Efficient Phase-Error Suppression for Multiband OFDM-Based UWB Systems

In orthogonal frequency division multiplexing (OFDM) systems, most of the conventional sampling frequency offset (SFO) estimation methods work under the assumption of time-invariant or slow time-variant channels. In mobile environment, the time-variant channel significantly degrades the accuracy of SFO estimation. To solve the problem, we first analyze the properties of time-variant channels. If terminal moves within some tens of the wavelength of radio frequency (RF) signal, channel path delay almost remains unchanged. For most practical OFDM systems, our analysis indicates that channel path delay can be regarded as unchanged during the interval of some tens of OFDM symbols in time-variant channels. Based on the analysis, we propose a novel SFO estimation method for pilot-aided OFDM systems. Different from the conventional methods, the proposed method estimates SFO by detecting the variation of the symbol timing error caused by SFO. The detection is finished by implementing correlation between the channel impulse responses (CIRs) estimated by different OFDM symbols. Performance of the proposed method is simulated and compared with that of two conventional post-FFT methods. Numerical results show that, the proposed SFO estimation method performs better than the conventional methods not only in time-variant channels, but also at low SNRs and large residual carrier frequency offsets (CFOs).

A pilot-aided scheme is proposed for the joint estimation and tracking of channel impulse response (CIR), carrier frequency offset (CFO) and sampling frequency offset (SFO) in burst mode, multiple-input-multiple-output (MIMO), and orthogonal frequency division multiplexing(OFDM) systems. First, a received signal model that takes into account nonlinear CFO/SFO effects is formulated. Then, based on the derived signal model and the received multicarrier signal samples containing the pilot tones in the frequency domain, an objective function that includes MIMO CIR, CFO, and SFO is introduced to develop a vector recursive-least-square (RLS)-based joint channel estimation and synchronization algorithm. The analysis and simulation results show that, over the large ranges of the CFO and SFO values, the proposed estimation and tracking scheme offers fast convergence, high stability, and a near-optimum receiver performance that is remarkably close to the ideal performance in the case of perfect channel estimation and synchronization over quasi-static Rayleigh multipath fading channels.

A successive interference cancellation (SIC)-based weighted least-squares (WLS) estimation for the carrier frequency offset (CFO) and the sampling frequency offset (SFO) is presented for wireless local area networks (WLANs) based on orthogonal frequency division multiplexing (OFDM). The proposed SIC-based WLS performs the estimation by exploiting the phase rotation in the frequency domain caused by the CFO and the SFO. SIC-based WLS estimates the CFO and the SFO successively instead of by traditional simultaneous estimation. The estimation of CFO based on the Taylor series is performed first, and then the WLS estimation of SFO based on successive cancellation of the CFO is carried out. The simulation results show that the SIC-based WLS can estimate the CFO and the SFO effectively. Compared to the WLS scheme, a performance improvement of more than 0.6 dB is achieved by SIC-based WLS, and nearly 10 percent of the complexity is reduced.

This study proposes an efficient channel-estimation scheme for Multiband (MB) Orthogonal Frequency Division Multiplexing (OFDM)-based Ultra Wide Band (UWB) communication systems. One of the challenges in wireless system is the frequency selective fading caused due to multipath channel between the transmitter and receiver. The signal bandwidth in broad band cellular wireless systems typically exceeds the coherence bandwidth of the multipath channel. To overcome such a multipath fading environment with low complexity and to increase the performance, UWB OFDM system is used. To practically realize MB-OFDM UWB, one needs to cope with numerous design challenges, particularly in receiver designs such as symbol timing, Carrier Frequency Offset (CFO) and sampling frequency offset compensation, as well as Channel Frequency Response (CFR) estimation. A channel estimation scheme using a Takagi-Sugeno (T-S) fuzzy based neural network under the time varying velocity of the mobile station in a UWB OFDM system is proposed in this study. In our proposal, by utilizing the learning capability of Adaptive Neuro-Fuzzy Inference System (ANFIS), the ANFIS is trained with correct channel state information then the trained network is used as a channel estimator. To validate the performance of our proposed method, simulation results are given and found that it gives more accurate prediction of channel coefficients as compared with fuzzy channel estimator under various highly noisy multipath channel conditions.

A multiband orthogonal frequency-division multiplexing (MB-OFDM) system, which is one of the effective modulation techniques that have been adopted for high-speed ultrawideband (UWB) systems, is very sensitive to sampling frequency offset (SFO) due to the mismatch between local oscillators at the transmitter and the receiver. In this paper, we propose an iterative SFO estimation method for a high-data-rate MB-OFDM UWB system to improve its SFO estimation accuracy in the case of a long transmission packet. The proposed method is an iterative process of 2-D SFO estimation across pilot subcarriers and consecutive OFDM symbols, together with joint channel estimation. Furthermore, we derive the Cramer-Rao lower bound (CRLB) for the proposed SFO estimation method. This CRLB can be used as a guide for algorithm design and to explore the theoretical limit. Our performance analysis and simulation results show that the proposed iterative SFO estimation method is both practical and effective.

This paper considers the problem of analytically assessing the maximum achievable rates (capacity) of orthogonal frequency division multiplexing (OFDM) transmissions when the receiver, for complexity reasons, only accounts for the common phase error (CPE) effect due to phase noise impairments with inter-carrier interference (ICI) treated as noise. By recognizing that the functional form of the CPE with respect to the phase noise realization is actually a free design parameter, determination of the capacity is posed as a functional optimization problem with respect to the, so-called, CPE function. A simple lower bound of the capacity is obtained, revealing the performance degradation due to the unknown CPE at the receiver, as well as the suboptimal performance achieved in severe phase noise conditions by the conventional CPE function that is routinely employed in previous works. The existence of an optimal number of subcarriers that balances the effects of the (unknown) CPE and ICI is highlighted and critical system design/operation issues, such as selection of the CPE function and effect of unknown channel on the achievable rate, are discussed. The analysis in this paper can be employed for determining the suitability of OFDM in phase noise channels and provides a tractable utility function for resource allocation purposes.

Carrier frequency offset (CFO) and phase noise are challenging problems in single carrier frequency division multiple access (SC-FDMA) system. In this study, the authors have studied single-carrier space frequency block coding (SC-SFBC) to reduce the peak to average power ratio (PAPR) of the multiple-input multiple-output (MIMO) SC-FDMA signal, in which Alamouti SFBC will change the signal spectrum structure, break the single-carrier property and increase PAPR. Also, the authors propose a joint algorithm to suppress the inter-carrier interference (ICI) caused by phase noise and CFO. Conventional methods are to estimate phase noise and CFO in other algorithms, which are pretty difficult and complicated to obtain accurate estimation results. Unlike the conventional works, the novelty of the authors proposed algorithm is that it directly calculates the interference components and then reconstructs the ICI matrix. Thus, it avoids the degrading interactions between phase noise and CFO estimations. The proposed algorithm exploits block-type pilot, which is a common pilot pattern in SC-FDMA communications and is used in other wireless communication standards. Simulation results show that the suppression performance keeps smooth while phase noise and CFO varies, and BER performance degradation can be significantly reduced in 3 dB.

On the basis of the analysis of the effect of PHase Noise (PHN) and Common Phase Error (CPE) on Orthogonal Frequency Division Multiplexing (OFDM) systems, a cost function is constructed. By the cost function and the idea of Least-Mean-Square (LMS) adaptive algorithm, the adaptive algorithm for the correction of CPE is presented. The simulations have been performed to investigate the performance for tracking PHN and estimating CPE, the results show that the algorithm performs soundly.

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.

In this paper, a residual frequency offset (RFO) and sampling frequency offset (SFO) estimator is proposed for ultra- wideband multi-band orthogonal frequency division multiplexing (UWB MB-OFDM) systems. The proposed scheme uses a time-domain spreaded data samples which is provided in MB-OFDM system. To demonstrate the efficiency of the proposed RFO and SFO estimator, comparisons are made with other existing estimator.

In the 5G system, orthogonal frequency division multiplexing (OFDM) waveform survived for its superior performance. As is well known, OFDM systems are sensitive to the phase noise introduced by local oscillators and it may get worse for likely higher carrier frequency in 5G systems. There are two aspects of the impact of phase noise, namely the common phase error (CPE) and the inter-carrier-interference (ICI). In this paper, first, we propose a more accurate way to estimate CPE. Then, we focus on ICI cancellation. To simplify the ICI model, we only consider the interference from adjacent sub-carriers. Based on the simplified model, we propose two schemes to estimate ICI. The performance of phase noise compensation algorithm we proposed is presented. Simulation results show that the algorithm we proposed can significantly reduce the impact of phase noise and improve the throughput of 5G systems.

Non pilot data-aided carrier and sampling frequency offsets estimation in fast time-varying channel

A precise estimation of SFO (Sampling Frequency Offset) is an important issue in OFDM (Orthogonal Frequency Division Multiplexing) system. However, the conventional method causes serious performance degradation of SFO estimation in low SNR (Signal to Noise Ratio) or large Doppler frequency environment. Therefore, in this paper, we propose a SFO estimation method which can achieve stable operation in low SNR and large Doppler frequency environment. The proposals for SFO estimation /compensation are mainly based on DVB (Digital Video Broadcasting) system, and we verified that the proposed method has a good performance and stable operation through extensive simulation.

A precise estimation and compensation of SFO (Sampling Frequency Offset) is an important issue in OFDM (Orthogonal Frequency Division Multiplexing) system, because sampling frequency mismatch between the transmitter and the receiver dramatically degrades the system performance due to the loss of orthogonality between the subcarriers. However, the conventional method causes serious performance degradation of SFO estimation in low SNR (Signal to Noise Ratio) or large Doppler frequency environment. Therefore, in this paper, we propose two SFO estimation methods which can achieve stable operation in low SNR and large Doppler frequency environment. The proposals for SFO estimation / compensation are mainly specialized on DVB (Digital Video Broadcasting) system, and we verified that the proposed method has good performance and stable operation through extensive simulation.

Digital radio mondiale (DRM) is a terrestrial radio broadcasting standard to replace existing analogue AM and FM broadcasting, which is based on an orthogonal frequency division multiplexing (OFDM) technique. This paper focuses on the issue of estimating a sampling frequency offset (SFO) in OFDM-based broadcasting systems under frequency selective fading channels. In order to design a robust SFO estimation scheme and to benchmark its performance, the performance of the various conventional SFO estimation schemes is discussed and some improvements on the conventional estimation algorithms are highlighted. The simulation results show that such a design enhances the robustness of the proposed scheme against frequency selective fading.