Simultaneous polling mechanism for low power sensor networks using ZC sequences

The 3rd Generation Partnership Project (3GPP) has started to investigate feasibility of machine type communication terminal class in Long Term Evolution (LTE) networks in the Release 12 to address the requirements of the Internet of Tings (IoT) targeting low-end device market with improved coverage. Along with that, the 3GPP has defined reference signals to support device discovery, communication and synchronization. These signals are transmitted by either an eNB within the coverage area, or a peer User Equipment (UE) in partial and out of coverage scenarios. The regular LTE synchronization signals, built from Zadoff-Chu (ZC) sequences and M-sequences, are reused in Rel-12. In this paper, we deal with low- complexity synchronization approach based on ZC sequences and tailored to LTE signal. The presented approach carries out Simply-Differential (SD) correlation-based metric that allows the detection of a ZC sequence pattern within the received signal. The SD metric correlates the received signal and compensates the output with an adjustment frequency whose value depends on the training ZC sequence. To reduce the huge computational load resulting from differential correlation operations, a recursive implementation of the SD metric is proposed. The performance is here evaluated in terms of theoretical probability of correct detection and compared to the experimental rate of correct detection to validate the analysis. The obtained results show good match between analytical and experimental probabilities.

The fast growth of drone applications in industrial, commercial and consumer domains in recent years has caused great security, safety and privacy concerns. For this reason, a demand for solutions of drone detection and monitoring in consumer market can be foreseen in the near future. For detecting drones that employ Zadoff-Chu (ZC) sequences for synchronization, these ZC sequences can be used to determine their presence in the air. However, it is a great challenge to blindly detect thousands of unknown ZC sequences possibly used by the drones in real time. Existing solutions mainly developed for LTE systems cannot be directly applied to the blind detection of ZCs in drones without incurring huge cost. In this paper, a low-complexity cost effective blind ZC detection method based on double differential is proposed for low-cost drone detection and monitoring systems. Signal-to-noise ratio (SNR) lower bounds are analytically derived for low and high SNR regimes. Monte Carlo simulations show the proposed scheme performs well in moderate and high SNR.

In this paper, a new preamble design technique that can increase the number of cell IDs (CIDs) and beam IDs (BIDs) significantly is proposed, using a preamble sequence constructed by a combination of two Zadoff-Chu (ZC) sequences. An efficient technique for the CID and BID (CBID) detection is also described for the proposed preamble. It is shown by simulations using a simple model of an mmWave cellular system that the proposed technique can obtain a significant reduction in the complexity of the CBID detection without a noticeable performance degradation, compared to the previous technique.

This paper proposes a downlink synchronization and cell identity (CID) estimation technique for cellular systems based on orthogonal time-frequency space (OTFS). In the proposed technique, each base station (BS) transmits one detection preamble (DP) and two OTFS symbols (pilot and secondary-CID (SCID) signal (SS)). The DP based on a linear frequency-modulated (LFM) waveform, called proposed-LFM (pLFM), carries the primary-CID (PCID) for symbol timing (ST) synchronization, whereas the SS based on the Zadoff-Chu (ZC) sequence mapped in the delay-Doppler domain carries the SCID. The pLFM is obtained by discretizing the LFM waveform, increasing the frequency sweeping parameter beyond the limit of the operational bandwidth, and incorporating the PCID into the LFM waveform. The autocorrelation and cross-correlation functions of the pLFM are analyzed to examine its correlation properties under the influence of a high Doppler shift. To reduce the undesirable correlation properties (side peak and time ambiguity), a receiver processing (RP) scheme is developed for the pLFM. It is found that the pLFM with RP is suitable for the DP design because it can provide an accurate ST in high-mobility scenarios. In addition, the influence of OTFS modulation on the ZC sequence is derived and a low-complexity detection algorithm based on message passing is applied to detect SCID at the user equipment. The simulation results demonstrate that the proposed downlink synchronization and CID estimation techniques are suitable for OTFS-based cellular systems in high-Doppler environments.

A frequency-domain cepstrum correlation and temporal transient filtered radio frequency fingerprints (RFF) blind extraction method is proposed for long term evolution uplink device authentication in this work. With the merits of the constant-modulus nature of the Zadoff-Chu (ZC) sequence and the cyclic prefix (CP) structure of the physical random access channel (PRACH) frame, the device RFF integrated in both the frequency-domain ZC sequence and the transient ramp-on/ramp-off sequences are extracted. For the frequency-domain RFF extraction, the cepstrum of the ZC sequence is calculated to enlarge the gap between the constant RFF and the random fading effects, and the correlation between two cepstrum fragments is then calculated to mitigate the random fading components. For the temporal RFF extraction, the ramp-on and ramp-off features induced by the device-specific power amplifier are extracted by exploiting the CP structure of the PRACH frame, where the CP part and the duplicate part are adaptively filtered and the final adapted weight of the least mean square filter is used as RFF. No prior PRACH parameter knowledge is required in RFF extraction and both the frequency-domain and the temporal RFF are combined as the input of the convolutional neural network to enhance the classification accuracy. With four-months sampling of PRACH signals emitted from universal software radio peripheral devices, the experimental results show that the authentication accuracy of the proposed combined RFF can reach as high as 99.9% in the line-of-sight (LOS) scenario and 99.6% in the non-LOS scenario.

In this letter, new sets of non-orthogonal spreading sequences are constructed for uplink grant-free access of devices. Based on Golay complementary sequences and sets, the spreading sequences have theoretically bounded low peak-to-average power ratio (PAPR) for multicarrier transmission. Also, the corresponding spreading matrix has theoretically bounded low coherence, which guarantees the reliable performance of compressed sensing (CS) based joint channel estimation (CE) and multiuser detection (MUD). While the spreading sequence set accommodates up to 300% overloaded devices, a large number of distinct sequence sets can also be constructed for future applications. Simulation results demonstrate that the Golay-based sequences exhibit the PAPR of at most 4, which is lower than those for random bipolar, Gaussian, and Zadoff-Chu (ZC) sequences. We also observe that the Golay-based sequences provide the reliable performance for CS-based joint CE and MUD. Finally, the Golay-based sequences have fewer phases than ZC sequences, which can be more suitable for low cost devices in machine-type communications (MTC).

This paper presents a configurable and optimized hardware architecture for computing Zadoff-Chu (ZC) complex sequences in the frequency domain. It is a hardware-efficient and accurate architecture for computing ZC sequences in realtime. The architecture is mainly based on the CORDIC algorithm for computing complex exponentials using only shift and add operations. Due to transformations applied to the Zadoff-Chu equation it is possible to eliminate the use of multipliers with non-constant terms. This hardware architecture is employed by the Physical Random Access Channel (PRACH) in LTE and LTE-A systems during the reception and detection of random access preambles. Its main advantage is that it eliminates the need for storing a large number of long complex ZC sequences. Simulation results show that the proposed architecture is accurate, efficient and renders the resulting PRACH receiver fully compliant with 3GPP's detection requirements.

An accurate frequency synchronization method using the zadoff-chu (ZC) constant envelop preamble is analyzed, and a new preamble weighted by pseudo-noise sequence is used for orthogonal frequency division multiplexing (OFDM) systems. Using this method, frequency offset estimator range is greatly enlarged with no loss in accuracy. The range of the frequency estimation is ±30 of subcarrier spacing using ZC sequence as preamble. Simulations in the MATLAB for an AWGN channel show that the proposed method achieves superior performance to existing techniques in terms of frequency accuracy and range.

Estimation of carrier frequency offset and channel state information of generalize frequency division multiplexing systems by using a Zadoff–Chu sequence

We propose a multiple chirp rate index modulation (MCR-IM) system based on Zadoff-Chu (ZC) sequences that overcomes the problems of low transmission rate and large-scale access in long-range wide-area network (LoRaWAN) using classical LoRa modulation. We demonstrate the extremely low cross-correlation of MCR-IM signals across different spread factors, showing that the proposed MCR-IM system also inherits the characteristics of ZC sequences modulation. Moreover, we derive an approximate approximate closed-form expression for the bit-error-rate (BER) of the proposed MCR-IM system over Nakagami-<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> fading channels. Simulation results confirm the accuracy of the derived approximate closed-form expression and demonstrate that the MCR-IM system achieves higher levels of spectral efficiency (SE) compared to existing systems like frequency-shift chirp spread spectrum with index modulation (FSCSS-IM), group-based CSS (GCSS), layered CSS (LCSS), and layered group-based CSS (LGCSS). In this context, assigning multiple chirp rates to each user results in a reduction in the number of parallel channels. To mitigate this issue, we propose a peak detection based successive interference cancellation (PD-SIC) algorithm to accommodate more users. Results further show that the proposed system with the PD-SIC algorithm achieves a lower BER and higher throughput than the orthogonal scatter CSS (OrthoRa) system under collision scenarios, making it a compelling solution for future large-scale, high-throughput Internet of Things network.

This paper introduces a novel way to accurately estimate Doppler scaling factors in multi-scale multi-lag (MSM-L) channels for underwater acoustic communications using a Zadoff-Chu (ZC) sequence. Taking advantages of the ZC sequence, the Doppler scale estimation is successfully transformed into a frequency analysis problem. An iterative approach is designed to calculate the Doppler scaling factor of each path in the MSML channel. Numerical simulations are carried out to compare the proposed method with the fractional Fourier transform (FrFT)-based one. The results show that the proposed method has a better performance than the latter one.

For the increasingly strong demand for low-orbit navigation enhancement, a novel navigation and communication integrated (NAVCOM) waveform for the LEO constellation is proposed, which can conduct communication and navigation simultaneously. Zadoff-Chu (ZC) sequence with controllable power is superimposed on the communication signal in the frequency domain as the positioning signal. Furthermore, positioning can be conducted with both time-domain correlation detection (TDCD) and frequency-domain phase estimation (FDPE) for higher ranging accuracy benefits from the Fourier invariance of ZC sequence. Interference between positioning and communication components is analyzed, and the Cramer-Rao low bound (CRLB) of ranging error is given. The performance evaluations show that the novel waveform can achieve high-precision positioning without signifilcantly affecting communication performance.

Ultrasonic Local Positioning Systems (U-LPS) can be used for fine-grained indoor positioning. Typically, multiple fixed beacons simultaneously emit ultrasonic signals whose time of arrival is estimated at a mobile receiver. The ultrasonic signals are encoded and modulated to allow separation of the signals at the receiver, identification of the transmitters, and mitigation of signal impairments such as multipath, the near-far effect, multiple access interference, and Doppler shift. Hence, waveform design (coding and modulation) plays a pivotal role in determining the performance of such a system. This paper compares the performance of four modulation techniques (specifically QPSK, OFDM, Slow-FHSS and Fast-FUSS) transmitting Zadoff-Chu (ZC) sequences in an U-LPS. The modulation schemes are evaluated in terms of time of arrival accuracy and positioning accuracy in simulation and real-world experiments. Simulation and, to a lesser extent, real-world tests indicate that ZC coded QPSK modulation with non-coherent detection using a matched filter, offers greater accuracy under realistic conditions than the other modulation schemes.

Mid-band frequencies have recently attracted attention as promising sixth-generation (6G) candidates due to their potential to mitigate the instability of sub-terahertz (sub-THz) and millimeter-wave (mmWave) bands. While ongoing studies investigate channel models for this spectrum, they largely focus on individual frequencies across diverse environments. For mobile network operators (MNOs), measurement-based comparative studies that directly evaluate the advantages and limitations of candidate bands under identical deployment scenarios are essential. Obtaining high-resolution channel impulse responses (CIRs) in the mid-band, however, is constrained by limited spectrum availability, and existing approaches often rely on costly, synchronization-dependent equipment, thereby restricting portability and versatility. This paper proposes an asynchronous and portable software-defined radio (SDR)-based channel sounder that employs a Zadoff-Chu (ZC) sequence to enable direct comparison between frequency range 1 (FR1, 4.55 GHz and 6.55 GHz) and FR3 (7.15 GHz) under identical transceiver conditions. The SDR system was validated through back-to-back calibration, and the verified platform was subsequently used to conduct channel measurement campaigns in both indoor hotspot (InH) and urban microcell (UMi) environments. The measured data were analyzed in terms of path loss and large-scale characteristics, and parameter comparisons with the third generation partnership projects (3GPP) standard were performed to ensure validity. The results of this channel analysis are expected to provide practical insights into frequency band selection for future 6G services.

The estimation of velocity, angle-of-arrival (AOA), and range of a target has been researched for decades, as it finds wide applications in radar and wireless communications. In recent years, this classic problem has gained renewed interest with the advent of 5G internet of things (IoT) technologies, owing to the numerous emerging localization-related applications. This paper studies the joint estimation of velocity, AOA, and range (JEVAR) of a target in a multipath environment. To solve the JEVAR problem, we propose a novel scheme, which has the target transmit a pair of conjugate Zadoff-Chu (ZC) sequences and has the multi-antenna receiver conduct maximum likelihood (ML) estimation. The simulations verify the effectiveness of the proposed scheme by showing that its performance can approach the Cramer-Rao bound (CRB).