Non-Orthogonal Golay-Based Spreading Sequences for Uplink Grant-Free Access

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.

For the novel channel estimation method using compressed sensing (CS), many strategies have been proposed for its performance improvements. Nevertheless, random sequences are usually used to construct sensing matrix, but it is difficult and expensive to be implemented in hardware, and may cause large Peak-to-Average Power Ratio (PAPR) in OFDM system. Consequently, in this paper, the method that to obtain deterministic sensing matrix by deterministic sequence named as Golay Complementary Sequence is detailed investigated. Golay sequence has the properties as perfect periodic auto-correlations, simultaneously realizing timing acquisition and channel estimation. Also PAPR can be limited within 3dB in OFDM system by the method. Simulation results show that the deterministic sensing matrix can offer reconstruction performance similar to random matrix.

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.

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.

The paper contains an analysis of the basic criteria for the selection of spreading sequences for the multi-carrier CDMA (MC-CDMA) systems with spectrum spreading in the frequency domain. It is shown that the time-domain crosscorrelation function between the spreading sequences is not a proper interference measure for the asynchronous MC-CDMA users. Therefore the spectral correlation function is introduced and, together with the peak-to-average power ratio (PAPR) and the dynamic range of the corresponding multi-carrier waveforms, is used for the evaluation of MC-CDMA sequences. Some well-known classes of sequences, such as Walsh and Gold sequences, as well as orthogonal Gold and Zadoff-Chu (1972) sequences, are evaluated with respect to the aforementioned basic criteria. It is also shown that the multi-carrier spread spectrum waveforms based on the (multilevel) Huffman sequences have the lower PAPR than a single sine wave.

Unique word (UW) OFDM is one of the alternative wave candidates for conventional OFDM for 5th Generation (5G) and beyond communication systems. Peak to average power ratio (PAPR) performance, which is one of the major disadvantages of conventional OFDM, is better in the UW-OFDM system. In this paper, the effects of different UW sequences such as Zadoff-Chu, CAZAC, PN, 0-word, 1-word and −1-word on PAPR performance of UW-OFDM systems are investigated. Computer simulation studies are carried out to compare the UW-OFDM waveform with the conventional OFDM and zero-tail discrete Fourier transform spread OFDM (ZT DFT-S OFDM) waveforms. The simulated results show that the UW-OFDM waveform has better PAPR performance than the conventional OFDM and ZT DFT-S OFDM waveforms. In particular, it is observed that UW-OFDM using Zadoff-Chu sequence has the best PAPR performance.

The generalized extreme value (GEV) distribution is suitable for modeling the extreme events, such as the maximum value of an asymptotic distribution. This paper presents results of an experimental investigation where the distribution of peak-to-average power ratio (PAPR) in downlink MC-CDMA systems is modeled by the GEV distribution. Two orthogonal sets of sequences, Walsh-Hadamard and Golay complementary sequences, are used in spreading processes in the system. Then the parameters of the GEV distribution are estimated for the PAPR distribution. Through intensive numerical results, it is shown that the GEV distribution is an accurate model of the PAPR distribution of MC-CDMA systems. Also, the statistically estimated GEV distribution parameters for the PAPR reveal that when the number of subcarriers increases, the PAPR distributions converge to the Gumbel distribution.

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.

This paper compares Single Carrier Frequency Division Multiplex (SC-FDM) with Orthogonal Frequency Division Multiplex (OFDM) for underwater acoustic communication. One of the drawbacks of OFDM transmission is the large variations in the instantaneous transmit power. This implies a reduced efficiency in power amplifiers and results in lower average power of the transmission signal. SC-FDM is utilized for 4G radio access technology such as Uplink communication of Long Term Evolution (LTE) in order to mitigate the above drawback of OFDM. Among the modulations in this communication system are QPSK, 16QAM and 64QAM. Zadoff-Chu sequence is used as Pilots for SC-FDM both for Channel Estimation and Phase Compensation of Doppler shift. Both Field Experiment at sea port in Okinawa, Japan and computer simulation show the quantitative merits of SC-FDM than OFDM. Peak-to-average Power Ratio (PAPR) of the transmitted signal has been successfully reduced by 1.5–2.0 dB for various modulations and roughly 50% of communication distance can be extended.

In this paper, we compare the performance between channel estimation based on compressed sensing (CS) and time-domain least square (LS) for single-carrier (SC) communication system. Unlike the conventional channel estimation techniques such as frequency domain LS which is used in the condition that the length of pilot sequence is equal to data sequence, the estimation scheme based on CS requires smaller length of pilot sequence. In this paper, the corresponding system structure is presented. Zadoff-Chu sequence is used to generate the pilot sequence, which is shown to perform better in forming measurement matrix of CS than pseudo random sequence. Simulation results demonstrate that channel estimation based on CS achieves a better bit error rate (BER) performance than time domain LS with a smaller pilot sequence and thus raising data rate of the SC communication system.

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

Grant-free access is an attractive approach to enable spectrum-efficient low-latency access for systems with massive number of users. Pilot design plays a crucial role for grant-free access as it needs to provide a large number of access codes with fast collision detection capability and good channel estimation performance. Recently, pilot designs with fast collision detection capability have been proposed for compressed sensing (CS) based channel estimation. But the existing designs are not optimized for the estimation of highly sparse and block-sparse channels. In this paper, we present several propositions related to the performances of the CS based sparse and block-sparse channel estimation. Utilizing these propositions, we develop a novel non-orthogonal pilot design with fast collision detection capability for grant-free access in block-sparse channels. We also propose two methods to optimize the Peak-to-Average Power Ratio (PAPR) of the proposed non-orthogonal pilot codes. The simulation results illustrate that the proposed design provides similar or better channel estimation and collision detection performances with much better pilot resource efficiency when compared to the existing designs. Finally, we investigate the trade-offs among different design parameters and the channel estimation performances to facilitate better design choices.

This paper describes a real-time implementation of the orthogonal frequency-division multiplexing (OFDM)-based system concatenated with super-orthogonal convolutional code (SOCC) and Golay complementary sequence using a software defined radio platform. The SOCC is a powerful low-rate channel code that guarantees low decoding latency and high reliability, and the use of Golay sequence ensures that the resulting signal peak-to-average power ratio (PAPR) is within 3 dB, which significantly improves the power amplifier efficiency. Comparison of bit error rate (BER) performance results demonstrates that the implemented system can approach the ideal performance suggested by computer simulation. We also report its performance after nonlinear power amplification through a testbed employing a real power amplifier device.