Pilot Pattern Research Articles

New design of pilot patterns for joint semi-blind estimation of CFO and channel for OFDM systems

The greatest threat to the OFDM system is the loss of orthogonality between subcarriers due to the carrier frequency offset (CFO) which results in significant performance degradation. In addition to this last problem was the effect of propagation over multipath fading channel. Hence, both the channel and the CFO need to be estimated and corrected at the receiver for subsequent symbol detection.A new joint semi-blind CFO and channel estimation method for OFDM systems operating in multipath fading channels is investigated in this paper. The proposed algorithms are based on virtual subcarriers (VSC) in one hand and on a new design of pilot patterns in OFDM blocks in other hand.We propose to use Newton–Raphson algorithm for the estimation of CFO that has a faster convergence and a lower complexity compared to similar estimators that not employed this algorithm.Finally, we derive the Modified Cramer–Rao bounds (MCRB) for semi-blind CFO and channel estimation to evaluate the performance bounds of the proposed methods for commonly encountered scenarios.The simulation results are given to verify the validity of the proposed methods.

Joint Pilot Power & Pattern Design for Compressive OFDM Channel Estimation

This letter investigates the deterministic design of pilot power and pattern for sparse channel estimation in OFDM systems based on minimizing the coherence of the DFT sub-matrix. It has been suggested that the pilot pattern forming a cyclic difference set (CDS) or almost difference set (ADS) is optimal. So, we proposed a deterministic procedure that jointly optimized for pattern and power of pilots as a solution. First, pilot patterns forming CDS/ADS were gathered through a search. Then, the power was numerically allocated to the different pilots from all the patterns. Finally, the pilot pattern and power pair leading to minimum coherence was selected from the available pairs. Simulation results demonstrated that the proposed scheme outperformed the existing methods in terms of efficiency.

Co-Channel and Adjacent Channel Interference and Protection Issues for DVB-T2 and IEEE 802.22 WRAN Operation

This paper presents a study on the coexistence issue of digital terrestrial TV broadcasting and cognitive broadband access operation in the TV white spaces (TVWS). Extended measurements were performed to evaluate the protection of the existing Second generation of digital video broadcasting terrestrial standard (DVB-T2) services in the presence of IEEE 802.22 WRAN co-channel and adjacent channel interference. The absence of picture failure over 30 consecutive seconds on decoded DVB-T2 streams has been monitored to obtain the maximum tolerable level of IEEE 802.22 WRAN interference, which ensures the protection of the primary broadcast system. This paper considers practical DVB-T2 system configuration options by varying parameters of the standard, such as constellation and code rate, FFT size, pilot pattern and guard interval, and rotated constellations and compares them in terms of robustness with respect to the interference generated by IEEE 802.22 WRAN operation. The goal is to provide cognitive broadband operators in the TVWS with guidelines to optimize their network by choosing the parameters that best fit their needs in case of coexistence with DVB-T2 broadcasting services.

Large size FFTs over time‐varying channels

In orthogonal frequency division multiplexing (OFDM) signals, the usage of large size fast Fourier transforms (FFTs) reduces the guard interval percentage, and therefore increases the data throughput reducing the data overhead. In addition, for the same pilot pattern, the distance between adjacent pilots is smaller, which will improve the channel estimation. Nevertheless, up to now, they have not been considered for delivering mobile services as the inter-carrier interference (ICI) due to the Doppler effect is very critical. The main objective is to show that taking advantage of the latest improvements in error correction techniques, it is feasible to use large size FFTs for time-varying channels. Furthermore, there is also presented a theoretical estimation for quantifying the loss due to the ICI, and finally several simulation results that reinforce the idea that large OFDM symbols are suitable for mobile channels.

An Improved Technique of Channel Estimation for OFDM in DVB-T2

Orthogonal Frequency Division Multiplexing (OFDM) with pilot assisted channel estimation is widely applied in wireless communication systems due to its high rate transmission capability and its robustness to multi-path fading and delay. In this paper an improved channel estimation method for OFDM in second generation Digital Video Broadcasting for Terrestrial (DVB-T2) is presented based on a pilot arrangement in time-varying frequency-selective fading channels. A new method which is based on an improved Domain Transform Least Square Estimation method (DTLSE) and a Two Dimensional Interpolation method (2-DI) have been proposed. The proposed methods give a good BER performance compared to other considered methods .The estimation matrix size for obtaining Channel Impulse Response (CIR) depends only on the length of the channel not on the number of pilot subcarriers nor the size of OFDM symbol, it does not require knowledge of channel statistics and works for any pilot pattern. The Minimum Mean Squared Error (MMSE) channel estimation was considered as the reference method that gives the best BER performance but suffers from a high computational load. The proposed method is compared with the two other methods: the improved DTLSE and MMSE. The proposed method proves to give a reduction in complexity compared to the MMSE technique with a comparable performance but better than the DTLSE one. General Terms Pilot-assisted channel estimation, wireless systems, DVB-T2.

Impact of pilot pattern on carrier frequency recovery for TETRA‐like multitone modulations

A study of maximum-likelihood pilot-aided frequency offset recovery for filtered multitone modulations such as that employed in the TETRA Release 2 Enhanced Data Service is presented. An approach is proposed to improve on previously published algorithms. When pilot symbols are arranged on a rectangular time–frequency grid, as envisaged by the cited standard, the acquisition range of a pilot-based frequency synchroniser may seem to be very narrow as it cannot exceed the inverse of pilot spacing in the time-domain. It is shown that the above drawback can be relieved by resorting to a pilot pattern where the pilot symbols are simply shifted in time along the subcarriers with respect to the rectangular arrangement.

Channel Estimation and Combining Orthogonal Pilot Design in MIMO-OFDM System

The current technology of high speed wireless communication exist the following weaknesses, limited bandwidth, bad transmitted channel, complex mobile environment and the quality of service under limited service time. The dispersing pilot pattern and the method of channel estimation using in MIMO-OFDM system couldn’t eliminate the same frequency interference caused by the OFDM frequency among different transmit-receive antenna couples. Aiming at these problems, we proposed a method of MIMO-OFDM channel estimation combining orthogonal pilot design. The data format of pilot is designed. It can retain the orthogonality of different sub-carriers of OFDM which are produced by different transmit-receive antenna couples or transmit-receive antenna couple. In wireless mobile environment, it can better estimate the channel parameters without any prior channel information. This method proposed in the paper has finished the design of the completely orthogonal pilot data symbol among the different subcarriers position of different transmitting-receiving antenna pair. And the pilot data symbols are distributed in the entire time-frequency grid of the channel reasonably, therefore this paper uses a FFT unit whose points are equal to the number of the OFDM subcarriers to realize the least-square channel estimation algorithm. In the process of channel estimation, the channel parameters estimation precision has increased because of the noise getting better inhibition, which reduces the least squares estimate noise sensitivity to the requirements

Pilot Design for Sparse Channel Estimation in OFDM-Based Cognitive Radio Systems

In this correspondence, sparse channel estimation is first introduced in orthogonal frequency-division multiplexing (OFDM)-based cognitive radio systems. Based on the results of spectrum sensing, the pilot design is studied by minimizing the coherence of the dictionary matrix used for sparse recovery. Then, it is formulated as an optimal column selection problem where a table is generated and the indexes of the selected columns of the table form a pilot pattern. A novel scheme using constrained cross-entropy optimization is proposed to obtain an optimized pilot pattern, where it is modeled as an independent Bernoulli random process. The updating rule for the probability of each active subcarrier selected as a pilot subcarrier is derived. A projection method is proposed so that the number of pilots during the optimization is fixed. Simulation results verify the effectiveness of the proposed scheme and show that it can achieve 11.5% improvement in spectrum efficiency with the same channel estimation performance compared with the least squares (LS) channel estimation.

Channel Correlation Estimation Exploiting Pilots for an OFDM System with a Comb-Type Pilot Pattern

Channel Correlation Estimation Exploiting Pilots for an OFDM System with a Comb-Type Pilot Pattern

Robust Pilot-aided Frequency Offset Estimation Scheme for OFDM-based Broadcasting System with Cyclic Delay Diversity

This paper proposes an improved carrier frequency offset (CFO) and sampling frequency offset (SFO) estimation scheme for orthogonal frequency division multiplexing (OFDM) based broadcasting system with cyclic delay diversity (CDD) antenna. By exploiting a periodic nature of channel transfer function, cyclic delay and pilot pattern with a maximum channel power are carefully chosen, which helps to enable a robust estimation of CFO and SFO against the frequency selectivity of the channel. As a performance measure, a closed-form expression for the achievable mean square error of the proposed scheme is derived and is verified through simulations using the parameters of the digital radio mondiale standard. The comparison results show that the proposed frequency estimator is shown to benefit from properly selected delay parameter and pilot pattern, with a performance better than the existing estimator.

An Enhanced DFT-Based Channel Estimator for LTE-A Uplink

In this paper, we investigate the popular discrete Fourier transform (DFT)-based channel estimator (D-bCE) for Long-Term Evolution (LTE)-Advanced uplink. Due to limitations of the current pilot pattern, orthogonality among channels of multiple antennas at the time domain does not exactly hold. This degrades the performance of a conventional D-bCE severely. Therefore, we propose a novel enhancement of the D-bCE by using the frequency-domain weighting scheme. By analyzing the mean square error, we present a heuristic way to design weights and reformulate the resulting optimization into a second-order cone programming problem, which can be easily solved. The proposed scheme does not rely on the channel covariance matrix, and the weights can be generated offline. Thus, it is easy to use this scheme in practice. Simulation results validate the effectiveness of our proposed method.

Sparsity adaptive matching pursuit algorithm based on adaptive threshold for OFDM sparse channel estimation

In order to reduce the complexity of the reconstruction algorithm and improve the precision of estimation,the authors proposed a new Sparsity Adaptive Matching Pursuit(SAMP) algorithm by using the adaptive threshold applied in the OFDM(Orthogonal Frequency Division Multiplexing) sparse channel estimation.The Monte Carlo simulation results show that,compared with the traditional method,the CPU run time decreased by 44.7%.And in lower SNR(Signal-to-Noise Ratio),the performance achieved obvious improvements.Besides,in OFDM sparse channel estimation,a new design of pilot pattern was presented based on the mutual coherence of the measurement matrix in Compressive Sensing(CS) theory.The Monto Carlo simulation results show that,the precision of channel is increased by 2-4 dB with the new pilot pattern.

Channel Estimation for OFDM Systems over Doubly Selective Channels: A Distributed Compressive Sensing Based Approach

Channel estimation for an orthogonal frequency-division multiplexing (OFDM) broadband system over a doubly selective channel is very challenging. This is mainly due to the significant Doppler shift, which results in a time-frequency doubly-selective (DS) channel. The DS channel features a large number of channel coefficients, which introduces inter-carrier interference (ICI) and forces the need for allocating a large number of pilot subcarriers. To tackle this problem, in this paper we propose a novel channel estimation scheme based on distributed compressive sensing (DCS) theory. Taking advantage of the basis expansion model (BEM) and the channel sparsity in the delay domain, we transform the original DS channel into a novel two-dimensional channel model, where several jointly sparse BEM coefficient vectors become the estimation goal. Then a special decoupling form originating from a novel sparse pilot pattern is designed for such estimation, which results in an ICI-free structure and enables the DCS application to make joint estimation of these vectors accurately. Combined with a smoothing treatment process, the proposed scheme can achieve significantly higher estimation accuracy than the existing ones, although with a much smaller number of pilot subcarriers. Theoretical analysis and simulation results both confirm its performance merits.

Pilot Allocation for Sparse Channel Estimation in MIMO-OFDM Systems

The frequency-selective channel-estimation problem in multi-input-multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems is investigated from the perspective of compressed sensing (CS). By minimizing the mutual coherence of the measurement matrix in CS theory, two pilot allocation methods for the CS-based channel estimation in MIMO-OFDM systems are proposed. Simulation results show that using the pilot patterns designed by the two proposed methods gives a much better performance than using other pilot patterns in terms of the mean square error of the channel estimate as well as the bit error rate of the system. Moreover, the optimal pilot patterns obtained by the proposed second method based on genetic algorithm and shift mechanism could offer a larger performance gain than those by the first method based on minimizing the largest element in the mutual coherence set possessed by pilot patterns for all multiple antenna ports.

Adaptive Pilot-Symbol Patterns for MIMO OFDM Systems

Recent standards for cellular transmission systems offer a lot of flexibility, such as the choice of transmission modes, modulation alphabets, coding rates, and precoding matrices. Despite this trend, pilot-symbol patterns in today's standards remain fixed, although such an approach is suboptimal. In this paper, we show how to design optimal pilot-symbol patterns by maximizing an upper bound of a constrained capacity that takes channel estimation errors and Inter Carrier Interference into account. Furthermore, we propose adaptive pilot-symbol patterns that follow changing channel statistics. As a proof of concept, we present throughput simulation results of two competitive systems, a transmission system compliant with the Long Term Evolution (LTE)-standard and an improved system utilizing the proposed adaptive pilot patterns. The transmission system utilizing adaptive pilot patterns outperforms an LTE-standard compliant system in all considered scenarios. The throughput gain for a single input single output system ranges between 3% and 80%. For a 4 × 4 transmission system, the performance gain is significantly higher and can reach up to 850% compared to a conventional LTE system.

A low complexity DFT-matrix based pilot allocation algorithm for sparse channel estimation in OFDM systems

The accuracy of channel estimation is very important for Orthogonal Frequency Division Multiplexing (OFDM) systems. In a high speed wideband wireless communication, the channel can be modeled as a sparse one. Therefore, the Compressed Sensing (CS) technique can be used for the estimation of the channel. In this paper, the problem of deterministic pilot allocation in OFDM systems is considered and a new criterion which is based on minimizing the summation of the correlations between the columns of the Discrete Fourier Transform (DFT) sub-matrix is proposed. It will be shown that the proposed criterion is a simple version of the well-known but complex criterion, Restricted Isometry Property (RIP). In addition, the pilot pattern design, using our proposed scheme, indicates better recovery performance than other proposed coherence based criteria in terms of the reconstruction mean square error (MSE) and successful channel recovery percentage. Simulation results confirm our analysis.

Scattered pilot-based channel estimation with joint noise reduction for PDM-CO-OFDM system

To improve the accuracy of the channel estimation in PDM-CO-OFDM system when LS algorithm is used, a joint denoising method is proposed in this paper. We have theoretically proposed and simulated designed scattered pilot pattern for PDM-CO-OFDM system, then multi-wavelet is used to denoise the LS channel estimation results which have been interpolation in frequency domain, ISFA is further used to denoise signals after interpolation in time domain. Simulation results show that for 4-QAM, 80GB/s PDM-CO-OFDM system, the proposed joint denoising method has improved 0.96dB in OSNR sensitivity at the BER of 1e−3 (threshold of FEC) compared to the common LS method and reduced system overhead at the same time.

Empirical DVB-T2 Thresholds for Fixed Reception

This paper provides minimum C/N values for correct reception of DVB-T2 signals under fixed reception conditions. The C/N values are obtained after analyzing the results of field and laboratory trials. The field measurements were taken in a middle-sized city, along 33 locations, with MFN and SFN configurations. Both the system configuration options (constellation and code rate, FFT size, pilot pattern, and rotated constellations) and the propagation channel are taken into account to quantify their influence on the reception requirements. DVB-T was also measured and both systems are compared. The final objective is to provide the broadcasters with some guides based on measurements to optimize the DVB-T2 networks by choosing the parameters that best fit their needs.

Pilot Symbol Parameter Optimization Based on Imperfect Channel State Prediction for OFDM Systems

The optimization of pilot symbol parameters can improve the spectral efficiency of adaptive modulation for orthogonal frequency division multiplexing (OFDM) systems, since pilot symbols impose an overhead on the system consuming power and bandwidth. An optimal pilot symbol assisted adaptive modulation (PSAAM) scheme for OFDM systems is proposed that maximizes spectral efficiency by adapting the power and constellation size of each subcarrier based on employing imperfect channel state information (CSI) at the transmitter. The pilot symbol power and spacing is also optimized in this scheme. A suboptimum scheme that decreases computational complexity without perceivable loss in performance is also presented. The optimality of minimum mean square error (MMSE) channel prediction for OFDM systems expressed in terms of a lower bound on spectral efficiency is approached. It is proved that the rectangular pilot pattern with equi-spaced and equal power pilot tones achieves the minimum MSE of the channel prediction in addition to having the advantage of simplifying PSAAM design. Numerical results show the importance of optimal pilot parameter adjustment for rapidly fading channels.

Investigation on Key Technologies in Large-Scale MIMO

Large-scale MIMO (multiple-input multiple-output) systems with numerous low-power antennas can provide better performance in terms of spectrum efficiency, power saving and link reliability than conventional MIMO. For large-scale MIMO, there are several technical issues that need to be practically addressed (e.g., pilot pattern design and low-power transmission design) and theoretically addressed (e.g., capacity bound, channel estimation, and power allocation strategies). In this paper, we analyze the sum rate upper bound of large-scale MIMO, investigate its key technologies including channel estimation, downlink precoding, and uplink detection. We also present some perspectives concerning new channel modeling approaches, advanced user scheduling algorithms, etc.