Optimal Power Allocation and Precoding Design for Channel Estimation in OFDM System

It is well known that traditional water-filling provides a closed form solution for capacity maximization in orthogonal frequency division multiplex (OFDM) system. In this paper, cooperative power allocation is investigated in a two-transmitter multi-receiver model for OFDM systems. The local full channel state information (CSI) is available at the two transmitters respectively, where each transmitter has an individual power constrain. The transmitters first cooperate by sharing CSI, and then jointly optimize power allocation in the metric of sum throughput, which can be modeled as a convex optimization problem. Through an application of Karush-KuhnTucker (KKT) conditions, the convex optimization problem is reformulated as a simplified convex one. Then the closed form solution is derived, which takes a form similar to classic waterfilling principle. Based on the solution, the optimal cooperative power allocation algorithm is constructed, the structure of which can be explained as a cooperative water-filling relative to the traditional water-filling. Finally, numerical simulation is given to evaluate and demonstrate the performance of the optimal cooperative water-filling scheme.

This paper deals with channel estimation for orthogonal frequency-division multiplexing (OFDM) systems with transmit diversity. Space time coded OFDM systems, which can provide transmit diversity, require perfect channel estimation to improve communication quality. In actual OFDM systems, training sequences are usually used for channel estimation. The authors propose a training based channel estimation strategy suitable for space time coded OFDM systems. This novel strategy provides enhanced performance, high spectrum efficiency and relatively low computation complexity.

A major disadvantage of the orthogonal frequency division multiplexing (OFDM) system is the large dynamic range of its time-domain waveforms, making OFDM vulnerable to nonlinearities (including clipping effects) of the power amplifier (PA). The effects are nonlinear distortions as well as low DC to RF power conversion efficiency. The peak-to-average power ratio (PAR) is commonly used to characterize a signal's dynamic range. In the recent literature, the distribution of the PAR of OFDM signals is revealed to be dependent on the power allocation among subcarriers. In this paper, the effect of different power allocation schemes on the power efficiency of peak-power constrained OFDM transmitters is investigated. Optimization problems are formulated to determine the optimal power allocation with respect to the power efficiency, power consumption and system throughput performance in AWGN channels.

Channel estimation and synchronization are considered the most challenging issues in Orthogonal Frequency Division Multiplexing (OFDM) system. OFDM is highly affected by synchronization errors that cause reduction in subcarriers orthogonality, leading to significant performance degradation. The synchronization errors cause two issues: Symbol Time Offset (STO), which produces inter symbol interference (ISI) and Carrier Frequency Offset (CFO), which results in inter carrier interference (ICI). The aim of the research is to simulate Comb type pilot based channel estimation for OFDM system showing the effect of pilot numbers on the channel estimation performance and propose a modified estimation method for STO with less number of pilot to mitigate ISI effect. Channel estimation is simulated for different pilot number with 16QAM modulation in Ped-A Rayleigh channel. The STO effect assumed less than the cyclic prefix length to minimize ISI and maintain the orthogonality between subcarriers. The simulation results show that the high number of pilots are needed to achieve good channel estimation in case no synchronization used while similar results are achieved with smaller number of pilots if the propose modification on the synchronization method are used aligned with the channel estimation. The proposed system is evaluated in terms of BER and SNR.

In this paper, we consider out-of-band radiations caused by high sidelobes in orthogonal frequency division multiplexing (OFDM) system. Suppression of sidelobes in OFDM system allows higher spectral efficiency and less interference with existing legacy systems in OFDM based overlay system. We combine different sidelobe suppression techniques to suppress the sidelobes in OFDM system. The multiple-choice sequence (MCS) is combined with cancellation carriers (CCs) and also MCS is combined with subcarrier weighting (SW) technique. MCS is applied prior to CCs or SW techniques. Simulation results show that combining MCS with CCs and MCS with SW techniques the sidelobes in OFDM system can be significantly reduced, which allow a successful co-existance between OFDM overlay system and an existing legacy system.

This paper analyzes and compares two time interpolators, i.e., time replica and time linear interpolator, for pilot aided channel estimation in orthogonal frequency division multiplexing (OFDM) systems. The mean square error (MSE) of two interpolators is theoretically derived for the general case. The equally spaced pilot arrangement is proposed as a special platform for these two time interpolators. Based on this proposed platform, the MSE of two time interpolators at the virtual pilot tones is derived analytically; moreover, the MSE of per channel estimator at the entire OFDM symbol based on per time interpolator is also derived. The effectiveness of the theoretical analysis is demonstrated by numerical simulation in both the time-invariant frequency-selective channel and the time varying frequency-selective channel.

ABSTRACTWhile inter-symbol interference is not of concern, inter-carrier interference that is caused by carrier frequency offset (CFO) is more concerned in orthogonal frequency division multiplexing (OFDM) systems. The estimation of channel impulse response (CIR) is another important parameter of interest in the system. Recently, a number of approaches for the joint estimation of CFO and CIR in OFDM systems have been proposed in the literature, and most of them are traditional maximum-likelihood-based approaches. In this paper, we propose a number of mixture cost-reference particle filtering (CRPF) approaches for joint estimation of CIR and CFO, and a couple of them can be applied without the knowledge of both state and measurement noise statistics. Conventional least mean squares algorithm or recursive least squares algorithm is jointly employed with recently developed CRPF for nonlinear and multiple parameters estimation in OFDM systems. The computer simulation results show that mixture CRPFs are more robust against particle impoverishment (PI) problem than standard mixture particle filtering (PF) and mixture regularized PF (RPF) approaches although RPF was particularly developed to tackle the PI problem. In this paper, we investigate a number of mixture PF approaches including ones that do not need the information of noise statistics for the joint estimation of CFO and channel in OFDM systems.

This paper investigates the optimal precoder design and power allocation between the source and relay for a half-duplex single-relay non-orthogonal amplify-and-forward (NAF) system. Based on the pair-wise error probability (PEP) analysis, an optimal class of 2 × 2 precoders is first derived for the traditional power allocation scheme, where one-third of the system power is spent at the relay node, while two-thirds are spent at the source node. Different from optimal unitary precoders proposed earlier, the derived class of precoders indicates that the source should spend all its power transmitting a superposition of the symbols in the broadcast phase, while being silent in the cooperative phase, for optimal asymptotic performance. We then further address the problem of jointly optimal precoder and power allocation for the system under consideration. It is shown that the total power should be equally distributed to the source and the relay, and the source should again spend no power during the cooperative phase for the best asymptotic performance. Analytical and simulation results reveal that the proposed precoders not only exploit full cooperative diversity, but also provide significant coding gain over the optimal unitary precoders. For instance, a coding gain of around 1dB can be attained at the practical BER level of 10 − 5 for various modulation schemes.

Orthogonal frequency division multiplexing (OFDM) systems suffer from high sidelobes level. In some applications, as cognitive radios, this phenomenon can be a serious matter. This paper proposes Minimum shift keying (MSK)-OFDM to address this problem. The proposed method is an OFDM system using MSK modulation in each subcarrier. The corresponding transmitter and receiver are introduced. The method doesn't entail great changes in the main parts of OFDM. Like OFDM systems, the transceiver can be implemented using DFT/IDFT. Simulation results show great reduction in out of band radiation in comparison with conventional OFDM.

Channel estimation is a critical component in orthogonal frequency division multiplexing (OFDM) systems for ensuring reliable wireless communication. In this study, we propose a fast super-resolution convolutional neural network (FSRCNN) model for channel estimation, designed to reduce computational complexity while maintaining high estimation accuracy. The proposed FSRCNN model incorporates modifications such as replacing linear interpolation with zero padding and leveraging a new fast CNN architecture to estimate channel coefficients. Our numerical experiments and simulations demonstrate that the FSRCNN model significantly outperforms traditional methods, such as least square (LS) and linear minimum mean square error (LMMSE), in terms of mean square error (MSE) across various signal-to-noise ratios (SNRs). Specifically, the FSRCNN model achieves MSE values comparable to MMSE estimation, particularly at higher SNRs, while maintaining lower computational complexity. At an SNR of 20 dB, the FSRCNN model shows a notable improvement in MSE performance compared to the ChannelNet and LS methods. The proposed model also demonstrates robust performance across different SNR levels, with optimal results observed when the training SNR is close to the operating SNR. These findings validate the effectiveness of the FSRCNN model in providing a low-complexity, high-accuracy alternative for channel estimation, making it suitable for real-time applications and devices with limited computational resources. This advancement holds significant promise for enhancing the reliability and efficiency of current and future wireless communication networks.

A Krylov subspace based low-rank channel estimation in OFDM systems

This study deals with pilot-aided multi-path channel estimation for orthogonal frequency division multiplexing (OFDM) systems under slow to moderate fading conditions. Some algorithms exploit the channel time-domain correlation by using Kalman filters (KFs) to track the channel multi-path complex amplitudes (CAs), assuming a primary acquisition of the delays. Recently, it was shown that less complex algorithms, based on a second-order Complex Amplitude Tracking Loop (CATL) structure and a Least-Square (LS) pilot-aided error signal, can also reach near optimal asymptotic mean-squared error (MSE) performance. The LS-CATL-based algorithms are inspired by digital Phase-Locked Loops (PLL), as well as by the “prediction-correction” principle of the KF (in steady-state mode). This paper sums up and extends our previous results for the tuning and steady-state performance of the LS-CATL algorithm: analytic formulae are given for the first-, second-, and third-order loops, usable here for the multi-path multi-carrier scenario, and adaptable to any Doppler spectrum model of wide-sense stationary channels.

In this paper, optimal power allocation is investigated for maximizing the secrecy rate of orthogonal frequency division multiplexing (OFDM) systems under arbitrarily distributed input signals. Considering the discrete inputs are used in practical systems rather than the commonly assumed Gaussian inputs, we focus on secrecy rate maximization under more practical finite discrete constellations in this paper. It is known that the secrecy rate achieved by Guassian distributed inputs is concave with respect to the transmission power. However, we prove that the secrecy rate of finite discrete constellations is non-concave, which makes traditional convex optimization methods not applicable to our problem. To address this non-concave power allocation problem, we propose an efficient power allocation algorithm. Its gap from optimality vanishes asymptotically at the rate \(O(1/\sqrt{N})\), and its complexity grows in order of O(N), where N is the number of sub-carriers. Numerical results are provided to illustrate the benefits and significance of the proposed algorithm.

Multi carrier modulation is Orthogonal Frequency Division Multiplexing (OFDM), dividing the large band spectrum into small (narrow) band spectrum.OFDM offers flexibility in adaptation to time varying channel condition by adopting the parameters at each subcarrier accurately.Due to the multipath effect the OFDM system suffers Inter Symbol Interference (ISI).ISI can be reduced by introducing the guard band (cyclic prefix).Time-varying channel estimation is an important activity in next generation wireless communication.Channel estimation is required mainly for the significant signal processing operation in multiple input multiple output MIMO-OFDM systems.In this project DFT -based channel estimation based on block type arrangement is implemented in MAT Lab.The bit error rate (BER) of DFT (Discrete Fourier Transform)based channel estimation is less than the BER of LS (Least Square) and MMSE (Minimum Mean Square Error) based channel estimation with same signal to noise ratio (SNR).

To reduce the complexity involved in decision-directed channel estimation (DDCE) in orthogonal frequency-division multiplexing (OFDM) systems with transmit diversity, both data decoupling and direct cancellation of inter-antenna interference (IAI) suffer from residual IAI caused by channel frequency selectivity and time selectivity. In this paper, we propose a new algorithm to improve the performance of low complexity DDCE in OFDM systems with transmit diversity. The proposed algorithm includes a new data decoupling scheme with weaker assumptions regarding channel frequency response, and residual IAI cancellation using the results of the DDCE. Simulation results demonstrate that the proposed algorithm improves the performance of MSE and BER considerably.