Search Results (19)

Large carrier frequency offsets (CFOs) can severely distort the correlation response of the Physical Random Access Channel (PRACH), generating multiple significant peaks even for a single transmitting user equipment (UE), such that CFO-induced pseudo-peaks may exceed the detection threshold and be erroneously identified as valid peaks. This work addresses the problem of peak disambiguation under such conditions by formulating peak selection as a model-consistency validation problem under mismatch. A generalized likelihood ratio test (GLRT) is first formulated to provide a principled statistical validation of each detected candidate peak based on the estimated timing advance (TA) and CFO parameters. While theoretically grounded, this approach is shown to be insufficient under realistic large-CFO conditions, where CFO-induced peak ambiguity is further complicated by multipath-induced model mismatch. To address this limitation, a complementary residual-energy-based criterion is introduced, along with a weighted combination of both metrics, interpreted as a penalized consistency criterion for robust peak selection under model mismatch. The proposed framework enables the selection of a single reliable TA/CFO pair among multiple candidates, improving receiver robustness and reducing spurious updates. Performance is evaluated using precision, recall, and F1-score for both short and long PRACH formats under 3GPP-aligned channel models, including high-CFO and high-Doppler scenarios. Results demonstrate that the proposed weighted strategy generally provides a more robust trade-off than the individual GLRT-only and residual-only criteria. Full article

This paper extends cyclic permutation coding, previously applied for error correction in power-line communications (PLC), to synchronization-oriented sequence design by introducing a novel class of Non-Binary Cyclic Permutation Sequences (NCPS) for low-correlation multiuser synchronization. Unlike conventional Zadoff–Chu (ZC) and constant-amplitude zero-autocorrelation (CAZAC) sequences that rely on complex-valued phase laws, NCPS employ discrete modular permutations mapped to complex exponentials. Autocorrelation properties were analytically derived where tractable, while general correlation behavior was characterized through structural analysis and confirmed via simulation. Results demonstrated that NCPS achieved near-orthogonal cyclic correlation performance comparable to ZC sequences while preserving optimal Hamming distance, beneficial for error correction, and offering reduced implementation complexity. These characteristics highlight the potential of NCPS as synchronization preambles in PLC systems and other low-complexity or quantized communication platforms, including Internet of Things networks. Full article

Satellite–terrestrial integrated communication systems (STICSs) are envisioned to provide ubiquitous, seamless connectivity in next-generation (6G) wireless communication networks for massive-scale Internet of Things (IoT) deployments. This global coverage extends beyond densely populated areas to remote regions (e.g., polar zones, open oceans, deserts) and disaster-prone areas, supporting diverse IoT applications, including remote sensing, smart cities, intelligent agriculture/forestry, environmental monitoring, and emergency reporting. Random access signals, which constitute the initial transmission from access IoT devices to base station for unscheduled transmissions or network entry in terrestrial networks (TNs), encounter significant challenges in STICSs due to inherent satellite characteristics: wide coverage, large-scale access, substantial round-trip delay, and high carrier frequency offset (CFO). Consequently, conventional TN preamble designs based on Zadoff–Chu (ZC) sequences, as used in 4G LTE and 5G NR systems, are unsuitable for direct deployment in 6G STICSs. This paper first analyzes the challenges in adapting terrestrial designs to STICSs. It then proposes a CFO-resistant preamble design specifically tailored for STICSs and details its detection procedure. Furthermore, a dedicated root set selection algorithm for the proposed preambles is presented, generating an expanded pool of random access signals to meet the demands of increasing IoT device access. The developed analytical framework provides a foundation for performance analysis of random access signals in 6G STICSs. Full article

Maritime search and rescue (SAR) demands reliable sensing and communication under sea clutter. Emerging integrated sensing and communication (ISAC) technology provides new opportunities for the development and modernization of maritime radio communication, particularly in relation to search and rescue. This study investigated the dual-function capability of a phase-coded frequency modulated continuous wave (FMCW) system for search and rescue at sea, in particular for life signs detection in the presence of sea clutter. The detection capability of the FMCW system was enhanced by applying phase-modulated codes on chirps, and radar-centric communication function is supported simultaneously. Various phase-coding schemes including Barker, Frank, Zadoff-Chu (ZC), and Costas were assessed by adopting the peak sidelobe level and integrated sidelobe level of the ambiguity function of the established signals. The interplay of sea waves was represented by a compound K-distribution model. A multiple-input multiple-output (MIMO) architecture with the ZC code was adopted to detect multiple objects with a high resolution for micro-Doppler determination by taking advantage of spatial coherence with beamforming. The effectiveness of the proposed method was validated on the 4-transmit, 4-receive (4 × 4) MIMO system with ZC coded FMCW signals. Monte Carlo simulations were carried out incorporating different combinations of targets and user configurations with a wide range of signal-to-noise ratio (SNR) settings. Extensive simulations demonstrated that the mean squared error (MSE) of range estimation remained low across the evaluated SNR setting, while communication performance was comparable to that of a baseline orthogonal frequency-division multiplexing (OFDM)-based system. The high performance demonstrated by the proposed method makes it a suitable maritime search and rescue solution, in particular for vision-restricted situations. Full article

Conventional synchronization signal detection methods rely on linear correlation function analysis with fixed thresholds, which are insufficient for handling the nonlinear characteristics of practical wireless communication systems. In such environments, the usage of a long synchronization signal is beneficial for ensuring sufficient correlation information and enhancing detection robustness. To address these problems, this paper proposes a novel framework that combines Hankelization-based preprocessing with the operation of a neural network (NN). The proposed method enhances feature extraction through the inverse Fourier transform and Hankel matrix construction, followed by singular value decomposition (SVD) to preserve dominant signal features and suppress noise components. Leveraging the ability of NNs to learn nonlinear patterns, the proposed method eliminates the need for fixed thresholds and achieves robust synchronization signal detection. The simulation results demonstrate superior accuracy in various environments compared to conventional methods, underscoring the potential of Hankelization-based preprocessing in future wireless communication systems. Full article

With the advancement of artificial intelligence, the inference capabilities of Autonomous Underwater Vehicles (AUVs) have significantly improved, leading to growing interest in AUV applications. To ensure reliable operations, the field of underwater communications demands robust schemes that account for AUV mobility and enable the formation of underwater cellular networks. Conventional approaches using Linear Frequency Modulation (LFM) and Zadoff–Chu sequence (ZCS) sequences for frame detection and Cell ID (CID) assignment degrade substantially under severe Doppler conditions. In particular, AUVs experience pronounced Doppler shifts due to their mobility in underwater channels. In this study, we propose a methodology in which distinct Superimposed Adjusted-HFM (SA-HFM) signals are assigned to multiple buoys, allowing AUVs to jointly perform frame detection, CID assignment, and Doppler estimation in challenging underwater environments. To validate the proposed scheme, an ocean experiment was conducted in the East Sea of the Republic of Korea. The results demonstrate that the SA-HFM-based signals successfully achieved frame detection, CID assignment, and Doppler estimation at distances ranging from 500 m to approximately 2 km, even when the AUV moved at speeds of 1.02–1.54 m/s. The experimental results indicate that the proposed approach can offer robust underwater communication and facilitate the deployment of underwater cellular networks for mobile AUV operations. Full article

In underwater communications for 6G, Doppler effects cause the coherent time to become similar to or shorter than the orthogonal frequency division multiplexing (OFDM) symbol length. Conventional time and frequency synchronization methods require additional training symbols for synchronization, which reduces the traffic data rate. This paper proposes the Zadoff–Chu sequence (ZCS) pilot-based OFDM for time and frequency synchronization. The proposed method transmits ZCS as a pilot for OFDM symbols and simultaneously transmits traffic data to increase the traffic data rate while estimating the CFO at each coherence time. For time–frequency synchronization, the correlation of the ZCS pilot is used to perform coarse and fine time and frequency synchronization in two stages. Since the traffic data cause interference with the correlation of ZCS pilots, we theoretically analyzed the relationship between the amount of traffic data and interference and verified it through computer simulations. The synchronization and BER performance of the proposed ZCS pilot-based OFDM were evaluated by conduction computer simulations and a practical ocean experiment. Compared to the methods of Ren, Yang, and Avrashi, the proposed method demonstrated a 6.3% to 14.3% increase in traffic data rate with similar BER performance and a 2 dB to 3.8 dB SNR gain for a 14.3% to 23.8% decrease in traffic data rate. Full article

This paper introduces a robust synchronization method for orthogonal frequency division multiplexing (OFDM) in multi-unmanned aerial vehicle (UAV) communication systems, focusing on minimizing overhead while achieving reliable synchronization. The proposed synchronization scheme enhances both frame efficiency and implementation simplicity. Initially, a high-efficiency frame structure is designed without a guard time interval, utilizing a preamble sequence to simultaneously achieve both symbol synchronization and automatic gain control (AGC) before demodulation. Subsequently, a novel 2-bit non-uniform quantization method for the Zadoff–Chu sequences is developed, enabling the correlation operations in the traditional symbol synchronization algorithm to be implemented via bitwise exclusive OR (XOR) and addition operations. The complexity of hardware implementation and the energy consumption for symbol synchronization can be reduced significantly. Furthermore, the impact of AGC on frequency synchronization performance is examined, and an improved frequency synchronization method based on AGC gain compensation is proposed. Finally, the performance of the proposed method is rigorously analyzed and compared with that of the traditional method through computer simulations, demonstrating the effectiveness and superiority of the proposed approach. Full article

Since orthogonal frequency division multiplexing (OFDM) systems are very susceptible to symbol timing offset (STO) and carrier frequency offset (CFO), which cause inter-symbol interference (ISI) and inter-carrier interference (ICI), accurate STO and CFO estimations are very important. In this study, first, a new preamble structure based on the Zadoff–Chu (ZC) sequences was designed. On this basis, we proposed a new timing synchronization algorithm, called the continuous correlation peak detection (CCPD) algorithm, and its improved algorithm: the accumulated correlation peak detection (ACPD) algorithm. Next, the correlation peaks that were obtained during the timing synchronization were used for the frequency offset estimation. For this, the quadratic interpolation algorithm was adopted as the frequency offset estimation algorithm, which was better than the fast Fourier transform (FFT) algorithm. The simulation results showed that when the correct timing probability reached 100%, under the parameters of m = 8 and N = 512, the performance of the CCPD algorithm was 4 dB higher than that of Du’s algorithm, and that of the ACPD algorithm was 7 dB. Under the same parameters, the quadratic interpolation algorithm also had a great performance improvement in both small and large frequency offsets, when compared with the FFT algorithm. Full article

In this paper, we propose a novel technique for the inspection of high-density polyethylene (HDPE) pipes using ultrasonic sensors, signal processing, and deep neural networks (DNNs). Specifically, we propose a technique that detects whether there is a diversion on a pipe or not. The proposed model transmits ultrasound signals through a pipe using a custom-designed array of piezoelectric transmitters and receivers. We propose to use the Zadoff–Chu sequence to modulate the input signals, then utilize its correlation properties to estimate the pipe channel response. The processed signal is then fed to a DNN that extracts the features and decides whether there is a diversion or not. The proposed technique demonstrates an average classification accuracy of $90.3\%$ (when one sensor is used) and $99.6\%$ (when two sensors are used) on $\frac{3}{4}$ inch pipes. The technique can be readily generalized for pipes of different diameters and materials. Full article

In underwater acoustic cellular (UWAC) systems, underwater equipment or sensor nodes (UE/SN) should perform downlink synchronisation and a cell search during the initial access stage using the preambles received from adjacent underwater base stations (UWBSs). The UE/SN needs to estimate accurate timing and cell ID (CID) using the received preambles, and synchronise with a serving UWBS, even in high-Doppler environments. In this paper, a sequence design technique for joint estimation of accurate timing and CID in UWAC systems with a high Doppler is proposed to decrease the receiver complexity and processing time. A generalised Zadoff–Chu sequence is proposed for the preamble design. This sequence is decomposed into multiple short sub-sequences to reduce the effect of Doppler shift on the timing and CID estimation. The performance loss caused by the short sequence length is compensated by combining the sub-sequences using the repetition property of the ZC sequence. The properties (autocorrelation and cross-correlation) of the proposed sequence are derived analytically in the presence of Doppler shift and compared with the simulation results. The simulation results reveal that the proposed technique performs better than existing techniques in both additive white Gaussian noise and multipath channels with a high-Doppler. It is concluded that the proposed technique is suitable for accurate timing estimation and CID detection in UWAC systems with a high Doppler. Full article

The concept of an intelligent reflecting surface (IRS) has recently emerged as a promising solution for improving the coverage and energy/spectral efficiency of future wireless communication systems. However, as the number of reflecting elements in an IRS increase, the beam training protocol in IRS-assisted millimeter-wave (mmWave) cellular systems requires a large beam training time because it needs to find the best beam pairs for the link between the base station (BS) and the IRS, as well as the link between the IRS and the mobile station (MS). In this paper, a fast beam training technique for IRS-assisted mmWave cellular systems with a uniform rectangular array is proposed for detecting the best beam pairs of BS-IRS and IRS-MS links simultaneously. Two different types of beam training signals (BTSs) are proposed to distinguish simultaneously transmitted beams from the BSs in multi-cell multi-beam environments: the Zadoff–Chu sequence based BTS (ZC-BTS) and m-sequence based BTS (m-BTS). The correlation properties of ZC-BTSs and m-BTSs are analyzed in multi-cell multi-beam environments. In addition, the effect of symbol time offset on the ZC-BTS and m-BTS is analyzed. Finally, simulation results reveal that the proposed technique can significantly reduce the beam training time for IRS-assisted mmWave cellular systems. Full article

From a conceptual perspective, beyond-5G technologies promise to deliver very low latency, even higher data rates, and ultrareliable connections for future generations of communication systems. Modulation schemes based on orthogonal frequency-domain multiplexing (OFDM) can accommodate these requirements for wireless systems. Several hybrid OFDM-based systems, such as the time-interleaved block-windowed burst–OFDM (TIBWB–OFDM), are capable of achieving even better spectral confinement and power efficiency. This paper addresses the implementation of the TIBWB–OFDM system in more realistic and practical wireless link scenarios by addressing the challenges of proper and reliable channel estimation and frame synchronization. We propose to incorporate a preamble formed by optimal correlation training sequences such as the Zadoff–Chu (ZC) sequences. The added ZC preamble sequence is used to jointly estimate the frame beginning through signal-correlation strategies and a threshold decision device, and acquire channel-state information (CSI) by employing estimators on the basis of the preamble sequence and transmitted data. The employed receiver estimators show that it is possible to detect the TIBWB–OFDM frame beginning and highlight the robustness of the TIBWB–OFDM technique to imperfect channel estimations by showing that it can provide comparatively close BER performance to the one where the CSI is perfectly known. Full article

Narrowband Internet of Things is one of the most promising technologies to support low cost, massive connection, deep coverage, and low power consumption. In this paper, a computationally efficient narrowband secondary synchronization signal detection method is proposed in the narrowband Internet of Things system. By decoupling the detection of complementary sequence and Zadoff–Chu sequence that make up the synchronization signal sequence, the search space of narrowband secondary synchronization signal hypotheses is reduced. Such a design strategy along with the use of the symmetric property of synchronization signals allows reduced-complexity synchronization signal detection in the narrowband Internet of Things system. Both theoretical and simulation results are provided to verify the usefulness of the proposed detector. It is shown via simulation results that the complexity of the proposed detection method is significantly reduced while producing some performance degradation, compared to the conventional detection method. Full article

Millimeter-wave (mmWave) bands is considered for fifth-generation (5G) cellular systems because abundant spectrum is available for mobile broadband communications. In mmWave communication systems, accurate beamforming is important to compensate for high attenuation in the mmWave frequency band and to extend the transmission range. However, with the existing beamformers in mmWave cellular systems, the mobile station (MS) cannot identify the source (base station; BS) of the received beam because there are many neighboring BSs transmitting their training signals, requiring a large overhead. This paper proposes a new beam weight generation method for transmitting (Tx) beamformers at the BS in mmWave cellular systems during a beam training period. Beam weights are generated for Tx beamformers at neighboring BSs, so that a mobile station (MS) can estimate the source (cell ID; CID) and angle of departure (AoD) for each BS in multi-cell environments. A CID and AoD estimation method for mmWave cellular systems in a line-of-sight (LOS) dominant condition is presented using the beam weights generated by Zadoff-Chu sequence. A simulation is conducted in a LOS dominant condition to show that the performances of CID detection and AoD estimation are similar for both the proposed and conventional methods. In the conventional methods, the DFT-based beamforming weight is used for Tx beamformer at the BS and orthogonal matching pursuit (OMP) algorithm is used for AoD estimation at the MS. The proposed method significantly reduces the processing time (1.6–6.25%) required for beam training compared to the conventional method. Full article