In this letter, we propose an efficient algorithm for the detection of the integer carrier frequency offset (CFO) and sector identity used in the LTE cell search For the conventional LTE cell search, the integer CFO and sector identity are jointly detected by utilizing the primary synchronization signal (PSS) By exploiting the symmetric property of the PSS, the integer CFO can be solely detected without the knowledge of sector identity, and thus, the joint detection of the integer CFO and sector identity is decoupled Additionally, the proposed sequential integer CFO and sector identity detection (SISID) removes the effect of the channel frequency responses such that the detection accuracy is enhanced We also design the SISID hardware architecture where the parts of the signals are processed in the polar coordinate so that all the multiplications are realized by additions/subtractions The simulation results demonstrate that the proposed SISID achieves better detection accuracy than the conventional methods with only one third of the computational complexity

Efficient Sequential Integer CFO and Sector Identity Detection for LTE Cell Search

Frequency offset estimation is an important module in the synchronisation of underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) systems. Different ways are used for carrier frequency offset (CFO) estimation such as maximum likelihood based on a cyclic prefix. In this paper, the Zadoff-Chu (ZC) sequences are used for OFDM synchronisation in underwater communications. The normalised carrier frequency offset can be estimated using the ZC cross-correlation between the primary synchronisation signal and the corresponding local signal, which causes large complexity. The ZC sequences have a time centre symmetric property, and thus the autocorrelation of the received primary synchronisation signal can be used for frequency offset estimation. In this paper, we propose a modified algorithm with low complexity for frequency offset estimation. Simulation results demonstrate that the proposed algorithm can estimate the frequency offset accurately with simple implementation in compariso...

Carrier frequency offsets estimation in UWA-OFDM communication systems using Zadoff-Chu sequences

Joint low‐complexity equalization and CFO estimation and compensation for UWA‐OFDM communication systems

We introduce predictive communication algorithms for channel estimation and equalization in vehicular environments. The proposed concept makes use of vehicular sensors combined with unique properties of surrounding environment to predict future changes in the communication scenario. This combination enables a new range of improvements in the direct-link vehicular communications. Among others, it allows predicting the Doppler frequency shift for some strong channel components in highly dynamic scenarios and estimating the likelihood for the communicating vehicles to remain in the line-of-sight conditions. A predictive Doppler-shift compensation is presented as an illustrative example of one of potential benefits for future vehicular communications. The algorithm is applied to compensate the strong line-of-sight component as well as the line-of-sight with one strong reflection which is received at the same sampling interval. The obtained simulation results show that the proposed sensor-based Doppler-shift prediction and compensation approach outperforms a benchmark least-squares channel estimation with linear interpolation algorithm in various road scenarios (urban, rural, and highway) and relative driving directions (same and oncoming) of communicating vehicles.

Predictive Communication and Its Application to Vehicular Environments: Doppler-Shift Compensation

Cellular to air communication is critical for the booming aerial package delivery and transportation business. Detecting cellular signals in airborne applications is challenging because it requires receiving and processing waveforms that are subject to significantly more interference than those experienced in terrestrial settings. This paper highlights and tackles the complexity of 4G Long Term Evolution (LTE) signal synchronization in high altitude applications, e.g., cell access onboard an aircraft. Specifically, we design a novel cell detector that operates efficiently under high interference levels found in airborne applications, maintains a constant false alarm rate using an optimized threshold implementation for Zadoff Chu sequences, and monitors multiple towers with different time delays simultaneously. We validate our cell detector through simulation and experimentation. Lastly, the cell detector is used to estimate the interference in live waveforms taken from an aircraft at 2 to 2.5 km altitude and velocities of 200–400 km/h. Our cell detection model can be adapted to support 5G New Radio (NR) synchronization signals as NR deploys aerial support in the future. The threshold implementation to handle correlation spurs can be applied directly to other Zadoff Chu based signals such as random access signals found in both LTE and NR.

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Detection Algorithm for Cellular Synchronization Signals in Airborne Applications

Frequency offset estimation is an important module in the downlink synchronization process of orthogonal frequency division multiplexing (OFDM) system. Research on frequency synchronization of OFDM, a low-complexity and efficient method is proposed to evaluate frequency offset in this paper. In general, maximum likelihood (ML) based on cyclic prefix (CP) and primary synchronization signal (PSS) frequency-domain cross-correlation algorithm are applied for fractional carrier frequency offset estimation. PSS time-domain cross-correlation algorithm is used to estimate integral carrier frequency offset. However, for fractional carrier frequency estimation, the performance of ML based on CP degrades in fading channel. The complexity of the other algorithm is high. Also, the conventional integral carrier frequency estimation requires cross-correlation between the received PSS and local PSS or auto-correlation of received PSS, so they also have great complexity. In this paper, relying on the PSS time center-symmetric property, we perform PSS auto-correlation method twice in the time domain. Hence fractional carrier frequency offset is obtained and compensated. Next, relying on the PSS frequency center-symmetric property, we perform energy difference computations to estimate the integral carrier frequency offset, which is equal to the distance between the calculated minimum and the central frequency in frequency domain. Simulation results demonstrate that the proposed algorithm can estimate frequency offset accurately, guarantee the reliance and reduce complexity in comparison with the normal methods

Xiaowen Li

Papers

Low-Complexity Carrier Frequency Offset Estimation Algorithm in TD-LTE