Long Range Wide Area Networks (LoRaWANs) have become a popular candidate for energy efficient networks like the Internet of Things (IoT). For the connection of remote regions, satellites in Low Earth Orbit (LEO) can be used to support the terrestrial LoRaWAN. LEO enables transmission from IoT devices with a very low transmit power. However, it also leads to high Doppler shifts as well as high Doppler rates. Both effects deteriorate the Long Range (LoRa) communications performance tremendously. Whereas new LoRa technologies are developed for systems with high Doppler effects, they are not backward compatible, i.e., they cannot be used for LoRa sensors which have already been deployed. In this paper, we propose a Doppler rate mitigation method which reduces these negative effects by subtracting an estimated Symbol Error (SE). Here, estimation is based on an adaptive linear regression method exploiting all LoRa symbols of a packet, compared to state-of-the-art techniques whose linear regression approachs are only using preamble symbols. Simulation results show that the proposed method tremendously outperforms state-of-the-art techniques, especially at high Doppler rates.
Reconfigurable intelligent surface (RIS) is a promising technology to enhance the spectral and energy efficiency in B5G/6G systems. Channel estimation in RIS-aided systems is quite challenging due to the passive architecture of the RIS. Since RIS consists of a large number of reflecting elements, we need many phase shift allocations during the channel estimation phase to estimate the RIS-associated channels perfectly. In the absence of a sufficient number of pilot or phase shift sequences during the training phase, we get imperfect channel state information (CSI), which can significantly degrade the overall performance of the system. In this work, we analyse the effects of limited pilot and phase shift sequences on the asymptotic performance of the RIS-aided systems. We also optimise the achievable sum-rate of the system in the absence of full pilot and phase shift sequences.
Unmanned aerial vehicle (UAV)-aided communications may suffer from the coexistence with existing network infrastructure and the spectrum scarcity. Underlay cognitive radio technology should be employed to manage the secondary UAV-aided networks with the existing primary networks using the same frequency spectrum, where the interference to the primary network should be bounded. In this paper, we focus on the problem of multi-UAV-assisted underlay cognitive radio for multiple secondary users (SUs) and primary users (PUs). We establish an optimization problem to maximize the minimum throughput among SUs with respect to multi-UAV deployment locations, power and service ratio allocation. The problem is highly intractable due to its mixed-integer and non-convex nature. The problem is solved by decomposing it into two nested optimization problems. The inner problem involves joint power and service ratio allocation given the deployment location and UAV-SU allocation, which we transform equivalently into a convex optimization problem. The outer problem determines the multi-UAV deployment locations and UAV-SU allocation, solved via a metaheuristic method. Via this decomposition with the inner problem optimally solvable in polynomial time by a convex optimization solver, the search space of the metaheuristic algorithm is drastically reduced, resulting in an efficient nearoptimal algorithm for the complex problem. Numerical results demonstrate that the proposed approach achieves significant throughput improvement compared to baseline methods.
Combining sensing and communication into a single system allows the integration of radar sensors mounted on locally installed road side units into future intelligent transportation systems. These units have great potential to improve safety in dense intersection scenarios. However, this combined functionality is limited due to their potential interference. This paper investigates the influences of antenna characteristics on sensing and communication performance in crossing scenarios at 77 GHz. Different antenna characteristics are compared in ray-tracing simulations. The radar sensing performance is evaluated based on the maximum peak detection in the range-Doppler map, while the communication is evaluated based on the channel characteristics. The different antenna types achieve either a higher detection power in the angular region or a higher antenna focus. The communication is compared with respect to the root mean square delay spread and the minimum timing delay for an interferencefree frequency-modulated continuous wave (FMCW) sensing. The power of the line-of-sight path between the radar-equipped road side units varies over 20 dB between the different antennas. The alignment with each other results in even higher gains and losses. The results show that coordinating the different RSUs with an additional time or frequency scheduling is necessary. In the future, the intersection scene will be improved with more road users to investigate the antenna characteristics' impacts further.
This paper provides a solution for the joint activity detection and channel estimation (JADCE) problem in grant-free access with correlated device activity patterns. In particular, we consider a massive machine-type communications (mMTC) network operating in an event-triggered traffic mode. To this end, to encode the prior information about the correlated sparse activity pattern, the paper proposes a first-order Markov chain coupled with a sparsity-promoting spike and slab to capture the sparse and correlated activity pattern. Furthermore, we drive a hierarchical Bayesian parameter estimation using Markov chain Monte Carlo (MCMC) sampling to provide an efficient solution to the JADCE problem. Numerical results highlight improved activity detection accuracy and channel estimation quality performance.
In this paper, we introduce a novel time domain correlation based channel sounder that operates at 485 GHz. The channel sounder targets the Y-band ($330 \text{GHz}-500 \text{GHz}$) and covers a center frequency up to 500 GHz. The setup has been validated in the laboratory for conducted and over-the-air measurements. The conducted measurements report a dynamic range of around 80 dB without spurious peaks, and a linear behavior between added attenuation and dynamic range with constant relative noise floor. The over-the-air measurements report a match of the line-of-sight path's propagation length and normalized received power.
This paper outlines an advanced characterization procedure for a D-band dielectric lens made of polytetrafluoroethylene (PTFE), utilizing a WR6 waveguide probe as the feeding antenna. The proposed measurement setup is designed to effectively measure the radiation pattern for various source positions relative to the lens with a precision of $5 \mu\mathrm{m}$, enabling a comprehensive analysis of individual array elements in conjunction with the lens, for which it was measured a gain of 15.6 dBi at 150 GHz. By measuring complex scattering parameters at each position, the setup emulates a phased array configuration, and the coupling matrix is integrated from previously acquired simulated data. The emulated radiation patterns derived from the measurement results demonstrate strong correlation with fullwave electromagnetic simulations of the complete array, both for uniform and for linear-phase-shifted excitations. These findings validate the effectiveness of the technique for conducting arrayintegrated lens measurements, thereby contributing valuable insights for future antenna and lens design in high-frequency applications.
Phase-modulated continuous waveform (PMCW) has attracted wide attention for integrated sensing and communications (ISAC). Aiming at the drawback of limited communications spectrum efficiency, a code-orthogonal PMCW (CO-PMCW) transmission scheme was proposed, which improves the data rate by the simultaneous transmission of radar and communication signals while raising the problem of mutual interference (MI) between them. This paper introduces the design strategy of the CO-PMCW-based multiple-input and multiple-output (MIMO) ISAC system with customized digital beamforming for MI suppression. The simulation results demonstrate the applicability of the designed system and its merits and demerits compared to PMCW.
This paper proposes a beam training-based hybrid precoding algorithm for holographic multiple-input multiple-output (HMIMO)-aided multi-user communication systems with low overhead and complexity. Unlike most of the works considering the precoding design based on perfect full channel state information (CSI), we design the analog precoding of HMIMO via beam training. Then, we estimate the low-dimensional effective CSI with the fixed analog precoding under the least-square criterion. Finally, utilizing the weighted minimum mean-square error (WMMSE) method, the digital precoding is designed in closed form using the estimated effective CSI, under the per-radio frequency (RF) chain power constraints. Simulation results demonstrate the effectiveness of the proposed algorithm compared with the conventional design with full CSI.
The integration of extremely large-scale multipleinput multiple-output (XL-MIMO) and ultra wideband (UWB) communications is essential to address the escalating demand for high data rates in sixth generation (6 G) wireless networks. However, the expansion of antenna array apertures and/or signal bandwidth introduces the spatial-wideband effect, resulting in frequency-dependent propagation characteristics and the manifestation of the beam squint phenomenon. To mitigate beam squint, true-time delay (TTD) elements have been proposed as promising hardware solutions. Despite this, most existing TTD-based precoding architectures assume idealized conditions, such as unbounded delay ranges and infinite resolution, which are impractical for real-world implementation. In this context, this paper investigates the performance degradation caused by practical TTD constraints. Simulation results demonstrate that under realistic hardware limitations and a finite number of TTD elements, conventional precoding schemes are insufficient to suppress beam squint in XL-MIMO systems as the antenna count scales. These findings underscore the necessity for hardwareaware TTD precoding designs that can effectively accommodate the constraints of practical implementations.
We present a simple modification of binary Modulation On Conjugate-reciprocal Zeros (MOCZ) which allows to combine the Direct Zero Testing decoder with a soft-input decoder. This decoder allows a straightforward combination of binary MOCZ with standard channel codes for practically relevant sequence lengths. Simulation results indicate that in the absence of any channel knowledge, good performance at realistic SNR values is achievable.
In this work, a Near-field Fed Reflective Intelligent Surface (NFED-RIS) System is designed and evaluated in preparation of the usage as an alternative beamforming system. The conceptual architecture of this smart antenna system has been developed and validated using a system model presented in this paper. Subsequently, a dual-polarized $8 \times 8$ RIS array and $2 \times 2$ Feeder array within the centimeter-wave band were designed and validated through an electromagnetic simulation prior to fabrication. The NFED-RIS system, which is based on these two patch arrays, will be experimentally evaluated and compared to the results of electromagnetic simulations, including potential deviations caused by imperfections not captured in the simulation model. Consequently, the RIS is regarded as a passive reflect array antenna that can be utilized as an analog beamformer. This is achieved by dynamically reflecting incident waves from the Feeder, resulting in steerable beams in the far field. The distance between the two arrays is critical to ensuring optimal system performance. One of the objectives of the experiments is to identify the optimal distance between RIS and Feeder through the analysis of the near field channel (S21 over-the-air measurements) across all antenna elements, excluding the RIS phase shifters. In addition to delivering deep insights and design trade-offs of the NFED-RIS system, the measurement provides the magnitude and phase distribution at the optimal distance on the RIS, which is crucial for determining the beamforming steering vectors for future far-field experiments.
This paper investigates the optimization of movable antenna (MA) arrays for integrated sensing and communications (ICAS) in downlink multiple-input single-output (MISO) systems. We propose an idealized beamsteering model that enables flexible configuration of antenna positions to enhance the signal-to-noise ratio (SNR) for both communication and radar sensing tasks. The study begins with analytical solutions for optimal antenna spacing in simplified scenarios involving one or two users and a radar target, demonstrating the advantages of controlled antenna aliasing and separate beamforming. For more complex scenarios with multiple users and targets, we propose a suboptimal yet efficient two-stage heuristic combining antenna distance optimization with weighted MMSE beamforming and power allocation. The results show that movable antennas can significantly enlarge the achievable SNR region and improve capacity, especially in cases with conflicting beamforming objectives. Numerical simulations validate the proposed methods and highlight the potential of MA technology for future 6 G integrated sensing and communication systems.
This paper analyses the achievable rates of a geostationary (GEO) satellite system equipped with a phased array-fed reflector. Them aim is to achieve efficient spatial beamforming adaptability to traffic demands, which in the recent GEO satellite launches based on digitally transparent payloads is limited to programmable beams (i.e., beam-hopping) or applications with limited bandwidth. Low-Earth orbit (LEO) systems rely on direct radiating antenna (DRA) arrays to implement spatial reconfigurability, but due to the larger path loss, GEO satellites require a large number of antennas, which impacts the feeder link capacity and satellite mass and power. In this case, a relevant compromise solution is to consider the proposed phased array-fed reflectors that combine the adaptive beamforming capabilities of the feeding array with the reflector gain. We analyze this payload configuration considering its attainable rates, and analyzing the different configuration trade-offs related to the focal distance and the number of antennas in the feeding array. Numerical results show the design principles of this next-generation satellite payload.
The rapid deployment of non-geostationary satellite orbit (NGSO) systems, which are fundamental for non-terrestrial networks (NTN) and 6G services, and which use spectrum allocated to the fixed-satellite service (FSS), complicate the coexistence with other FSS networks and systems having frequency overlap. Frequency bands used by broadband FSS systems, like Ku-, Ka-, and Q/V-band, are mainly subject to equivalent power flux-density (EPFD) limits to protect GSO systems. Those limits are based on the conservative assumption that NGSO and GSO paths are uncorrelated, considering the conservative approach of clear-sky for the interfering non-GSO path and rain for the victim GSO path. However, no existing models quantify the correlation between the two Earth-to-space paths. Our study quantifies the correlation as a function of topocentric angular separation between the two Earth-to-space paths, employing Pearson's correlation coefficient as a metric, for the Ka-band. The results reveal characteristic behaviors of rain fade correlation that depend on geometry and propagation conditions. Building on these findings, the potential for simplified models to approximate spatial correlation effects to reduce computational complexity while retaining physical accuracy is discussed. The presented work, focusses solely on the Ka-band and contributes to ongoing efforts to enable more reliable and spectrum-efficient design and operation of future multiorbit satellite networks.
Precoding for multiple-input multiple-output orthogonal frequency division multiplexing systems is often based on a per-subcarrier singular value decomposition, where phase smoothing is applied to the singular vectors that form the transmit beamformers. We show that such a smooth solution can ideally be based on an analytic singular value decomposition, but for estimated channel matrices is beset by challenges that deny a smooth or even continuous evolution of singular vectors with frequency. We show how such problems can be bypassed by admitting complex-valued singular values or fractional delays, and by exploiting a method analogous to the analytic eigenvalue decomposition to approximate ground truth analytic singular vectors from estimated channel matrices. We present examples and demonstrate some of the capabilities of a proposed algorithm through simulations.
Due to increasing relative bandwidths and antenna array sizes, beam squinting is one of the significant challenges that wideband mobile communications systems will face. Although systems employing a true-time delay (TTD) per antenna element could resolve the problem, this is unfortunately not a satisfactory solution as both the digital and analog implementations of TTDs are too expensive w.r.t. power consumption or hardware complexity. Instead, in this work, we extend a recently proposed architecture combining phased subarrays with digitally implemented discrete TTDs to continuous TTDs instead. We further provide a closed-form performance approximation, which is also a lower bound for the average beamforming gain. Our numerical results demonstrate that the proposed design offers a good trade-off regarding hardware complexity and beam squint mitigation.
Precise clock synchronization is essential in modern wireless sensor networks (WSNs) and plays a critical role in emerging Integrated Sensing and Communication (ISAC) systems. In ISAC, accurate timing alignment is vital to enable simultaneous sensing and communication functionalities with high efficiency and reliability. Global Navigation Satellite Systems (GNSS)-based methods face limitations in indoor or GNSS-denied environments and may not provide the ultrahigh precision required for applications such as time-based localization techniques. To overcome these challenges, Signals of Opportunity (SoO) offer a flexible and highly accurate alternative for synchronization. Nonetheless, this approach increases the data rate demands on network links since SoO signals have to be exchanged between base stations. In this work, we evaluate both lossless and lossy compression algorithms to reduce the data load. While lossless methods deliver good performance, lossy algorithms can achieve substantially higher compression rates with only minor reductions in synchronization accuracy. Our results demonstrate that a compression ratio of approximately five is reachable with acceptable loss in time and frequency synchronization precision.
This paper investigates a secure cell-free integrated sensing and communication (ISAC) system designed to simultaneously localize a potential eavesdropper (Eve) and ensure secure communication for legitimate user equipment (UEs). Unlike existing solutions that focus primarily on direction estimation, a distributed architecture employs multiple access points (APs) that collaboratively transmit communication signals and omnidirectional sensing signals for localization. We present analytical closed-form expressions for the signal-to-interference-plus-noise ratios (SINRs) at the legitimate UEs and Eve, facilitating a theoretical evaluation of the system's secrecy spectral efficiency (SSE). Furthermore, we derive a tractable closed-form expression for the localization SINR after matched filtering and subsequently develop the corresponding Cramér-Rao lower bound (CRLB) for the received signal strength (RSS)-based localization, which is validated through Monte-Carlo simulations using the GaussNewton method. To optimally enhance the communication security performance and sensing accuracy, we formulate and solve an optimization problem, allocating power subject to a total transmit power and localization SINR constraints. Numerical results demonstrate the effectiveness of the proposed approach, highlighting significant improvements in both the secure communication performance and localization accuracy within cell-free ISAC architectures.
To ensure ubiquitous coverage for different scenarios of broadband and narrowband connectivity, deployment and integration of Non-Terrestrial Networks in a seamless way is quintessential. This requires optimization of handover management in dual mobility scenarios with hybrid terrestrial and non-terrestrial infrastructure. Many solutions that have been researched and investigated so far make some assumptions about the presence of intra-RAN and inter-RAN interfaces. The paper here presents an overview of the available solutions in both 3GPP and O-RAN specifications with selected case studies involving both terrestrial and non-terrestrial networks. Some of the evaluations involving AI-assisted handover are also illustrated for selected scenarios.
