Fractional Carrier Frequency Offset Research Articles

Efficient Maximum Likelihood Algorithm for Estimating Carrier Frequency Offset of Generalized Frequency Division Multiplexing Systems

This study presents a computationally efficient maximum likelihood (ML) algorithm for estimating the carrier frequency offset (CFO) of generalized frequency division multiplexing systems. The proposed algorithm uses repetitive subsymbols and virtual carriers to estimate the fractional and integer CFOs, respectively. Through the use of repetitive subsymbols, this study first calculates the ML estimate of the fractional CFO in the time domain and then, accordingly, compensates for it from the received signal. The integer CFO can then be estimated through a virtual-carrier-mapping process in the frequency domain. In addition to improving performance in terms of estimation accuracy and computational complexity, the proposed non-data-aided algorithm is spectrally efficient relative to traditional algorithms.

Throughput analysis of frequency-domain contention under realistic conditions for hyperautomation

ABSTRACT Internet of Things (IoT) has widely been deployed in various industrial fields. To achieve hyperautomation in IoT-based applications, it calls for high-efficient wireless transmission technologies to improve the response speed of IoT nodes. Frequency-domain contention (FDC) is a promising contention-based channel access mechanism to meet this requirement. However, the nature of FDC’s multiple-transmission-multiple-reception and the limit of IoT chip’s synchronization accuracy will lead to carrier frequency offset (CFO) and hence frequent transmission collisions and null transmissions. Considering integer and fractional CFO, this paper theoretically analyzes the FDC throughput and verifies the accuracy of our model via extensive simulations.

Design of a Blind Estimation Technique of Carrier Frequency Offset for a Universal-Filtered Multi-Carrier System Over Rayleigh Fading

This letter proposes a blind and simple estimation technique of carrier frequency offset (CFO) for a universal-filtered multi-carrier (UFMC) system under specified carrier assignment. The estimation design is divided into a fractional part and an integer part. In particular, by utilizing the characteristic of auto-correlation functions, the proposed scheme only needs a single UFMC symbol and a few complex multiplications to achieve fractional CFO estimation. Furthermore, the integer CFO is selected from the admissible candidates that minimize the frequency response of the frequency-compensated signal corresponding to the specified null subcarriers. The proposed CFO estimation does not require the aid of pilot symbols, and is easy to implement. Its achievable performance is quantified by our derived closed-form expression of the mean-square error of the proposed fractional CFO estimation. The computer simulation results verify the effectiveness and reliability of the proposed approach that does not require an exhaustive frequency search method.

Efficient carrier frequency offset estimation algorithm for generalized frequency division multiplexing systems

This paper presents an efficient carrier frequency offset (CFO) estimation algorithm for generalized frequency division multiplexing (GFDM) systems. The proposed algorithm formats the preamble into multiple identical subsymbols, and then decimates the received signal in the time domain to estimate the fractional CFO through array signal processing. After compensating for the fractional CFO, the proposed algorithm uses a low-complexity searching process to estimate the integer CFO in a maximum likelihood. The proposed algorithm presents some distinctive features: (1) it provides the full range of frequency acquisition region (FAR), which was considerably larger than that provided by many existing algorithms whose FAR was limited to one subcarrier spacing; (2) the proposed algorithm can use a single subsymbol to estimate the integer CFO by using the searching process of stepsize 1, significantly reducing its computational complexity; and (3) the decimation of the received signal ensures the proposed algorithm a power gain in fractional CFO estimation, resulting in an improved estimation accuracy compared with conventional algorithms.

Robust OFDM-Based Synchronization Against Very High Fractional CFO and Time-Varying Fading

This article investigates the advantages and disadvantages of cell search for LTE and NR. This investigation enables us to design a couple of synchronization signals specified in frequency domain for a whole of cell search. For time/frequency synchronization and partial cell identification, to achieve both low complexity and robustness against very high carrier frequency offset (CFO) and time-varying fading, we propose a primary synchronization signal generated by the centrally symmetric concatenation of a Zadoff-Chu sequence and its modified sequence. Also, for final cell identification, to minimize intercell interference, we propose a secondary synchronization signal constructed by element-wise exclusive-OR operation of two different cyclic-shifted m-sequences. By complexity, intercell interference analysis, and accuracy-optimized searching description, as well as cell-search evaluation, we elucidate that the proposed scheme provides many advantages, such as lower complexity, immunity toward CFO and mobility, and shorter mean cell search time directly related with latency and battery life.

Synchronization for LTE-A System Downlink: A Proposed Novel Method Used at LTE Wireless Communications

This article presents a synchronization method for the LTE system to determine time offset (TO) and fractional carrier frequency offset (FCFO) in multipath fading channels. With coarse and fine detection steps, the proposed TO estimation method exhibits better mean-squareerror performance and at least 80% lower computational complexity than conventional methods. The proposed method can detect the channel length and uses the undistorted cyclic prefix region to detect FCFO. Results show that the proposed FCFO detection method performs better than conventional methods.

ID Insertion and Data Tracking with Frequency Offset for Physical Wireless Parameter Conversion Sensor Networks.

As the applications of the internet of things are becoming widely diversified, wireless sensor networks require real-time data reception, accommodation of access from several sensors, and low power consumption. In physical wireless parameter conversion sensor networks (PhyC-SN), all the sensors use frequency shift keying as the modulation scheme and then access the channel to the fusion center, simultaneously. As a result, the fusion center can recognize the statistical tendency of all the sensing results at a time from the frequency spectrum of the received signal. However, the information source, i.e., the sensor, cannot be specified from the received signal because no ID-indicating sensor is inserted to the signal. The data-tracking technique for tracing the time continuity of the sensing results is available for decomposing the sequence of the sensing results per sensor but the error tracking, which is a wrong recognition between the sensing results and the sensor, occurs owing to the similarity of the sensing results. This paper proposes the sensing result separation technique using a fractional carrier frequency offset (CFO) for PhyC-SN. In the proposed scheme, the particular fractional CFO is assigned to each user and it is useful for the ID specifying sensor. The fractional CFO causes inter-carrier interference (ICI). The ICI cancellation of the narrowband wireless communications is proposed. The two types of data-tracking techniques are proposed and are selectively used by the fusion center. Since the proposed data-tracking technique is multi-dimensional, high accuracy of data tracking is achieved even under the similar tendency of the sensing results. Based on computer simulation, we elucidate the advantage of the proposed sensing results separation.

Maximum‐likelihood synchronization and channel estimation with multiuser detection in GFDMA

AbstractAccurate estimation and correction of channel distortions and carrier frequency offset (CFO) are of a great importance in any multicarrier communication system. Hence, in this paper, we propose data‐aided CFO and channel estimation techniques for both multiuser uplink and downlink of the generalized frequency division multiple access (GFDMA). Our proposed solutions jointly estimate the CFO and channel responses based on the maximum‐likelihood criterion. To simplify the implementation of the proposed estimation algorithms, we suggest a preamble composed of two similar Zadoff‐Chu training sequences in a generalized frequency division multiplexing block. It is worth mentioning that our proposed technique can estimate both integer and fractional CFO values without any limitation on the acquisition range of CFO. In the uplink phase, each user aligns its carrier frequency with the base station using the estimated CFO in the downlink. However, the CFO estimates may get outdated for the uplink transmission. Thus, residual CFOs may still remain in the received signal at the base station. While being trivial in the downlink, CFO correction is a challenging task in the uplink. Thus, we also propose a joint CFO correction and channel equalization technique for the uplink of GFDMA systems. Finally, we evaluate our proposed estimation and correction algorithms in terms of estimation mean square error and bit error rate performance through simulations.

A Hardware-Efficient Synchronization in L-DACS1 for Aeronautical Communications

L-band digital aeronautical communication system type-1 (L-DACS1) is an emerging standard that aims at enhancing air traffic management by transitioning the traditional analog aeronautical communication systems to the superior and highly efficient digital domain. L-DACS1 employs modern and efficient orthogonal frequency-division multiplexing (OFDM) modulation technique to achieve more efficient and higher data rate in comparison to the existing aeronautical communication systems. However, the performance of OFDM systems is very sensitive to synchronization errors such as symbol timing offset (STO) and carrier frequency offset (CFO). STO and CFO estimations are extremely important for maintaining orthogonality among the subcarriers for the retrieval of information. This paper proposes a novel efficient hardware synchronizer for L-DACS1 systems that offers robust performance at low power and low hardware resource usage. Monte Carlo simulations show that the proposed synchronization algorithm provides accurate STO estimation as well as fractional CFO estimation. Implementation of the proposed synchronizer on a widely used field-programmable gate array (FPGA) (Xilinx xc7z020clg484-1) results in a very low hardware usage which consumed 6.5%, 3.7%, and 6.4% of the total number of lookup tables, flip-flops, and digital signal processing blocks, respectively. The dynamic power of the proposed synchronizer is below 1 mW.

Carrier Frequency Offset Estimation for CO-OFDM: The Matched-Filter Approach

This paper proposes a novel carrier frequency offset (CFO) estimator for the coherent optical orthogonal frequency-division multiplexing (CO-OFDM) systems using the matched-filter (MF) concept. We consider an OFDM symbol with $N$ subcarriers so that the receiver takes $N$ time samples of the received noisy CO-OFDM signal. Our idea is to first append these $N$ received samples with $(L-1)N$ zeros at the end to get a sequence of $LN$ time samples. By taking the discrete Fourier transform of these $LN$ samples, we compute the spectrum of the CO-OFDM symbol at $LN$ discrete frequency points. We think of this spectrum as being made up of $L$ sets of $N$ points each, each set consisting of the frequency points $\lbrace \frac{2\pi }{LN}l, \frac{2\pi }{LN}l+\frac{2\pi }{N}, \ldots, \frac{2\pi }{LN}l+\frac{2\pi (N-1)}{N}\rbrace$ , for each value of $l$ , where $l=0,1,\ldots,L-1$ . Each set of $N$ points for one value of $l$ can be considered as the spectrum of the CO-OFDM symbol corresponding to one hypothesized value $\frac{2\pi }{LN}l$ of the CFO. The receiver can now obtain the maximum likelihood (ML) CFO estimate by determining the hypothesized value that best matches the spectrum of the CO-OFDM symbol received from the channel. In the case of data-aided (DA) ML estimation, we treat the OFDM symbol as a pilot symbol in which we know the data in all the subcarriers, and this pilot symbol is used as the reference signal for the MF. In the case of blind (BL) ML estimation, the data in all the subcarriers are unknown, and the receiver uses an OFDM symbol with no data modulation in all the subcarriers as the reference signal. After making the ML decision of the hypothesized value of the CFO, a fine search will be carried out to determine the actual value more accurately. It turns out only one step is necessary to locate the actual value of the CFO. The DA MF ML algorithm can achieve full-range (integral and fractional part) CFO estimation with high accuracy, while the BL MF ML algorithm has low computational complexity but focuses on the fractional CFO estimation only. We discuss the complexity and performance of this MF ML algorithm, and present simulation results to demonstrate the estimation error variance for 16-PSK/QAM modulations. The simulation results show that the estimation error variance of the DA MF ML algorithm can achieve the Cramer–Rao lower bound in the absence of the laser phase noise.

Maximum Likelihood Frequency Estimation and Preamble Identification in OFDMA-based WiMAX Systems

In multi-cellular WiMAX systems based on orthogonal frequency-division multiple-access (OFDMA), the training preamble is chosen from a set of known sequences so as to univocally identify the transmitting base station. Therefore, in addition to timing and frequency synchronization, preamble index identification is another fundamental task that a mobile terminal must successfully complete before establishing a communication link with the base station. In this work we investigate the joint maximum likelihood (ML) estimation of the carrier frequency offset (CFO) and preamble index in a multicarrier system compliant with the WiMAX specifications, and derive a novel expression of the relevant Cramer-Rao bound (CRB). Since the exact ML solution is prohibitively complex in its general formulation, suboptimal algorithms are developed which can provide a reasonable trade-off between estimation accuracy and processing load. Specifically, we show that the fractional CFO can be recovered by combining the ML estimator with an existing algorithm that attains the CRB in all practical scenarios. The integral CFO and preamble index are subsequently retrieved by a suitable approximation of their joint ML estimator. Compared to existing alternatives, the resulting scheme exhibits improved accuracy and reduced sensitivity to residual timing errors. The price for these advantages is a certain increase of the system complexity.

Robust and Efficient OFDM Synchronization for FPGA-Based Radios

Orthogonal frequency division multiplexing (OFDM) is a popular modulation technique that can combat impulsive noise, is robust to multipath fading, is spectrally efficient, and can allow flexible allocation of spectrum. It has become a key standard in cognitive radio systems as well as an enabling technology for mobile data access systems. An OFDM receiver's performance is heavily impacted by the accuracy of its symbol timing offset (STO) and carrier frequency offset (CFO) estimation. This paper proposes a novel OFDM synchronization method that combines robust performance with computational efficiency. FPGA prototyping is used to explore the trade-off between the number of computations to be performed and computation word length with respect to both synchronization performance and power consumption. Through simulation, the proposed method is shown to provide accurate fractional CFO estimation as well as STO estimation in a range of channels. In particular, it can yield excellent synchronization performance in the face of a CFO that is larger than many state-of-the-art synchronization implementations can handle. The system implementation demonstrates efficient resource usage and reduced power consumption compared with existing methods, and this is explored as a fine-grained trade-off between performance and power consumption. The result is a robust method suitable for use in low-power radios, enabling less precise analog front ends to be used.

Baseband Transceiver Design of a High Definition Radio FM System Using Joint Theoretical Analysis and FPGA Implementation

Advances in wireless communications have enabled various technologies for wireless digital communication. In the field of digital radio broadcasting, several specifications have been proposed, such as Eureka-147 and digital radio mondiale (DRM). These systems require a new spectrum assignment, which incurs heavy cost due to the depletion of the available spectrum. Therefore, the in-band on-channel (IBOC) system has been developed to work in the same band with the conventional analog radio and to provide digital broadcasting services. This paper discusses the function and algorithm of the high definition (HD) radio frequency modulation (FM) digital radio broadcasting system. Content includes data format allocation, constellation mapping, orthogonal frequency division multiplexing (OFDM) modulation of the transmitter, timing synchronization, OFDM demodulation, integer and fraction carrier frequency (integer carrier frequency offset (ICFO) and fractional CFO (FCFO)) estimation, and channel estimation of the receiver. When we implement this system to the field programmable gate array (FPGA) based on a hardware platform, both theoretical and practical aspects have been considered to accommodate the available hardware resources.

An OFDM Carrier Frequency Offset Estimation Scheme with Wide Fractional Offset Estimation Range

In this paper, we propose a carrier frequency offset (CFO) estimation scheme which is robust to the fractional CFO variation for orthogonal frequency division multiplexing (OFDM) systems. The proposed scheme first performs the envelope equalization process to convert the offset estimation problem to a carrier estimation problem, and then, estimates the integer and fractional parts of CFO by using periodogram of the received signal. Especially, in the estimation stage for fraction CFO, the ratio of the square-roots of periodograms is employed enlarging the estimation range of the stage than that of the conventional scheme. Numerical results demonstrate that the proposed scheme has better estimation performance than the conventional scheme for wider fractional CFO range in various channel conditions.

Time and Frequency Synchronization for Multicarrier Transmission on Hexagonal Time-Frequency Lattice

In this paper, a novel synchronization acquisition approach, including preamble structure, time and frequency synchronization algorithms, is proposed for hexagonal multicarrier transmission (HMCT) system. Specifically, a novel signal acquisition scheme based on time-frequency subspace projection (TFSP) and its simplified form are proposed for reliable signal acquisition. Time and frequency synchronization is divided into three steps: 1) the coarse time offset (TO) and coarse fractional carrier frequency offset (CFO) estimation; 2) fine TO and integer CFO estimation; and 3) fine fractional CFO estimation. The closed-form Cramér-Rao lower bound of the proposed CFO estimation scheme is given. Theoretical analyses and simulation results show that the proposed preamble structure, time and frequency synchronization algorithms for HMCT system can obtain robust performance over doubly dispersive (DD) channel, and the simulation results show excellent agreement with theoretical analyses.

Carrier Frequency Offset Estimation for OFDM Direct-Conversion Receivers

We investigate the problem of carrier frequency offset (CFO) recovery in an OFDM direct-conversion receiver plagued by both dc-offset and frequency-selective I/Q imbalance. In order to enlarge the frequency acquisition range, the CFO is divided into an integer part, which is multiple of the subcarrier spacing, plus a remaining fractional part. The fractional CFO is firstly estimated by resorting to the least-squares (LS) principle using a suitably designed training sequence. Since the exact LS solution requires a complete search over the frequency uncertainty range, we propose a simpler scheme that dispenses from any peak-search procedure. We also derive an approximated closed-form expression of the estimation accuracy that reveals useful for assessing the impact of various design parameters on the system performance. After computing the fractional CFO, the integer frequency error is eventually retrieved by following a weighted LS approach. Numerical simulations and theoretical analysis indicate that the proposed scheme can be used to obtain accurate CFO estimates with affordable complexity.

Multiple Invariance MUSIC-Based Blind Carrier Frequency Offset Estimation for OFDM System with Multi-Antenna Receiver

In this paper, we address the problem of carrier frequency offset (CFO) estimation for orthogonal frequency division multiplexing (OFDM) systems with multi-antenna receiver. The received signal can be reconstructed to form data model with multi-invariance property, and then a multi-invariance MUSIC algorithm for CFO estimation is proposed. This algorithm has better performance of CFO estimation than ESPRIT method, multi-invariance ESPRIT method and trilinear decomposition algorithm, and also qualifies the estimation for both integer CFO and fractional CFO. Simulation results illustrate validity of this algorithm.

A Practical Scheme for Frequency Offset Estimation in MIMO-OFDM Systems

This paper deals with training-assisted carrier frequency offset (CFO) estimation in multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. The exact maximum likelihood (ML) solution to this problem is computationally demanding as it involves a line search over the CFO uncertainty range. To reduce the system complexity, we divide the CFO into an integer part plus a fractional part and select the pilot subcarriers such that the training sequences have a repetitive structure in the time domain. In this way, the fractional CFO is efficiently computed through a correlation-based approach, while ML methods are employed to estimate the integer CFO. Simulations indicate that the proposed scheme is superior to the existing alternatives in terms of both estimation accuracy and processing load.

Frequency Offset Estimation and Training Sequence Design for MIMO OFDM

This paper addresses carrier frequency offset (CFO) estimation and training sequence design for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems over frequency selective fading channels. By exploiting the orthogonality of the training sequences in the frequency domain, integer. CFO (ICFO) is estimated. With the uniformly spaced non-zero pilots in the training sequences and the corresponding geometric mapping, fractional CFO (FCFO) is estimated through the roots of a real polynomial. Furthermore, the condition for the training sequences to guarantee estimation identifiability is developed. Through the analysis of the correlation property of the training sequences, two types of sub-optimal training sequences generated from the Chu sequence are constructed. Simulation results verify the good performance of the CFO estimator assisted by the proposed training sequences.

Carrier Frequency Offset Estimation for OFDM Systems with Null Subcarriers

An accurate estimation of carrier frequency offset (CFO) is a crucial task for orthogonal frequency-division multiplexing (OFDM) systems but should be performed with affordable computational complexity for practicality. In this paper, the authors derive two new estimation algorithms (one for the integer part and the other for the fractional part of CFO), each of which utilizes only one OFDM block with null subcarriers but offers improved accuracy and reduced complexity. The proposed estimator for fractional CFOs operates iteratively and is insensitive to the initial CFO. The other proposed estimator for integer CFOs employs a pseudonoise binary random sequence to assist in subcarrier arrangement and accurate estimation of the integer CFO. To demonstrate the efficiency of the proposed methods, numerical results are provided from computer simulation and analysis, and comparisons are made with other existing methods in the literature