Drone Detection via Low Complexity Zadoff-Chu Sequence Root Estimation

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.

A major challenge in low power sensor networks is collecting data from large number of nodes with low latency. Access point (AP) typically needs to poll large number of nodes individually and schedule transmission times for each of the nodes resulting in large latency. In this paper, we propose a physical layer technique that parallelizes the polling response from multiple nodes (so called parallel acknowledgment) in order to decrease the latency. Each node responds to the poll request of an AP by using the well-known Zadoff-Chu (ZC) sequences. By using the orthogonal properties of the ZC sequences, the AP is able to resolve the multiple signatures of different nodes simultaneously. We further develop low complexity transmission scheme for the ZC sequences in order to reduce the number of computations and complexity required by the low power sensor nodes. We also compare the performance of both time and frequency domain receivers.

In this paper, we present the error probability expressions for a wideband coherent spatially correlated Multiple Input Multiple Output (MIMO) channel in low signal to noise ratio (SNR) regimes. Prior works have depicted a decrease in performance due to spatial correlation in high SNR regimes. This work proves that in a power limited broadband MIMO system, spatial correlation across the channel fading matrix elements improves the probability of error performance. In other words, spatial correlation impacts the MIMO performance differently in high SNR compared to low SNR (wideband) regimes.

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 investigates the simultaneous wireless information and power transfer (SWIPT) for network-coded two-way relay network from an information-theoretic perspective, where two sources exchange information via an SWIPT-aware energy harvesting (EH)relay. We present a power splitting (PS)-based two-way relaying (PS-TWR) protocol by employing the PS receiver architecture. To explore the system sum rate limit with data rate fairness, an optimization problem under total power constraint is formulated. Then, some explicit solutions are derived for the problem. Numerical results show that due to the path loss effect on energy transfer, with the same total available power, PS-TWR losses some system performance compared with traditional non-EH two-way relaying, where at relatively low and relatively high signal-to-noise ratio (SNR), the performance loss is relatively small. Another observations is that, in relatively high SNR regime, PS-TWR out-performs time switching-based two-way re-laying (TS-TWR) while in relatively low SNR regime TS-TWR outperforms PS-TWR. It is also shown that with individual available power at the two sources, PS-TWR outperforms TS-TWR in both relatively low and high SNR regimes.

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.

To understand the network response to large-scale physical attacks, we investigate the asymptotic capacity of a half-duplex fading relay network with random node failures when the number of relays N gets infinitely large. In this paper, a simplified independent attack model is assumed where each relay node fails with a certain probability. The noncoherent relaying scheme is considered, which corresponds to the case of zero forward-link channel state information (CSI) at the relays. Accordingly, the whole relay network can be shown equivalent to a Rayleigh fading channel, where we derive the ε-outage capacity upper bound according to the multiple access (MAC) cut-set, and the ε-outage achievable rates for both the amplify-and-forward (AF) and decode-and-forward (DF) strategies. Furthermore, we show that the DF strategy is asymptotically optimal as the outage probability ε goes to zero, with the AF strategy strictly suboptimal over all signal to noise ratio (SNR) regimes. Regarding the rate loss due to random attacks, the AF strategy suffers a less portion of rate loss than the DF strategy in the high SNR regime, while the DF strategy demonstrates more robust performance in the low SNR regime.

This paper investigates the impact of different linear processing techniques on the outage performance of dual-hop amplify-and-forward (AF) relaying systems with co-channel interference (CCI) at the multiple antenna relay. Specifically, three heuristic linear precoding schemes are proposed to combat the detrimental effect of CCI, namely, 1) Maximum ratio combining/maximal ratio transmission (MRC/MRT), 2) Zero-forcing/MRT (ZF/MRT), 3) Minimum mean-square error/MRT (MMSE/MRT). New exact outage expressions as well as simple high signal-to-noise ratio (SNR) outage approximations are derived for all three schemes. Our results demonstrate that while the MRC/MRT and the MMSE/MRT schemes achieve a full diversity order of N, the ZF/MRT scheme can only achieve a diversity order of N-M, where N is the number of relay antennas and M is the number of interferers. In addition, it is observed that the MMSE/MRT scheme always achieves the best outage performance. The ZF/MRT scheme outperforms the MRC/MRT scheme in the low SNR regime, and exhibits an inferior performance compared to the MRC/MRT scheme in the high SNR regime.

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.

This paper addresses the performance analysis of an adaptive wireless link with one antenna transmitter and a multiple antenna maximum-ratio combining (MRC) receiver. Two main assumptions are used in this paper: (1) Rayleigh fading correlated channels (i.e., MRC branch correlation) and (2) imperfect (outdated) channel state information at the transmitter (CSIT) side. The main contribution of this work lies in the derivation of analytic expressions (in terms of a series expansion) of the statistics of correct packet reception conditional on the decisions made by the transmitter based on outdated CSIT. The novelty of this derivation is the joint modelling of spatially correlated branches, imperfect CSIT, and adaptive modulation based on threshold-trigger decision. Contrary to common belief, the results presented here suggest that spatial correlation not always affects the performance of the MRC receiver: at low signal-to-noise ratio (SNR), correlation can improve performance rather than degrading it. In contrast, at high SNR, correlation is found to always degrade performance. At high SNR, correlation tends to worse the degrading effects of imperfect CSIT, particularly when the number of antennas increases. Imperfect CSIT causes errors in the assignment of MCSs, thus reducing throughput performance. These errors become more evident in the high SNR regime, particularly when the values of branch correlation and the number of antennas increase.

Rolling bearings constitute indispensable components within rotating machinery, where unforeseen failures precipitate substantial economic losses and critical safety risks. This study introduces BFD-Net, an innovative deep learning paradigm engineered for robust bearing fault detection (BFD), surmounting the inherent difficulties posed by intricate operational conditions, pervasive noise interference, and the extraction of discriminative features from unprocessed data. At its nucleus lies a Cross-Modal Fusion (CMF) module, which adeptly amalgamates temporal attributes of raw vibration sequences with spectral signatures derived from Short-Time Fourier Transform (STFT), augmented by a bidirectional multi-head attention mechanism to capture intricate inter-modal dependencies. These synthesized features are subsequently refined through a Long Short-Term Memory (LSTM) network for temporal dynamics modeling and a hierarchical backbone, integrating convolutional and hybrid blocks, to encapsulate multi-scale characteristics. Given the profound influence of fluctuating noise levels in industrial settings on detection efficacy, we strategically embedded Signal-to-Noise Ratio (SNR) metadata into the Case Western Reserve University (CWRU) dataset, simulating noise conditions spanning -10dB to 8dB, thereby fortifying the model's resilience. Empirical validation on this enriched dataset underscores BFD-Net's superior performance, achieving an accuracy of 92.27 % with remarkable robustness across low SNR (-10dB to -2dB) and high SNR (0dB to 8 dB) regimes, surpassing extant methodologies.

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