Frequency ambiguity free tiered differential‐polyphase codes for GNSS signal design

We evaluate the performance improvement in orthogonal frequency-division multiplex access (OFDMA) achievable with cooperative relaying in the presence of frequency offsets. The relays can operate in either the amplify-and-forward (AF) or decode-and-forward (DF) mode. In each transmission, node S has M relays when transmitting its own signal, and it also helps the other M relays transmit their signals. The total power used to transmit each symbol, including the power consumed in S and the relays, is kept constant. The outage information rates of the proposed cooperative transmission scheme are first derived. The performance improvement in the frequency offset estimation by using cooperative relay is then analyzed. Channel estimation in a cooperative OFDMA network in the presence of frequency offsets is also evaluated, and the pairwise error probability (PEP) of orthogonal space-time coding in cooperative OFDMA due to both the frequency offset and channel estimation errors is derived. Numerical results illustrate the superior performance of the proposed scheme over the conventional transmission with regard to outage information rate, frequency offset estimation error and the PEP.

In this paper, we propose a hybrid scheme for the carrier frequency offset (CFO) estimation in OFDM communication systems. The main novelty of the approach is the judicious combination of two methods so as to reduce the bandwidth overhead and computational complexity without compromising the estimation range. The cyclic prefix (CP) associated with the OFDM symbols are used for the fractional frequency offset estimation. The integer frequency offset is estimated by means of a cost function minimization employing a few null subcarriers, which are allocated using a modified Fibonacci series. Performance of the frequency offset estimator is mathematically analyzed by deriving the Cramer-Rao bound (CRB) and is compared with the mean square error performance of the estimator. For moderate SNRs, our algorithm is shown to outperform some existing methods in terms of MSE (and thereby BER) performance, training overhead and receiver complexity.

In this literature, we present a new method for estimating the coarse frequency offset in multi-band orthogonal frequency division multiplexing (MB-OFDM) based ultra-wideband (UWB) communication systems. The proposed training based coarse frequency offset (CFO) estimator performs an averaging of initial estimate over the multiple bands of transmission during estimation process. The proposed multi-band averaging provides an improved estimation of approximately three times for band group 1 (BG1) compared to our earlier proposed scheme. To prove the efficiency of the proposed scheme, the Cramer Rao lower bound (CRLB) of the estimation error is calculated and compared with the simulation results. We illustrate the performance of MB-OFDM system in terms of bit-error rate (BER) with multi-band averaged frequency synchronization (MBAFS) and compare with earlier reported results for 100,000 noisy realizations in UWB channel model 2 (CM2).

We consider joint estimation of carrier frequency offset and channel impulse response (CIR) for orthogonal frequency division multiplexing (OFDM) systems with pilot symbols and virtual subcarriers (VCs). We derive the receive-signal correlation structure due to the pilots and VCs, give the evidence of joint multivariate Gaussian distribution of the received samples, and derive an approximate maximum likelihood (ML) frequency offset estimator. We also derive the asymptotic mean-square error (MSE) and an approximate Cramer-Rao bound (CRB) and establish the asymptotic unbiasedness. Without pilots, in high signal-to-noise ratio, our estimator is equivalent to Liu and Tureli's estimator with Nv virtual carriers. When the pilot number (Np) is greater than the channel length L, our estimator acts as a subspace-based estimator with Nv + Np - L virtual carriers. A decision-directed joint ML estimator is derived to iteratively update the estimates of frequency offset, data symbols and CIR. The optimal pilot and virtual carrier placement strategies are also discussed. The resulting decision-directed joint estimator performs within 0.8 dB of the ideal case even when the frequency offset is as large as 20%

The estimation of carrier and sampling frequency offsets is considered, for IEEE 802.11a-based OFDM wireless LAN (WLAN) systems, based on the guard interval and two long symbols (GI2L) in the preamble of an OFDM WLAN packet. The model of the measurement of the GI2L is developed, in the presence of both carrier and sampling frequency offsets. Based on this model, a method is proposed, based on the GI2L. Improved performance, measured by estimation error and bit error rate, is achieved by the proposed method, as compared with some relevant existing methods.

Automatic Modulation Classification (AMC) is a critical technology in the field of non-cooperative communication. Carrier frequency offset is an inevitable impairment factor in communication systems, and it significantly affects the performance of AMC, especially when the range is large. Therefore, frequency offset estimation and compensation are essential for automatic modulation classification. To address this issue, this paper proposes an innovative cascading network based on deep learning, primarily comprising pre-classification and compensation mechanisms. With the pre-classification mechanism, we categorize the eleven unknown modulation formats into three major classes: PSK, FSK, and QAM. Subsequently, we utilize deep neural networks to estimate the frequency offset of signals within these major classes, followed by performing the corresponding signal compensation. The experimental results demonstrate that the pre-classification mechanism effectively reduces the error in frequency offset estimation, minimizing the error <Formula format="inline"><TexMath><?TeX $\log MSE$ ?></TexMath><File name="a00--inline1" type="gif"/></Formula> (mean-square error) to as low as -3.9. Under various signal-to-noise ratio (SNR) ranges, the classification accuracy achieved through pre-classification and compensation is up to 14% higher than the accuracy without this method. Specifically, at SNR = 10 dB, it can reach 99%. Moreover, the proposed scheme is robust and performs stably across different frequency offsets range, outperforming other existing network classification schemes to some extent.

An initial carrier frequency offset estimation algorithm is proposed for a multi-user frequency hopping orthogonal frequency division modulation-frequency division multiple access (FH-OFDMA) system with a single preamble symbol. Since a multi-user OFDMA system is sensitive to carrier frequency offset which causes interferences among users, data loaded in subcarriers are easily damaged by the frequency offset. To mitigate the effect of the frequency offset, every mobile station needs to accurately and rapidly acquire synchronization. The proposed algorithm uses only one preamble symbol in which two kinds of subcarriers are designed for coarse and fine frequency offset estimation. The non-data aided estimation using the energy spectrum is exploited for fine offset estimation, and maximum likelihood estimation using correlation for coarse offset estimation. By combining the two estimation results, an accurate frequency offset can be estimated with a single symbol. Through simulations, the performance of the proposed algorithm is evaluated by comparing estimation error variance with a conventional method.

The effect of IQ imbalance on the initial frequency offset estimation algorithm in an orthogonal frequency division multiplexing (OFDM) direct conversion receiver is studied. The impact of the phase and amplitude IQ imbalances and channel response on the frequency offset estimation is formulated for a flat channel case. Analysis of the IQ imbalance on the frequency offset estimation is provided and the results are presented in this paper. The results show that the frequency offset estimation algorithm generates an error in the estimated offset frequency with IQ imbalance and the error can be reduced by an appropriate choice of the correlation window length.

In this paper a frequency offset estimation technique for Wireless Local Area and Wireless Metropolitan Ar- ea Networks is presented. For frequency offset estimation, we have applied a low-complexity frequency offset estimator for simple AWGN channels to fading channels for MIMO-OFDM systems. Simulation results have shown that the performance of the proposed estimator is better than the low complexity frequency offset estimator designed for AWGN channels.

A new carrier frequency offset estimation scheme in orthogonal frequency division multiplexing (OFDM) is proposed. The scheme includes coarse frequency offset estimation and fine frequency offset estimation. The coarse frequency offset estimation method we present is a improvement of Zhang's method. The estimation range of the new method is as large as the overall signal-band width. A new fine frequency offset estimation algorithm is also discussed in this paper. The new algorithm has a better performance than the Schmidl's algorithm. The system we use to calculate and simulate is based on the high rate WLAN standard adopted by the IEEE 802.11 standardization group. Numerical results are presented to demonstrate the performance of the proposed algorithm

Low complexity joint time offset and frequency offset estimations for LTE uplink system

The single-carrier frequency-division multiple access (SC-FDMA) or the discrete Fourier transform (DFT) pre-coded orthogonal frequency-division multiple access (OFDMA) technique has been adopted in the uplink transmission of the long term evolution (LTE) terrestrial communication standard, for its lower peak-to-average power ratio (PAPR) and similar receiver complexity, compared with OFDM. It is, however, rarely investigated in underwater acoustic (UWA) communications. This paper presents an SC-FDMA transceiver scheme for multiple-input, multiple-output (MIMO) UWA communications, and studies the performance of turbo equalization on the receiver side. The signalling of the pilot symbols bypasses the DFT precoding module, so the channel estimation and the carrier frequency offset (CFO) estimation are performed in a similar way as in a conventional OFDM system. A recently proposed high-performance frequency-domain turbo equalization technique is adopted for detecting the data symbols, which suffer inter-symbol interference (ISI) due to the DFT spreading operation. Experimental results clearly show the performance gain attributed to the turbo equalization, especially for high-order modulations.

In recent years, the constant-envelope orthogonal frequency-division multiplexing (CE-OFDM) has been considered as a candidate waveform in broadband satellite systems as it has a 0-dB peak-to-average power ratio (PAPR). However, the carrier frequency offset (CFO) estimation scheme for CE-OFDM broadband satellite systems directly affects system performance. In this paper, we analyze the network architecture and the propagation environment of CE-OFDM broadband satellite systems, and we propose a data-aided CFO estimation strategy based on the frequency domain pilot symbols. The Cramer–Rao bound (CRB) of our CFO estimator is given by mathematical analysis, and the effect of the number of pilot symbols on the estimation performance is analyzed. The pilot symbol-based CFO estimator is composed of a phase demodulator and a discrete Fourier transform (DFT) module, and it can obtain a large estimation range under a small pilot overhead. The simulation results show that the CE-OFDM broadband satellite systems can achieve a good bit error rate (BER) performance by using the proposed strategy to estimate and compensate the CFO.

This paper deals with the problem of joint frequency offset (FO) and channel estimation for multi-input multi-output (MIMO) systems in the presence of a timing error. Two equivalent signal models with FO and a timing error are given, and then a joint estimation method is derived. The proposed estimation method consists of two steps. Firstly, a maximum likelihood (ML) FO estimator is proposed based on the second signal model. Secondly, based on the FO estimate, we formulate the timing error and channel estimation as a problem of composite hypothesis testing according to the first signal model, and then solve the problem using a composite hypothesis testing approach. Simulation results are performed to show the effectiveness of the proposed method.

We design a new kind of fractional Fourier transform superimposed training sequence (TS) to simultaneously estimate linear distortions including chromatic dispersion (CD), timing offset (TO), and frequency offset (FO), etc. Without sacrificing additional spectrum efficiency, the scheme can reduce the computational complexity sharply compared to a regular estimation method. The feasibility of the proposed scheme is verified by simulations of 28 GBaud dual polarization quadrature phase-shift keying (DP-QSPK) and 16-ary quadrature amplitude modulation (DP-16 QAM) system. Simulation results show that the superimposed TS has negligible negative effects on the transmission performance considering 7% forward error correction while the TO, FO, and rough CD estimation perform well after a long distance transmission. The max TO estimation (TOE) errors are, respectively, eight samples and 12 samples for QPSK and 16 QAM, and the max FO estimation errors are, respectively, 5.7 and 3.6 MHz for QPSK and 16 QAM. The rough CD estimation (CDE) error is below 946 ps/nm. The TOE and rough CDE separately decrease the complexity of frame synchronization and CDE. In total, the computation complexity of the estimations decreases by 91.8% compared to a regular blind estimation method.