional four-color frequency reuse (FR4). We employ a deterministic modeling approach of the spacecraft motion, the satellite channel and the pre-generation of the downlink channel state information (CSI). To mitigate co-channel interference in the MIMO case, zero-forcing precoding is applied. We study the effects of an outdated CSI on the MIMO downlink performance. Simulation results confirm that even under the effects of an outdated CSI at the precoder, the MIMO LEO satellite system with FFR substantially outperforms the multibeam scenario with the FR4.

6th Generation (6G) Non- Terrestrial Networks (NTN) prove to be the next step for integrating satellites into existing communication network infrastructure. Moreover, mega-constellations will play a predominant role in this integration. With the success of disruptive and innovative constellations, such as Starlink and OneWeb, a highly competitive field of commercial broadband satellite internet is currently established. In this paper, we introduce a novel technological framework demonstrating the economic performance indicators of mega-constellations to compete with the existing terrestrial broadband internet market. Furthermore, we implement a comprehensive economic model to measure the influence of technology on decreasing the costs in mega-constellations and compare the technological parameters in their cost reduction efficiency. Our analysis enables the identification of main cost drivers in the technical design of mega-constellations, independently of the applied waveform or transmission standard. By optimizing these cost drivers, mega-constellations can achieve a cost regime comparable to terrestrial competitors to secure their participation in future integrated 6G networks.

We investigate the throughput of a multi-user multiple-input multiple-output aviation network where multiple aircraft are connected to a High Throughput Satellite (HTS). We assume full frequency reuse in the downlink and a multibeam antenna architecture with multiple reflectors on the HTS. To maximize the system throughput, we apply zero forcing precoding along with a scheduling algorithm to group multiple aircraft that are simultaneously served with data via space division multiple access. For a more realistic scenario, the flight paths of the airplanes are based on real airline routes, and interference from terrestrial fixed service stations is considered. Our simulation results show that the proposed concept enables a massive throughput increase while the required update rate of the precoder coefficients and the user groups remain moderate.

The leading trends in the framework of the Internet of Things are driving the research community to provide smart systems and solutions aimed at revolutionizing medical sciences and healthcare. One of the major opportunities offered by IoT lies in the ubiquitous connectivity, thus enabling smart services such as remote patient monitoring, in-home therapy/rehabilitation, and assisted living platforms. In this paper we present a prototype of wearable smart glasses able to monitor the Eye Blinks (EBs) through ElectroOculoGram (EOG) signal in a transparent way with respect to the final user. We propose a novel pre-filtering scheme to reduce EOG noise along with an analytical derivation of a matched filter to detect and count EBs. We have carried out an in-depth experimental campaign in order to validate the robustness of our approach with respect to the main solutions available in the literature. Furthermore, we have compared the performances obtained with out wearable prototype versus the results achievable with professional medical equipments. Results show that our solution is able to achieve very high accuracy in EB detection, obtaining comparable performance with respect to professional medical desktop equipment, with the additional benefit of portability, comfort and easiness of use for the patients.

In satellite communication downlinks, physical layer security is challenging to achieve due to their broadcasting nature and Line-of-Sight channel characteristics. This paper provides a precoding algorithm to secure the downlinks of multiple users against multiple eavesdroppers with optimization of the minimum secrecy capacity. By the use of artificial noise, a positive secrecy capacity is achievable even if the number of eavesdroppers is higher than the number of beams. We demonstrate that a multiple-reflector antenna design provides a significantly higher secrecy and throughput performance when compared to a single-reflector design due to additional degrees of freedom, exhibited by the signal phases. The total vulnerability region is introduced as a new figure of merit with respect to unidentified eavesdroppers.

This paper introduces a new magnetic field based system design for 3D-orientation and -position acquisition in mobile applications for human motion analysis. The system basically consists of a source unit and a sensor unit and does not require any line of sight between its components. The source unit contains a single one-axis coil for magnetic field generation as well as a MARG sensor for 3D-orientation estimation. The sensor unit contains a single MARG sensor both for 3D-orientation and 3D-position estimation. For 3D-position estimation, a new algorithm is proposed which exploits not only the magnitude of the coil generated magnetic field, but also the phase information and thus is able to determine a unique position solution based on the data of a single 3D-magnetometer only. A wearable prototype of both the source and the sensor unit is realized and used for system verification by comparing the position data of the prototype to the data of a camera-based reference system (Vicon Vero). The verification results indicate high accuracy and repeatability of the proposed system.

In previous work, it has been shown that massive machine type communication (mMTC) is possible with direct access to satellites in the geostationary earth orbit (GEO) using very compact Internet of Things (IoT) devices. The non-directive antenna of preferably small terminals restricts the transmit power to limit the interference for other satellites. The ultra narrow-band (uNB)-IoT signals received by adjacent satellites are used in this paper for the geolocation of the transmitter. By this, the amount of data is reduced if the position of the sender shall be transmitted. We investigate the accuracy of remote geolocation of IoT devices transmitting short bursts at low power directly to GEO satellites. We further derive the geolocation error in latitudinal and longitudinal directions and calculate the required amount of information to be transmitted to achieve a desired resolution for the position information of the tracked object. For a typical scenario, we find that 35% to 63% of the transmitted bits could be saved, which results in a huge saving of transmit energy of battery powered small devices in the Internet of Remote Things (IoRT).

Given the extreme diffusion of Alzheimer's disease (AD) and Parkinson's disease (PD), the necessity for a solution to early detect neurological symptoms of such diseases strongly arose. According to the medical literature, such early detection can be achieved by exploiting the correlation between PD and AD and some external symptoms: the Essential Tremor (ET) and the number of Eye Blinks (EBs). In this paper we present a prototype of sensored glasses able to detect the presence of ET of the head and to count the number of EBs at the same time. To the best of authors' knowledge this is the first attempt to monitor such external symptoms with a transparent and wearable device without any a-priori training. Numerical results prove the reliability of the proposed approach: the proposed algorithms are able to i) correctly recognize the ET with an overall accuracy above 97% and ii) count the number of EBs with a Root Mean Square Error (RMSE) around 0.4.

Precoding for multibeam satellite systems with full frequency reuse in a multi-user multiple-input multiple-output (MU-MIMO) downlink scenario is addressed. A testbed is developed to perform an over-the-air field trial of zero forcing precoding for the spatial multiplexing of two separate video streams over two co-located geostationary satellites. Commercialoff-the-shelf DVB-S2x receivers in two single-antenna user terminals (UTs) are operated to successfully decode two independent video streams. To this end, particular attention is paid to a comprehensive assessment of the practical synchronization tasks of a precoding based MU-MIMO system. In particular, carrier frequency recovery and carrier phase synchronization in the most challenging multi-satellite scenario with different oscillators in the payloads is performed. An estimation method for channel state information (CSI), i.e. the complex channel coefficients, is also proposed and implemented. The successful video transmission finally constitutes the first field trial of MUMIMO precoding and proves the feasibility of precoding concepts for multibeam satellite systems.

In this paper, a geographical non-orthogonal multiple access based multiuser beamforming (NOMA-BF) scheme is investigated to improve spectral efficiency in multi-beam satellite-based Internet of Things (IoT), where the primary user per beam needs to be timely served with a small targeted data rate while other users per beam are opportunistically served by using the NOMA concept. We first design a novel user scheduling to enhance spectrum efficiency. Then, a multi-layer beamforming (BF) is developed to mitigate inter-beam interference, augment the difference of the effective channel gains of the users, and perform inter-beam power allocation in a separate manner. Additionally, a dynamic intra-beam power allocation policy is conceived to further improve spectrum efficiency, while meeting predefined target data rates of the primary NOMA users. Numerical results show the capability of our proposal.

We apply the concept of spatial multiple-input-multiple-output (MIMO) to co-located satellites and discuss its potential to further increase the capacity of a single geostationary slot. We show that the achievable capacity in fixed satellite services applications strongly depends on the co-location method. To obtain a constantly high MIMO capacity gain, the geometry between the satellites must be maintained, which requires the implementation of a coordinated station-keeping strategy. The impact of satellite positioning errors on the capacity due to inaccuracies of the orbit determination or the thruster system is investigated. Monte Carlo simulations involving two satellites show that, even for a conservative assumption on the satellite positioning accuracy, a capacity increase of at least 1.7 for more than 90% of all observations can be realized compared to a conventional single-input-single-output (SISO) satellite system.

The increasing demand for in-flight connectivity via satellite communications and the use of unmanned aircraft beyond line of sight pose the requirement for additional allocations in the non-exclusive Ka band satellite spectrum. This is to be decided by the International Telecommunications Union at the World Radio Conference 2019. With the terrestrial fixed service being the dominant interference source of the incumbent radio services in the Ka band satellite downlink, we simulate radio frequency interference due to emissions from multiple sources into an aeronautical receiver. Based on a specified reference scenario, we provide first order interference statistics for different flight altitudes. To this end, we approximate the sample probability density distributions of exhaustive interference scenario simulations using a log skew normal distribution to provide an analytical expression of probabilities for frequency coordination and system design.

Direct access of small terminals in the Internet of Things (IoT) to geostationary satellites may provide wide coverage and almost 100% availability for remote locations without access to terrestrial networks. However, existing waveforms and IoT solutions do not close the link to the geostationary earth orbit (GEO) for massively deployed small devices. We present a novel modulation and signaling scheme based on chirp-spread spectrum (CSS) that enables reliable transmission at ultra low bit-rate. The proposed structure for the transmit signal applies unipolar codes in a novel manner, which allows random multiple access to a common channel for a large number of devices. Further, the transmit signal is designed to allow robust signal detection with low effort even at high carrier frequency offsets. We propose a system concept for the receiver including synchronization, and provide the results of extensive simulations carried out on system and link levels. As a result, we demonstrate that the proposed scheme, referred to as unipolar-coded CSS (UCSS), enables true random multiple access for a very large number of devices, closing the challenging link between IoT devices and satellites in the GEO even at high carrier frequencies from C-band to Ka-Band.

Future high throughput satellites (HTS) aim at providing ultra high data rates with flexible payloads. The multiport amplifier (MPA) is an important flexible payload technology that provides efficient use and allocation of the radio frequency (RF) power. However, several practical limitations affect their performance. This paper outlines general design principles and mathematical models for the MPAs to highlight different practical scenarios which can lead to system performance degradation. Two major issues detailed in this paper are the hardware imperfections in implementing input/output-hybrid Butler matrices (INET/ONET) and the non-linear effects of high power amplifiers (HPAs). The paper also presents a two-step adaptive technique to improve the overall MPA performance, where in the first step a novel onboard compensation technique for the imperfect INET/ONET is presented. Furthermore, the high power amplifiers (HPAs) in the MPA are digitally predistorted to reduce the intermodulation noise and spectral regrowth in the second step. Simulation results indicate that by implementing the proposed two-step solution, there is not only a gain in the bit error ratio (BER) performance, but also in system robustness against hardware imperfections and aging effects due to the technique's adaptive nature.

The development of next-generation high throughput satellite systems raises major design challenges, especially for their uplink. To supply data to a large number of user beams, tens of feeder links in the Q/V-band must be deployed. Moreover, transmit diversity is required to cope with the strong rain fades experienced in this higher range of frequencies. To address these issues, a multiple-input-multiple-output (MIMO) feeder link architecture is introduced. By doubling the amount of supported data traffic per link, this solution enables a reduction of the number of spatially separated feeder beams required to operate the system. As a consequence, larger angular separations can be realized to lower the inter-beam interference. Besides, a better robustness against weather impairments is ensured. Using a carrier to interference plus noise ratio measure, an outage analysis of a MIMO-based smart gateway architecture with 15 active MIMO feeder links and 1 redundant link proves the superiority of this novel approach.

In communication satellites, high power amplifiers (HPAs) are generally driven into the nonlinear region to improve their power efficiency. Due to the emergence of the onboard processors (OBPs), digital predistortion (DPD) can now be directly implemented in the transponder to improve the power efficiency of the HPA while maintaining its linearity. However, in DPD implementation, the computational complexity of the DPD coefficients estimation is a key performance metric, especially since the contemporary OBPs have extremely limited processing capabilities. This paper presents and discusses a possible implementation of low-effort sample-based DPD solutions and compares their performance against the state-of-the-art blockbased computationally exhaustive DPD techniques. The presented simulation results show that the sample-based methods exhibit a similar carrier to noise ratio gain and intermodulation noise reduction at a much lower computational and hardware cost.

Aggressive frequency reuse in the forward link of multibeam satellite communication causes considerable inter-beam interference. It is possible to use such inter-beam interference in a beneficial way by employing multiple multibeam reflectors. The reflectors and the single antenna receivers on Earth form a multi-user multiple-input multiple-output system. In order to enable simultaneous data transmissions to multiple users inside the coverage zone, zero forcing (ZF) precoding is used. Aiming for maximizing the fairness between the receivers while applying a realistic per-antenna power constraint, the ZF precoding matrix is calculated by the help of generalized inverses. In this paper a low-complexity scheduling algorithm is proposed to cluster all customers in the service area into groups ensuring a high multiplexing gain within the individual groups. The novel scheme outperforms contemporary four color frequency and polarization reuse schemes by a factor of 2.5 in terms of throughput.

A particular problem in satellite communications is the estimation of the current operating point of a bent-pipe transponder. Various special effects aggravate this estimation problem, among which the capture effect, gain compression, unknown attenuation in the transmission channel, or noisy received signals are the most prominent. In most practical cases, operators desire a fully blind estimator that is nevertheless able to cope with these unwanted impairments. We provide the theoretical background and further results on a novel estimator based on signal statistics that enables accurate operating point estimation in multicarrier operation as well as in single carrier mode with higher-order modulation. In this paper we focus on three basic use cases for our estimator, and we discuss results on the estimation accuracy.

We present a novel linear minimum-mean-squared-error (MMSE) joint precoding and equalization technique for a downlink (DL) massive multiple-input-multiple-output (MIMO) scenario. To lower the power consumption, the computational and the design complexity, 1-bit digital to analog converters (DACs) and analog to digital converters (ADCs) are used at the transmitter and at the receiver antennas. These economical and computational gains come at the cost of a performance loss which can be recovered by the large number of antennas deployed at the base station and by implementing appropriate precoders and equalizers which can mitigate the coarse quantization effects. The proposed technique implements a two-stage digital and an analog precoder with a digital equalizer, both of which take into account the effects of the 1-bit quantizers. The simulation results indicate the superiority of the novel joint precoder and equalizer design to the previously proposed linear precoders and equalizers not only in terms of the uncoded bit error rate (BER) performance but also in terms of the robustness to errors in the estimation of channel state information at the transmitter (CSIT).

If multiple-input multiple-output (MIMO) satellite communications (SATCOM) systems use spatial multiplexing instead of polarization multiplexing, the channel capacity depends on the geometrical conditions of the antenna setup. This theoretical result is proven and confirmed for the first time by a true-MIMO measurement campaign. We utilize two Ku-band satellites and a ground station with two antennas as a 2 × 2 MIMO SATCOM probing system. The channel capacity is estimated and compared to its theoretical prediction. Moreover, an error analysis is provided for the capacity estimation.

Multiple-input multiple-output (MIMO) satellite systems are currently under intensive research due to their enormous potential to improve the link capacity. The key to achieve high multiplexing gains are the fine tuned phase relations inside the MIMO channel matrix. These relations are realized by a smart placement of the ground station antennas. However, the signal phase of a space- earth link is influenced by atmospheric distortions. Therefore measurements of the signal phase from related field campaigns are analyzed and examined regarding their relevance for the capacity prediction of real MIMO satellite links. Further, the impact of these phase distortions with respect to the resulting ergodic capacity and to the complementary cumulative distribution function of the channel capacity is investigated. Simulations point out only minor performance losses under the expectable conditions. Nevertheless, for a reliable forecast of MIMO satellite communication systems, additional measurements are needed.

In contrast to present space communication systems in the Ultra-High-Frequency (UHF) band, like military communications or communication to space crafts, present and upcoming animal tracking systems introduce a novel UHF propagation channel with a larger bandwidth, low-gain antennas and new challenging propagation scenarios like for example the forest. The ground reflection, as a phenomenon of wave propagation, is relevant in this scenario. Unlike other multipath components with larger excess delays or lower power, the ground reflection cannot be equalized; even not at large system bandwidths. In this paper, the relevance of the ground reflection for animal tracking systems is proven by measurement and simulation. Further results from a measurement campaign are presented, where the forest as a novel scenario is included. A statistical model is provided to predict the received signal power, and to estimate the required additional fading margin to close the link of UHF animal tracking systems in the presence of a reflected signal from the ground.

We present a novel interferometer for the accurate measurement of the channel transfer matrix of future multiple-input multiple-output (MIMO) satellite communication (SATCOM) systems. The capacity of such a SATCOM system heavily depends on the phase relations inside the channel matrix. Above 10 GHz, these phase relations are affected and determined by tropospheric perturbations when the signal passes through the atmosphere. To measure the transfer matrix of the signal phase with sufficient accuracy, the interferometer must provide a fine temporal resolution. The paper shows a low-cost measurement approach at Ku-band with remarkable precision as well as the first results of the measurement campaign.

Due to the steady increase of satellite networks in the geostationary arc, operators and governments must take measures to ensure that each network can operate without being interfered by adjacent satellite networks. Usually this is achieved by strict regulation of the allowed power spectral density within the shared operating spectrum. Unfortunately, limiting the allowed transmit power ceteris paribus manifests in limited data rates, especially if terminals with small apertures are used. In this paper we will show that the recently proposed Multiple Input-Multiple Output (MIMO) technology for communication satellite systems is a convenient concept to mitigate data rate limitations induced by adjacent satellite interference (ASI). Given a fixed data rate required by the end user, MIMO systems are superior over conventional Single Input - Single Output (SISO) systems because they work at less satellite transmit power and, therefore, enable more narrow satellite spacing or smaller ground terminal dish sizes without violating negotiated ASI limits.

A multiple-input multiple-output (MIMO) satellite communications system for fixed-satellite services (FSS) is considered. The MIMO Line-of-Sight (LOS) satellite channel is optimized to achieve maximum spectral efficiency. This requires an orthogonal MIMO channel matrix, ending up with large antenna spacing of the ground terminal antennas. As the main drawback, considerable propagation delays between the MIMO paths are observed, and the MIMO signal sub-streams interfere asynchronously in the order of several tens or hundreds of a symbol duration at the receiver. To cope with these delays, we propose a system architecture that uses a sufficiently large guard-interval or cyclic prefix between successive data blocks. The delay equalization at the receiver is then performed by a zero-forcing frequency domain equalizer for single-carrier transmission (SC-FDE). Thanks to the orthogonality of the considered MIMO channel, the SC-FDE architecture achieves even perfect spatial equalization of the multiplexed signal streams at considerably low implementation effort. The capacity reduction caused by the guard-interval is, moreover, mitigated by long data blocks, which can be used because of the long channel coherence times in FSS applications. The system concept reveals superior BER and transinformation performance, which is verified through fair comparison with current single-input single-output (SISO) systems. If the channel orthogonality is violated through narrow antenna spacing, the system performance degrades dramatically.

The bandwidth efficiency of Multiple Input - Multiple Output (MIMO) channels with different antenna arrays is analyzed. MIMO channels with a strong and unobstructed line-of-sight (LOS) signal component are considered, as it is the case in indoor in-room scenarios. The bandwidth efficiency of such channels is strongly dependent upon the applied antenna array and its orientation. Simulations of the pure LOS channel without multipath components are carried out to demonstrate this effect. So called polyhedron antenna arrays with antenna elements mounted on the faces of a regular polyhedron as well as the MIMO Cube deliver a bandwidth efficiency that is almost invariant from rotations of the antenna arrays. The measurement results verify this result. Polyhedron arrays appear to be a good alternative for MIMO systems, as the measured bandwidth efficiency of a polyhedron array is comparable to this of an uniform linear array (ULA), while the standard deviation is reduced to a large extend.

We investigate the impact of atmospheric impairments on the theoretical bandwidth efficiency of Multiple-Input Multiple-Output (MIMO) geostationary satellite links which are shaped to optimize the channel bandwidth efficiency. We analyze the impairments caused by precipitation, since this is the most severe atmospheric effect causing capacity degradations. By theory, the MIMO channel capacity is strongly affected by signal attenuation as well as signal phase shifts that might reduce the number and strength of spatial subchannels (eigenmodes). We will show, however, that the characteristics of the phase disturbances prevent a loss of capacity. Regarding the additional attenuation, which the signals may encounter passing through the troposphere, we will quantify outage values for several levels of link capacity degradation. Although a loss of capacity cannot be avoided in total, it still turns out that MIMO systems outperform conventional Single-Input Single-Output (SISO) designs in terms of reliability. Even in the presence of atmospheric perturbations, MIMO systems still provide enormous capacity gains and vast reliability improvements. Thus, the MIMO satellite systems presented are perfectly suited to establish the backbone network of future broadband wireless standards (e.g. DVB-SH), supporting high data rates for a variety of worldwide services.

The bandwidth efficiency of Multiple Input - Multiple Output (MIMO) channels is analyzed for point-to-point (P2P) and relay channels. The focus lies on channels with a strong and unobstructed line-of-sight (LOS) signal component between transmitter (Tx) and receiver (Rx), as it is the case in indoor in-room scenarios. The bandwidth efficiency of the resulting correlated P2P MIMO channel is strongly dependent upon the geometrical antenna setup. Especially the angle of arrival (AOA) and the inter-array antenna spacing of uniform linear arrays (ULAs) influence the bandwidth efficiency. Both influences are minimized by the use of distributed simple amplify-and-forward relay stations, while the resulting relay MIMO channel is correlated. In the relay case, the total transmit power spent at the Tx and the relay is limited to the transmit power of the Tx in the P2P case for a fair comparison. Relay stations are capable to enhance the bandwidth efficiency of the pure LOS MIMO channels, while the high bandwidth efficiency of channels with LOS and non line-of-sight (NLOS) signal components is not further increased in the considered scenario.

MIMO satellite links have recently attracted a high interest with respect to possible link capacity enhancements. In it has been shown that especially in Line-of-Sight (LOS) satellite channels maximum multiplexing gain can be achieved via the construction of orthogonal channels by means of the geometrical arrangement of the ground terminal antennae in relation to the antennae in orbit. Based on these theoretical results, we present practically relevant design and configuration examples for satellite communication systems, involving transparent pay loads for the first time. Thus, we significantly extend the results, that have been limited to regenerative payloads. The examples cover multiple-satellite and single-satellite MIMO scenarios. The assets and drawbacks of the applications are investigated, especially highlighting system-inherent design uncertainties.

We propose a fixed-effort MIMO decoder for frequency selective indoor channels that are characterized by strong line-of-sight (LOS) components. Contrarily to the maximum likelihood (ML) approach, where all possible hypotheses are investigated by the metrics calculation, the proposed MIMO detector performs the search over a reduced set of candidates. This search set contains a reduced but representative set of hypotheses around the linear solution obtained at the first detection stage. The candidates are selected according to pre-computed search probabilities. A decision feedback equalizer (DFE) is applied in order to remove the effect of the inter symbol interferences (ISI) caused by the channel dispersion. The method provides a near ML performance using a fixed computational effort determined by the hardware resources. The proposed detector also shows a significant complexity reduction compared to popular MIMO detectors such as the V-BLAST and the sphere decoder. Moreover, the proposed detector provides a soft output information for each transmitted bit, using the pre-selected candidates from the reduced search set which presents a promising aspect for the coded transmission.

Different multiple input - multiple output (MIMO) channel models are analyzed with regard to the indoor line-of-sight (LOS) MIMO channel. In the literature this channel is proven to achieve high capacities while being highly correlated. The modeling results from physical as well as analytical models are compared with measured channels, showing that none of the established models is exactly suitable for the considered indoor LOS MIMO channel. However, there is a promising approach that applies an extended Saleh model in conjunction with the physically correct spherical wave propagation. Although in its current state this basic approach cannot be regarded as a complete MIMO channel model, at least it provides an adequate origin for the correct prediction of MIMO capacities in different types of LOS channels. This is due to the fact, that the crucial prerequisites for an appropriate LOS MIMO channel model, which are by name the application of the physically correct spherical wave propagation, the correct modeling of the high correlation in LOS channels and the inclusion of the geometrical antenna setup, are regarded correctly. Contrarily, these prerequisites are included in none of the current models that are widely accepted in MIMO radio communications nowadays. The proof of this statement using measured data is a major objective of this paper.

A novel strategy of precalculating potential MIMO spectral efficiencies of correlated channels based on both, measured as well as appropriately modeled SISO channel impulse responses is presented. Besides capacity prediction, the model is capable of comprising the physical nature of the channel in form of its frequency response. The method is applied to indoor MIMO channels where the correlation is introduced mainly by a strong LOS signal component coinciding with low mobility. A spherical wave model is applied and the distributions of angle of arrival and angle of departure turn out to be important modeling parameters. The modeled MIMO capacities are compared to measured capacity records for verification, proving high accuracy.

This paper provides an approach to reach a near maximum likelihood performance, for MIMO systems, with a strongly reduced computational effort. This method is based on a two-step detection. The first detection step will be performed by using a MMSE equalizer and a subsequent decision unit The second step is a reduced search (RS) algorithm, that is applied only in a neighborhood of the detected symbols of the first step. For complexity reasons only the least reliable symbols are processed by the RS algorithm. The simulation results show that this MMSE RS detector outperforms the MMSE V-BLAST detector. It provides an improved performance using the same complexity.

A novel strategy for the modeling of indoor MIMO channels based on a spatial extension of appropriate SISO channel models is presented. The approach enables a precalculation of potential MIMO spectral efficiencies within a particular environment from the SISO channel information while taking into account the correlation of the MIMO channel. The objective measure is given by the spatial probability distribution of the MIMO capacity which is to be predicted correctly. The method is exemplified by Saleh's popular SISO indoor channel model. However, the approach is not limited to this SISO model. In order to practically verify the method, firstly, the key parameters for the SISO model are derived from measured data, before the extension to the MIMO channel model is performed. Finally, the spatial cumulative distribution function, which is predicted by the model is compared to its counterpart which was derived using a fast MIMO radio channel sounder. In the measurements a strong line-of-sight (LOS) signal component was always present resulting in correlated entries within the MIMO channel matrix. For the accurate capacity modeling in such correlated channels, the characterization of the LOS signal part by a spherical wave model is a crucial prerequisite.

The indoor MIMO line-of-sight (LOS) channel in theory strongly depends on the geometrical arrangement and spacing of the antennas at both, the transmitter as well as the receiver. Recently, theoretical directives have been presented [1] which enable the user to achieve high-rank LOS channels for linear antenna arrays which are oriented broadside to each other. The authors focus on proper phase angle relations within the entries of the channel transfer matrix, while neglecting the channel path loss in a first approach, and they consider the antenna spacings as the major degree of freedom for optimization. Contrarily, in practical indoor scenarios we consider the antenna array spacings to be fixed at the base station as well as the mobile unit and therefore they can be optimized for one particular transmitter-receiver distance at most. Furthermore, the free space path loss has to be taken into account as it causes huge SNR variations across an indoor environment. Thus, in this paper we try to apply the results in [1] to an exemplary real-world scenario observing the spatial capacity distribution as well as their variation. This way, we endorse the results in [1] by further design hints for practical MIMO systems using linear antenna arrays of arbitrary positioning.

We present broadband capacity snapshots as well as grid measurements derived with a fast 5times5 MIMO channelsounder in a typical, large-scale, non-mobile, in-room office scenario where we focus on line-of-sight (LOS) transmission channels. The accessible MIMO capacity is compared to its theoretic counterpart which would have been obtained if only the LOS signal without any reflections was considered. Our premise is to enable the user of quantifying the LOS signal's impact on the overall channel capacity for the particular scenario and coinciding to demonstrate the LOS's beneficial effect for the capacity. For a huge amount the beneficial effect of the LOS signal has to be ascribed to its receive signal power increase, an advantage which can hardly be balanced by any measures in the non-LOS case. The results generally indicate the overall capacity staying fairly high even for single channel matrix realizations and widely independent from the current geometric antenna assembly. Besides, strong variations over frequency are observed. These variations are shown to be slightly reducible by rising the number of antennas, but more efficient, larger bandwidths seem to be an appropriate measure for stabilizing the overall channel capacity per bandwidth unit