Meixia Hu

A Piecewise Linear Companding Transform for PAPR Reduction of OFDM Signals With Companding Distortion Mitigation

Companding is a well-known technique for the peak-to-average power ratio (PAPR) reduction of orthogonal frequency division multiplexing (OFDM) signals. However, as companding transform is an extra operation after the modulation of OFDM signals, companding schemes reduce PAPR at the expense of increasing the bit error rate (BER). In this paper, a new piecewise linear companding scheme is proposed aiming at mitigating companding distortion. In the design of the companding transform, we study the theoretical characterization of companding distortion. It demonstrates that companding larger signals with smaller amplitude increments are more favorable in reducing companding distortion. Based on the analysis results, a new piecewise linear companding transform is proposed by clipping the signals with amplitudes over a given companded peak amplitude for peak power reduction, and linearly transforming the signals with amplitudes close to the given companded peak amplitude for power compensation. With the careful design of the companded peak amplitude and the linear transform scale, the proposed transform can achieve enhanced BER and power spectral density performance, while reducing PAPR effectively.

Parameter-adjustable piecewise exponential companding scheme for peak-to-average power ratio reduction in orthogonal frequency division multiplexing systems

High peak-to-average power ratio (PAPR) is a major drawback of orthogonal frequency division multiplexing (OFDM) systems. A new companding scheme is proposed to reduce PAPR by transforming the statistics of the companded signal into exponential distribution with adjustable parameters. The proposed scheme can enhance the bit error rate (BER) performance significantly by minimising the companding distortion in the reduction of PAPR. Moreover, with the introduction of an inflexion point and transform parameters, the proposed scheme can offer more flexibility in the PAPR reduction, and therefore achieves a better tradeoff among the PAPR reduction, BER and power spectral density (PSD) performance. With a theoretical analysis presented, the parameter selection criteria are derived. Simulation results verify that the proposed scheme can significantly improve the BER and PSD performance while reducing PAPR effectively.

A Low-Complexity Tone Injection Scheme Based on Distortion Signals for PAPR Reduction in OFDM Systems

Tone injection (TI) can effectively reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals without incurring data rate loss and extra side information. However, the optimal TI scheme requires an exhaustive search over all combinations of the possible perturbations of the expanded constellation over all perturbed subcarriers, which is not suitable for practical applications. To reduce the complexity while still achieving good PAPR performance, a low-complexity TI scheme based on distortion signals is proposed in this paper. Motivated by the goal of mitigating the distortions when OFDM signals pass high power amplifiers, we intuitively get the perturbation information for OFDM signals directly from the distortion signals. By exploiting the distribution of the perturbation vectors depending on the distortion signals, we design a search range limited extended constellation. Then, based on the statistical information of perturbed subcarriers, the number of the subcarriers to be perturbed is restricted. Moreover, to further reduce the complexity, we choose a proper subcarrier perturbation sequence from candidate subcarrier sets according to the mutual information between the peak sample and the distortion signals. With the selected subcarrier perturbation sequence, the original problem is decomposed into a sequential search problem, which provides a dramatic complexity reduction. Simulation results demonstrate that the proposed scheme can achieve significant complexity savings while maintaining a good PAPR performance.

A Low Complexity PAPR Reduction Method Based on FWFT and PEC for OFDM Systems

Orthogonal frequency division multiplexing (OFDM) is a multi-carrier modulation technique for transmitting large volumes of digital data but suffers high peak-to-average power ratio (PAPR) at the transmitter. In this paper, we propose a PAPR reduction technique based on the combination of a low complexity transform-Fast Walsh–Hadamard and Fourier transform (FWFT) and the parameter-adjustable piecewise exponential companding (PEC). To reduce algorithm complexity, FWFT uses a fast orthonormal unitary transform to calculate both the Walsh–Hadamard transform (WHT) and the discrete Fourier transform (DFT). In FWFT, WHT realizes precoding to OFDM signals and as a result the PAPR is reduced first. Moreover, the parameter-adjustable PEC transform is adopted to further reduce PAPR by transforming the statistics of the companded signal into exponential distribution with adjustable parameters. Simulation results show that the hybrid method achieves significant PAPR reduction and improves the BER performance of OFDM systems when used in multipath fading channels.

Computationally efficient fixed complexity LLL algorithm for lattice-reduction-aided multiple-input–multiple-output precoding

In multiple-input–multiple-output broadcast channels, lattice reduction (LR) preprocessing technique can significantly improve the precoding performance. Among the existing LR algorithms, the fixed complexity Lenstra–Lenstra–Lovasz (fcLLL) algorithm applying limited number of LLL loops is suitable for the real-time communication system. However, fcLLL algorithm suffers from higher average complexity. Aiming at this problem, a computationally efficient fcLLL (CE-fcLLL) algorithm for LR-aided (LRA) precoding is developed in this study. First, the authors analyse the impact of fcLLL algorithm on the signal-to-noise ratio performance of LRA precoding by a power factor (PF) which is defined to measure the relation of reduced basis and transmit power of LRA precoding. Then, they propose a CE-fcLLL algorithm by designing a new LLL loop and introducing new early termination conditions to reduce redundant and inefficient LR operation in fcLLL algorithm. Finally, they define a PF loss factor to optimise the PF threshold and the number of LLL loops, which can lead to a performance-complexity tradeoff. Simulation results show that the proposed algorithm for LRA precoding can achieve better bit-error-rate performance than the fcLLL algorithm with remarkable complexity savings in the same upper complexity bound.

Wishart-matrix based blind estimation of transmit-antenna number for non-collaborated MIMO systems

An accurate estimation of the transmit-antenna number is a prerequisite for blind signal detection in non-collaborated multiple-input multiple-output (MIMO) systems. This paper proposes a Wishart-matrixs largest eigenvalue (WME) based hypothesis testing algorithm for blind detecting the transmit-antenna number. By introducing the Random Matrix Theory (RMT), we can get a precise distribution of the Wishart matrixs largest eigenvalue. With this distribution, we can achieve a threshold which leads to a reliable estimation. A series of simulations show that under a wide range of conditions the proposed WME algorithm is superior over the algorithms based on Akaike information criterion (AIC), minimum description length (MDL) and predicted eigen-threshold (PET).

Tone Reservation to Minimize Nonlinearity Impact on OFDM Signals

To enhance the power efficiency of high-power amplifiers (HPAs) with the demand of reducing energy consumption, a tone reservation (TR) technique is adopted to make orthogonal frequency-division multiplexing (OFDM) signals less sensitive to nonlinearity of HPAs. In this paper, we attempt to minimize the sensitivity from the point of signal-to-noise ratio (SNR) loss at the receiver. Specifically, the nonlinearity impact on OFDM signals is evaluated by a normalized correlation coefficient (NCC) of amplifier input and output signals. With the introduction of the NCC, we model the design of TR as an optimization problem and propose an adaptive-scaling-based gradient-project approach. Simulation results show that, in terms of bit error rate (BER) and power spectral density (PSD) performance, our proposed approach is superior to conventional schemes.

Improved Cross-Entropy-Based Tone Injection Scheme With Structured Constellation Extension Design for PAPR Reduction of OFDM Signals

The application of the cross entropy (CE) method to tone injection (TI) can make the peak-to-average power ratio (PAPR) of the orthogonal frequency division multiplexing (OFDM) signals reduced efficiently with great complexity savings. However, as a population-based search method, the CE method requires large samples to find a high-quality solution, which means higher complexity and more time consuming concerning convergence. To reduce the complexity while achieving promising PAPR performance, an improved CE based TI scheme is proposed in this paper. First, a structured extended constellation for rectangular quadrature amplitude modulation is designed to provide more freedom degrees. With proper parameter selection, the proposed extended constellation can offer more design flexibilities and achieve a better tradeoff between freedom degree and power increase. Then, by analyzing the impact of the subcarrier candidate population on the conventional CE based TI scheme, we derive an explicit expression for the determination of the size of the subcarrier candidate population. And, based on the prior information carried by the clipping signal, proper candidate subcarriers are selected. Finally, an improved CE based TI scheme is proposed, which can efficiently enhance the solution quality and greatly accelerate the convergence speed. Simulation results demonstrate that the improved CE based TI scheme achieves great improvements on the performance of PAPR, bit error rate, power increase and complexity compared with the conventional CE based TI scheme.

Dual layer beamforming with limited feedback for full-dimension MIMO systems

Eigen-beamforming is an optimal beamforming scheme for full-dimension multi-input multi-output (FD-MIMO). However, it suffers from high complexity of the singular value decomposition (SVD) of the 3D channel matrix. In this paper, we propose a low complexity dual layer beamforming scheme to exploit both the horizontal and vertical degrees of freedom. The proposed scheme first segments the channel matrix into several sub-channel matrices. Then, by selecting the vertical and horizontal beamforming from the sub-channel matrices respectively, the proposed scheme can reduce the complexity, while achieving the performance approximate to the optimal eigen-beamforming scheme. Moreover, to enable practical implementation, a hybrid codebook design is proposed which exploits the structure of the dual layer beamforming to reduce feedback overhead. According to the different correlation characteristics in horizontal and vertical direction, we design different codebooks for the horizontal and vertical beamforming. Simulation results demonstrate that the proposed scheme can effectively improve the spectral efficiency of FD-MIMO systems with limited feedback, especially for the cell edge users.

Precoder Design for the Downlink of Multi-User MIMO Systems with Multiple Antenna Receiver

The paper considers precoder design for the downlink of multi-user MIMO systems where antenna array are used at both the base station and the mobile receiver. The proposed precoder does not completely eliminate multi-user interference (MUI) as previous schemes with multiple receive antennas per user, but obtains an optimum compromise between noise enhancement and MUI mitigation. Furthermore, by extracting diversity from each users subspace and reducing precoding loss, the proposed scheme can offer a significant gain in term of average bit error rate (BER).