Search Results (114)

An analog joint source-channel coding (AJSCC) based on Shannon–Kotel’nikov (S-K) mapping transmitting discrete-time encoded samples in orthogonal frequency division multiplexing (OFDM) systems over wireless channel has exhibited excellent performance. However, the phenomenon of carrier frequency offset (CFO) caused by the frequency mismatch between the transmitter’s and receiver’s local oscillators often exists in actual scenarios; thus, in this paper the performance of AJSCC-OFDM with CFO is analyzed and the S-K mapping is optimized. A joint optimization strategy is developed to maximize the signal-to-distortion ratio (SDR) subject to CFO constraints. Considering that the optimized AJSCC-OFDM strategies will change the amplitude distribution of encoded symbol, the peak-to-average power ratio (PAPR) characteristics under different AJSCC parameters are also analyzed. Full article

The Lunar Augmented Navigation Service (LANS) is the lunar equivalent of GNSS for future lunar explorations. It offers users accurate position, navigation, and timing (PNT) capabilities on and around the Moon. The Augmented Forward Signal (AFS) is a standardized signal structure for LANS, and its recommended standard was published online on 7 February 2025. This work presents software-defined radio (SDR) implementations of the LANS AFS simulator and receiver, which were rapidly developed within a month of the signal specification release. Based on open-source GNSS software, including GPS-SDR-SIM and Pocket SDR, our system provides a valuable platform for future algorithm research and hardware-in-the-loop testing. The receiver can operate on embedded platforms, such as the Raspberry Pi 5, in real-time. This feature makes it suitable for lunar surface applications, where conventional PC-based SDR systems are impractical due to their size, weight, and power requirements. Our approach demonstrates how open-source SDR frameworks can be rapidly applied to emerging satellite navigation signals, even for extraterrestrial PNT applications. Full article

This paper presents a novel, four-port, rectangular microstrip, inset-feed multiple-input and multiple-output (MIMO) antenna array, enhanced with metamaterials for improved gain and isolation, specifically designed for multi-operator 5G open radio access network (ORAN)-based indoor software-defined radio (SDR) applications. ORAN is an open-source interoperable framework for radio access networks (RANs), while SDR refers to a radio communication system where functions are implemented via software on a programmable platform. A 3 × 3 metamaterial (MTM) superstrate is placed above the MIMO antenna array to improve gain and reduce the mutual coupling of MIMO. The proposed MIMO antenna operates over a 300 MHz bandwidth (3.5–3.8 GHz), enabling shared infrastructure for multiple operators. The antenna’s dimensions are 75 × 75 × 18.2 mm³. The antenna possesses a reduced mutual coupling less than −30 dB and a 3.5 dB enhancement in gain with the help of a novel 3 × 3 MTM superstrate 15 mm above the radiating MIMO elements. A performance evaluation based on simulated results and lab measurements demonstrates the promising value of key MIMO metrics such as a low envelope correlation coefficient (ECC) < 0.002, diversity gain (DG) ~10 dB, total active reflection coefficient (TARC) < −10 dB, and channel capacity loss (CCL) < 0.2 bits/sec/Hz. Real-world testing of the proposed antenna for ORAN-based sub-6 GHz indoor wireless systems demonstrates a downlink throughput of approximately 200 Mbps, uplink throughput of 80 Mbps, and transmission delays below 80 ms. Additionally, a walk test in an indoor environment with a corresponding floor plan and reference signal received power (RSRP) measurements indicates that most of the coverage area achieves RSRP values exceeding −75 dBm, confirming its suitability for indoor applications. Full article

The identification of vital signs is becoming increasingly important in various applications, including healthcare monitoring, security, smart homes, and locating entrapped persons after disastrous events, most of which are achieved using continuous-wave radars and ultra-wideband systems. Operating frequency and transmission power are important factors to consider when conducting earthquake search and rescue (SAR) operations in urban regions. Poor communication infrastructure can also impede SAR operations. This study proposes a method for vital sign detection using an integrated sensing and communication (ISAC) system where a unified orthogonal frequency division multiplexing (OFDM) signal was adopted, and it is capable of sensing life signs and carrying out communication simultaneously. An ISAC demonstration system based on software-defined radios (SDRs) was initiated to detect respiratory and heartbeat rates while maintaining communication capability in a typical office environment. The specially designed OFDM signals were transmitted, reflected from a human subject, received, and processed to estimate the micro-Doppler effect induced by the breathing and heartbeat of the human in the environment. According to the results, vital signs, including respiration and heartbeat rates, have been accurately detected by post-processing the reflected OFDM signals with a 1 MHz bandwidth, confirmed with conventional contact-based detection approaches. The potential of dual-function capability of OFDM signals for sensing purposes has been verified. The principle and method developed can be applied in wider ISAC systems for search and rescue purposes while maintaining communication links. Full article

Complexity of non-orthogonal multiple access (NOMA) digital signal processing schemes is particularly relevant in mobile environments because of the varying channel conditions of every single user. In contrast to legacy modulation and coding schemes (MCSs), NOMA MCSs typically have irregular symbol constellations with asymmetric symbol decision regions affecting synchronization at the receiver. Research papers investigating signal processing in this emerging field usually lack sufficient details for facilitating software-defined radio (SDR) implementation. This work presents a new symbolic framework approach for simulating signal processing functions in SDR transmit–receive paths in a dynamic NOMA downlink use case. The proposed framework facilitates simple and intuitive implementation and testing of NOMA schemes and can be easily expanded and implemented on commercially available SDR hardware. We explicitly address several important design and measurement parameters and their relationship to different tasks, including variable constellation processing, carrier and symbol synchronization, and pulse shaping, focusing on quadrature amplitude modulation (QAM). The advantages of the proposed approach include intuitive symbolic modeling in a dynamic framework for NOMA signals; efficient, more accurate, and less time-consuming design flow; and generation of synthetic training data for machine-learning models that could be used for system optimization in real-world use cases. Full article

Traditional wireless positioning techniques often suffer from accuracy degradation in indoor environments due to multipath effects and occlusion. To address this issue, this paper proposes an indoor positioning method for visible light communication (VLC) combined with intelligent reflective surface (IRS) assistance to improve the positioning accuracy and stability in complex environments. This work proposes the concepts of a virtual source and virtual receiver based on IRS and conducts positioning optimization by combining the measurements of the time difference of arrival (TDOA) and angle of arrival (AOA). The research adopts a semi-positive definite relaxation (SDR) optimization method to efficiently solve the nonlinear optimization problem, ensuring the global convergence and accuracy of the algorithm. Meanwhile, the weights of the positioning results of the virtual light source and the real light source are dynamically adjusted by using the distance residual, thereby reducing the influence of measurement noise. Monte Carlo simulation experiments demonstrate the advantages of the proposed method in terms of the positioning error and robustness compared with traditional positioning algorithms in the environment of large noise interference. The experimental results demonstrate the efficacy of the method in addressing multipath and occlusion issues, while also exhibiting notable adaptability and stability across diverse hardware configurations. Full article

Introduction: The combination of BRAF and MEK inhibitors (BRAF/MEKi) has significantly improved survival in melanoma patients with BRAF V600 mutations. However, these agents can cause cardiovascular (CV) toxicity, compromising efficacy. This study evaluated the CV adverse events (cAEs) associated with BRAF/MEKi using the U.S. FDA Adverse Event Reporting System (FAERS) to identify new signals of disproportionate reporting (SDRs). Methods: Descriptive and disproportionality analyses were conducted on reports listing dabrafenib (D), vemurafenib (V), encorafenib (E), trametinib (T), cobimetinib (C), or binimetinib (B) as suspects in monotherapy or combination therapy (D + T, V + C, E + B), with melanoma as the indication and at least one cAE. Standardized MedDRA Queries (SMQs) related to cAEs, including bradyarrhythmias and tachyarrhythmias, cardiac failure, cardiomyopathy, thrombotic events, ischaemic heart disease, and myocarditis/pericarditis, were analyzed. Results: Of the 14,077,067 reports retrieved, 18,370 (0.1%) were linked to BRAF/MEKi, with 1591 (8.7%) reporting cAEs, primarily in combination therapy (n = 1268). Disproportionality analysis identified 64 clinically relevant SDRs, most of which were unexpected. Notable findings included bradyarrhythmias, such as QT prolongation with D + T (n = 59; Reporting Odds Ratio, ROR = 5.09, 95% Confidence Interval, CI = 3.94–6.58), cardiac failure with V + C (29; 3.76, 2.6–5.42), and tachyarrhythmias, particularly atrial fibrillation with D + T (99; 2.37, 1.94–2.89). Among embolic and thrombotic events, clinically significant SDRs were observed for disseminated intravascular coagulation with D + T (38; 10.22, 7.42–14.06) and pulmonary embolism with V + C (22; 2.79, 1.83–4.24). Conclusions: Our findings underscore the need for comprehensive CV monitoring in patients receiving BRAF/MEKi therapy to prevent or detect cAEs early and reduce treatment-related risks, particularly in high-risk populations. Full article

Aim: Socioeconomic factors are known to influence access to health services, including for children with cerebral palsy (CP). This study aims to determine whether socioeconomic disadvantage and/or geographical remoteness influence access to specialised CP interventions: selective dorsal rhizotomy (SDR) and intrathecal baclofen (ITB). Methods: This was a cross-sectional study of children with CP from (i) the Australian SDR Research Registry and (ii) an Australian ITB audit study. Socioeconomic disadvantage was grouped (quintiles) using the Index of Relative Socioeconomic Disadvantage (IRSD). Geographical remoteness was determined using the Australian Statistical Geographical Standard. IRSD quintiles and remoteness were compared with the Australian CP Register (ACPR) (birth years 1995–2016). Results: A total of 64 children (31.3% female) had received SDR surgery and 52 children (48.1% female) had received ITB therapy. Of these, 7 (11.1%) (SDR) and 7 (13.5%) (ITB) lived in the most disadvantaged neighbourhoods (IRSD quintile 1); 41 children (65.1%) (SDR) and 42 (82.4%) (ITB) lived in major cities. In comparison, 1630 (18.8%) of children on the ACPR resided in IRSD quintile 1; 6122 (70.4%) resided in major cities. There were no statistical differences in IRSD distribution between ACPR, SDR, and ITB groups. More children in major cities received ITB therapy (p = 0.03) and more children in outer regional/remote areas had received SDR (p = 0.03). Conclusions: Access to SDR and ITB in Australia varies by geographical remoteness. Equity of access is important to monitor, and interventions should be considered to reduce inequity. Full article

Galileo Signal Authentication Service (SAS) is an assisted signal authentication capability under development by Galileo, designed to enhance the robustness of the European Global Navigation Satellite System (GNSS) against malicious attacks like spoofing. It operates by providing information about some fragments of the unknown spreading codes in the E6-C signal. Unlike other approaches, Galileo SAS uniquely employs Timed Efficient Stream Loss-tolerant Authentication (TESLA) keys provided by Open Service Navigation Message Authentication (OSNMA) in the E1-B signal for decryption, avoiding the need for key storage in potentially compromised receivers. The encrypted fragments are made available to the receivers before the broadcast of the E6-C signal, along with their broadcast time. However, if the receiver lacks an accurate time reference, searching for these fragments—which typically last for milliseconds and have periodicities extending to several seconds—can become impractical. In such cases, the probability of detection is severely diminished due to the excessively large search space that results. To mitigate this, initial estimates for the code phase delay and Doppler frequency can be obtained from the E1-B signal. Nevertheless, the alignment between E1-B and E6-C is not perfect, largely due to the intrinsic inter-frequency biases they exhibit. To mitigate this issue, we can leverage auxiliary signals like E6-B, processed by High Accuracy Service (HAS)-compatible receivers. This is a logical choice as E6-B shares the same carrier frequency as E6-C. This could help in obtaining more precise estimates of the location of the encrypted fragments and improving the probability of detection, resulting in enhanced robustness for the SAS authentication process. This paper presents a comparison of uncertainties associated with the use of the E1-B and E6-B signals, based on real data samples obtained with a custom-built Galileo SAS evaluation platform based on Software Defined Radio (SDR) boards. The results show the benefits of including E6-B in SAS processing, with minimal implementation cost. Full article

In this connected world, communication in all kinds of complex environments is crucial. As a result, indoor satellite communication could enable many new applications and use cases. In this study, we explore the potential of Low Earth Orbit (LEO) satellites to provide indoor coverage. This is done by evaluating the signal strength of Orbcomm LEO satellite signals in multiple indoor environments within a suburban home. Starting from IQ samples, we developed an algorithm to calculate the Carrier-to-Noise Density Ratio (C/N0) as a key performance metric to compare environments when the Carrier-To-Noise Ratio (CNR) is above 0 dB. By utilizing a Software Defined Radio (SDR) in combination with this algorithm, we were able to evaluate the signal strength differences between environments. We found that the LEO satellite signals penetrated into every environment including the basement. The signals were even received with high signal strength in the attic, reaching values above 55 dB-Hz. Moreover, the signals were well received in every above-ground environment. Unsurprisingly, the satellite signals were received the weakest in the basement and only for a short duration of time. Full article

In this study, we propose a method to estimate the Angle-of-Arrival (AoA) of OFDM-based drone signals with wideband and burst characteristics using only a single-channel receiver and a switched-beam antenna. First, six circularly arranged directional antennas are time-division controlled using RF switches to measure the received power of each antenna. Next, the maximum beam pattern and the measured power of each antenna are synthesized in vector form, and the direction of the synthesized vector becomes the angle of arrival of the drone signal. To verify the proposed method, an experiment was conducted using the video signal of DJI Phantom 4 Pro with a bandwidth of 10 MHz. As a result, it was confirmed that stable angle-of-arrival estimation of drone video signals was possible with an average error of less than 5°. The proposed system has the advantage of being able to estimate the AoA of a drone with only a single receiver without the need for synchronization. Therefore, the proposed system is expected to be used as a low-cost, compact, and highly portable anti-drone system. Full article

This paper deals with the concept of a GNSS monitoring network, which fulfills requirements in relation to sustainability, cost efficiency and flexibility. For the proposed approach, the hardware of the GNSS monitoring stations should be reduced to a minimum. Therefore, Remote Radio Head sensors or especially RF Front-Ends, which are already used in the field of GNSS, should be used. In this concept, GNSS network stations are equipped with an antenna, an RF Front-End, and hardware for data transfer (raw I&Q samples) to a central processing facility. The idea is to realize a collaborative processing of all receivers with a Multi-Receiver-Vector Tracking (MRVT) algorithm in one single Software-Defined GNSS receiver (SDR). Full article

This paper addresses the feasibility of implementing spatial diversity techniques to mitigate interference signals using low-cost GNSS receivers. Global Navigation Satellite Systems (GNSSs) remain at the core of navigation technologies and obtaining precise and robust positioning solutions in harsh scenarios becomes essential for the proper functioning of modern applications. Furthermore, this challenge is even more complex when mass-market receivers are addressed, since the previous requirements must be achieved while maintaining low-cost architectures. A promising solution is to use beamforming techniques, which exploit the spatial domain to achieve enhanced reliability and robustness. In this paper, the potential of beamforming in mass-market receivers is analyzed by implementing two interference mitigation techniques and using a five-channel low-cost software defined radio (SDR), KrakenSDR. The results show that the algorithms implemented are able to mitigate strong interference signals, allowing the GNSS receiver to compute an accurate positioning solution. Full article

The Internet of Underwater Things (IoUT) has attracted significant attention from researchers due to the fact that seventy percent of the Earth’s surface is covered by water. Reliable underwater communication is the enabler of IoUT. Different carriers, such as electromagnetic waves, sound, and light, are used to transmit data through the water. Among these, optical waves are considered promising due to their high data rates and relatively good bandwidth efficiency, as water becomes transparent to light in the visible spectrum (400–700 nm). However, limitations such as link range, path loss, and turbulence lead to low power and, consequently, a low signal-to-noise ratio (SNR) at the receiver. In this article, we present the design of a smart transceiver for bidirectional communication. The system adapts the divergence angle of the optical beam from the transmitter based on the power of the signal received. This paper details the real-time data transmission process, where the transmitting station consists of a light fidelity (Li-Fi) transmitter with a 470 nm blue-light-emitting diode (LED) and a software-defined radio (SDR) for underwater optical communication. The receiving station is equipped with a Li-Fi receiver, which includes a photodetector with a wide field of view and an SDR. Furthermore, we use pulse position modulation (PPM), which demonstrates promising results for real-time transmission. A key innovation of this paper is the integration of the Li-Fi system with the SDR, while the system adapts dynamically using a servo motor and an Arduino microcontroller assembly. The experimental results show that this approach not only increases throughput but also enhances the robustness and efficiency of the system. Full article

Recent advances in deep learning have fostered a transition from the traditional, bit-centric paradigm of Shannon’s information theory to a semantic-oriented approach, emphasizing the transmission of meaningful information rather than mere data fidelity. However, black-box AI-based semantic communication lacks structured discretization and remains dependent on analog modulation, which presents deployment challenges. This paper presents a new semantic-aware digital speech communication system, named Hybrid-DeepSCS, a stepping stone between traditional and fully end-to-end semantic communication. Our system comprises the following parts: a semantic encoder for extracting and compressing structured features, a standard transmitter for digital modulation including source and channel encoding, a standard receiver for recovering the bitstream, and a semantic decoder for expanding the features and reconstructing speech. By adding semantic encoding to a standard digital transmission, our system works with existing communication networks while exploring the potential of deep learning for feature representation and reconstruction. This hybrid method allows for gradual implementation, making it more practical for real-world uses like low-bandwidth speech, robust voice transmission over wireless networks, and AI-assisted speech on edge devices. The system’s compatibility with conventional digital infrastructure positions it as a viable solution for IoT deployments, where seamless integration with legacy systems and energy-efficient processing are critical. Furthermore, our approach addresses IoT-specific challenges such as bandwidth constraints in industrial sensor networks and latency-sensitive voice interactions in smart environments. We test the system under various channel conditions using Signal-to-Distortion Ratio (SDR), PESQ, and STOI metrics. The results show that our system delivers robust and clear speech, connecting traditional wireless systems with the future of AI-driven communication. The framework’s adaptability to edge computing architectures further underscores its relevance for IoT platforms, enabling efficient semantic processing in resource-constrained environments. Full article