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One of the major questions in human genetics is what percentage of individuals in the general population carry a disease-causing mutation. Based on publicly available information on genotypes from six main world populations, we created a database including data on 276,921 sequence variants, present within 187 genes associated with autosomal recessive (AR) inherited retinal diseases (IRDs). Assessment of these variants revealed that 10,044 were categorized as disease-causing mutations. We developed an algorithm to compute the gene-specific prevalence of disease, as well as the mutational burden in healthy subjects. We found that the genetic prevalence of AR-IRDs corresponds approximately to 1 case in 1,380 individuals, with 5.5 million people expected to be affected worldwide. In addition, we calculated that unaffected carriers ofmutations are numerous, ranging from 1 in 2.26 individuals in Europeans to 1 in 3.50 individuals in the Finnish population. Our analysis indicates that about 2.7 billion people worldwide (36% of the population) are healthy carriers of at least one mutation that can cause AR-IRD, a value that is probably the highest across any group of Mendelian conditions in humans.

Optoelectronics is a valuable solution to scale up wireless links frequency to sub-THz in the next generation antenna systems and networks. Here, we propose a low-power consumption, small footprint building block for 6 G and 5 G new radio wireless transmission allowing broadband capacity (e.g., 10–100 Gb/s per link and beyond). We demonstrate a wireless datalink based on graphene, reaching setup limited sub-THz carrier frequency and multi-Gbit/s data rate. Our device consists of a graphene-based integrated optoelectronic mixer capable of mixing an optically generated reference oscillator approaching 100 GHz, with a baseband electrical signal. We report >96 GHz optoelectronic bandwidth and −44 dB upconversion efficiency with a footprint significantly smaller than those of state-of-the-art photonic transmitters (i.e., <0.1 mm 2 ). These results are enabled by an integrated-photonic technology based on wafer-scale high-mobility graphene and pave the way towards the development of optoelectronics-based arrayed-antennas for millimeter-wave technology. Here, the authors report the realization of a sub-THz wireless data link based on a graphene-integrated optoelectronic mixer with a >96 GHz bandwidth, −44 dB upconversion efficiency and <0.1 mm 2 footprint, providing an alternative approach for the realization of millimeter-wave transmitters.

Orthogonal frequency division multiple access (OFDMA) is a multi-carrier, multiple access (MA) technique, which is widely adopted in contemporary wireless standards. Single carrier-frequency division multiple access (SC-FDMA) is a modified version of OFDMA which employs single carrier transmission by pre-coding the data symbols using discrete Fourier transform (DFT). However, these systems are highly vulnerable to the adverse effects arising in the channel, carrier frequency offset (CFO) and in-phase/quadrature phase (I/Q) imbalances. In the uplink communication scenario, the signal received at base station is the superposition of signals from all the active users. Even though the adverse effects caused by the communication channel and CFOs are addressed in the related literature extensively, the effect of I/Q-imbalances at the transmitter and the receiver is rarely considered. The effect of I/Q-imbalances will make the equalization process at the base station more complex. It is because the overall effective channel with radio impairments must be included in the system modelling. Hence the receiver processing should contain the equalization for effect of the channel, CFOs and I/Q imbalances. In this paper, we propose a novel technique based on the oblique projection (OP) technique for equalizing the channel, radio imbalances and synchronization errors caused by both transmitter (TX) and receiver (RX) for OFDMA/SC-FDMA uplink systems. We also propose an equalization technique with reduced computational complexity to overcome the adverse effects caused by I/Q imbalances and CFOs. The results of the simulation studies illustrate that the proposed techniques can compensate all the above-mentioned effects and they offer very good performance under both TX and RX I/Q imbalances.

This research allows the secure surveillance approach for the Internet of Things (IoT) methodology to be developed by integrating wireless signalling and image encryption strategy. Since the Cloud Service Telco (CST) is a semi-trusted body in cloud services, user data is encrypted before uploading to a cloud server for data protection from disclosure. The flexibility of encrypted data sharing is essential for cloud storage users. This study investigates the Discrete Wavelet Transform (DWT) technique with modified Huffman compression and Elliptic Curve Cryptography (ECC). It encrypts and decrypts the data and enhances industrial security surveillance in transmission. It uses the wireless network’s next generation (5G or 6G) as uplink Single Carrier Frequency Division Multiple Access (SC-FDMA) strategies via the IoT. This study presented a novel approach to proposing hardware architecture for a secure web camera integrated with the Atmel in the mega AVR family (ATMEGA) microcontroller, suitable for IoT applications. The experimental results confirm the proposed model’s efficacy compared with existing robustness and security analysis algorithms. These systems are also used by implementing industry-standard protocols using IoTs to monitor industrial applications. The proposed framework can also minimise bandwidth, transmission cost, storage space, tracking data, and decisions about abnormal events such as potential fraud and extinguisher detection in surveilling applications.

Emerging low Earth orbit (LEO) satellites offer new opportunities for navigation augmentation. This paper investigates the potential of orthogonal frequency division multiplexing (OFDM) signals for LEO satellite navigation, focusing on challenges arising from carrier frequency offsets (CFOs) in low signal-to-noise ratio (SNR) environments. We comprehensively analyze the navigation properties of OFDM signals, assessing two synchronization sequence (SS) candidates for their resilience against CFOs. Our findings suggest that the m-sequence effectively mitigates integer CFOs while minimally impacting the receiver’s ranging estimation in the presence of fractional CFOs. Additionally, we introduce an SS detection architecture that integrates differential coherent accumulation (DCA) with a near-optimal likelihood ratio test (NOLRT). This DCA-NOLRT-based LEO receiver enhances detection reliability and sensitivity, effectively managing residual fractional CFOs and improving detection probabilities in low-SNR scenarios. Numerical simulations and terrestrial experiments validate the proposed framework’s capability to minimize CFO-induced ranging errors, even under demanding conditions in LEO navigation scenarios.

This paper deals with the blind carrier frequency offset (CFO) estimation based on weighted subspace fitting (WSF) criterion with fuzzy adaptive gravitational search algorithm (GSA) for the interleaved orthogonal frequency-division multiplexing access (OFDMA) uplink system. For the CFO estimation problem, it is well known that the WSF has superior statistical characteristics and better estimation performance. However, the type of CFO estimation must pass through the high-dimensional space problem. Optimizing complex nonlinear multimodal functions requires a large computational load, which is difficult and not easy to maximize or minimize nonlinear cost functions in large parameter spaces. This paper firstly presents swarm intelligence (SI) optimization algorithms such as GSA, particle swarm optimization (PSO), and hybrid PSO and GSA (PSOGSA) to improve estimation accuracy and reduce the computational load of search. At the same time, this paper also integrates a fuzzy inference system to WSF-GSA to dynamically adjust the gravitational constant, which can not only reduce the searching computational load, but also improve the performance of GSA in the global optimization and solution accuracy. Finally, several simulation results are provided for illustrating the effectiveness of the proposed estimator.

In this paper, we study the joint effects of timing offset (TO), carrier frequency offset (CFO), phase noise (PN), and nonlinear power amplifier distortion on a generalized frequency division multiplexing (GFDM) system. Classifying the TO into four cases based on the direction of offset, our work analyzes the signal-to-interference ratio (SIR) for each of the four cases at the GFDM receiver in the presence of synchronization errors, PN, and nonlinear power amplifier. Then, we conduct simulations to compare the performance of GFDM systems under these impairments with that of orthogonal frequency division multiplexing (OFDM) systems, considering both matched filter and zero-forcing. The results show that GFDM systems are more robust against TO and PN while they are more sensitive to CFO and nonlinear distortion compared to OFDM systems. More specifically, it is shown that employing GFDM improves the system SIR compared to OFDM by up to 3 dB and 1.5 dB under TO and PN distortions, respectively.

OFDM is superior technique in wireless sensor networks with low power consumption. Channel estimation modelling for low power wireless access might lead to exclusive access of transmission leading to failure of an augmented path. The proposed work models the channel where in intricate scenario of interference, error in carrier frequency offset the possibility to counter sensor data is being initiated from source sensor. The proposed work incorporates residual network architecture and uses two paths for considering a flow from source to sink. The first main path estimates the channel between source and relay then between relay and penultimate node to sink with the objective of minimizing the carrier frequency offset error. Second skip connection estimate the direct forwarding from source to penultimate node to sink for calculating the residual block characteristics. Thus the simulation work shows the proposed Residual Neural Network based OFDM achieves superiority is balancing every flow and superiority than conventional OFDM technique.

The global navigation satellite system (GNSS) spoofing technology is an important method to control the targets that pose threats and protect sensitive areas. Traction spoofing can gradually take over the tracking loop by spoofing signals. To achieve more covert spoofing of a receiver configured with phase lock loop (PLL) assisted delay lock loop (DLL) loop, the following research work has been carried out: First, the response of the combined loop to GNSS spoofing is analyzed; Second, a new asynchronous traction signal spoofing algorithm is proposed; in the design of the code rate and carrier frequency of spoofing signal, the dynamic performance of the loop is fully considered, while maintaining a good consistency with the carrier frequency. In the design of the power of the spoofing signal, the success rate of spoofing is improved as much as possible while avoiding absolute power monitoring. Finally, the calculation method of the parameters of the spoofing signal is given. Third, by building the GNSS signal generation software and software receiver platform to carry out experimental verification and through experimental comparison and analysis with many existing representative spoofing schemes, it is proved that the new algorithm can successfully achieve spoofing. The spoofing takes 107.8 s, which makes the local code rate increase 0.03 Hz, the carrier frequency increase 50 Hz, the average value of consistency spoofing detection is 9.40 × 10−3, and finally stabilized at the convergence value  − 2.95 × 10−8, that is, during the spoofing process, spoofing signal maintains the consistency of the authentic signal, which can well avoid the consistency spoofing detection of the receiver, the effectiveness and superiority of the proposed algorithm compared with other spoofing methods are fully verified.

Ambient backscatter systems enable passive sensing and information transfer by utilizing the reflection and modulation of incident radio-frequency (RF) signals. However, in real-world scenarios involving non-cooperative targets such as off-the-shelf printed circuit boards (PCBs), the backscattered signal is extremely weak and often obscured by strong direct-path self-interference (SI) at the receiver. This issue becomes even more severe when unintentional PCB structures act as radiating elements. In this work, we explore ambient backscatter leakage from a compromised PCB using a realistic measurement setup that includes separated transmit and receive antennas and a direct-conversion Universal Software Radio Peripheral (USRP)-based receiver. We demonstrate that residual carrier frequency offset (CFO), caused by oscillator mismatch and hardware imperfections, can spread the dominant SI in the baseband and completely mask the weak backscattered signal. To solve this problem, a software-based post-processing framework is applied. This method leverages the complex baseband representation enabled by the homodyne receiver to jointly manage the carrier and SI components without relying on intermediate-frequency processing or prior knowledge of the target signal parameters. Experimental results show that this approach significantly improves the detectability of weak backscattered baseband information that would otherwise be concealed within the raw I/Q data. This study emphasizes the importance of CFO-aware digital processing in ambient backscatter systems and offers new insights into unintended electromagnetic leakage mechanisms from commercial PCB platforms.