Clipping is an efficient and simple method that can reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. However, clipping causes in-band distortion referred to as clipping noise. To resolve this problem, a novel iterative estimation and cancellation (IEC) scheme for clipping noise is one of the most popular schemes because it can significantly improve the performance of clipped OFDM systems. However, IEC exploits detected symbols at the receiver to estimate the clipping noise in principle and the detected symbols are not the sufficient statistic in terms of estimation theory. In this paper, we propose the post-processing technique of IEC, which fully exploits given sufficient statistic at the receiver and thus further enhances the performance of a clipped OFDM system as verified by simulations.

In recent years, there has been significant interest in information-theoretic security techniques that encrypt physical layer signals. We have proposed chaos modulation, which has both physical layer security and channel coding gain, as one such technique. In the chaos modulation method, the channel coding gain can be increased using a turbo mechanism that exchanges the log-likelihood ratio (LLR) with an external concatenated code using the max-log approximation. However, chaos modulation, which is a type of Gaussian modulation, does not use fixed mapping, and the distance between signal points is not constant; therefore, the accuracy of the max-log approximated LLR degrades under poor channel conditions. As a result, conventional methods suffer from performance degradation owing to error propagation in turbo decoding. Therefore, in this paper, we propose a new LLR clipping method that can be optimally applied to chaos modulation by limiting the confidence level of LLR and suppressing error propagation. For effective clipping on chaos modulation that does not have fixed mappings, the average confidence value is obtained from the extrinsic LLR calculated from the demodulator and decoder, and clipping is performed based on this value, either in the demodulator or the decoder. Numerical results indicated that the proposed method achieves the same performance as the one using the exact LLR, which requires complicated calculations. Furthermore, the security feature of the proposed system is evaluated, and we observe that sufficient security is provided.

This paper proposes a parallel peak cancellation (PC) process for the computational complexity-efficient algorithm called PC with a channel-null constraint (PCCNC) in the adaptive peak-to-average power ratio (PAPR) reduction method using the null space in a multiple-input multiple-output (MIMO) channel for MIMO-orthogonal frequency division multiplexing (OFDM) signals. By simultaneously adding multiple PC signals to the time-domain transmission signal vector, the required number of iterations of the iterative algorithm is effectively reduced along with the PAPR. We implement a constraint in which the PC signal is transmitted only to the null space in the MIMO channel by beamforming (BF). By doing so the data streams do not experience interference from the PC signal on the receiver side. Since the fast Fourier transform (FFT) and inverse FFT (IFFT) operations at each iteration are not required unlike the previous algorithm and thanks to the newly introduced parallel processing approach, the enhanced PCCNC algorithm reduces the required total computational complexity and number of iterations compared to the previous algorithms while achieving the same throughput-vs.-PAPR performance.

This paper proposes a computational complexity-reduced algorithm for an adaptive peak-to-average power ratio (PAPR) reduction method previously developed by members of our research group that uses the null space in a multiple-input multiple-output (MIMO) channel for MIMO-orthogonal frequency division multiplexing (OFDM) signals. The proposed algorithm is an extension of the peak cancellation (PC) signal-based method that has been mainly investigated for per-antenna PAPR reduction. This method adds the PC signal, which is designed so that the out-of-band radiation is removed/reduced, directly to the time-domain transmission signal at each antenna. The proposed method, referred to as PCCNC (PC with channel-null constraint), performs vector-level signal processing in the PC signal generation so that the PC signal is transmitted only to the null space in the MIMO channel. We investigate three methods to control the beamforming (BF) vector in the PC signal, which is a key factor in determining the achievable PAPR performance of the algorithm. Computer simulation results show that the proposed PCCNC achieves approximately the same throughput-vs.-PAPR performance as the previous method while dramatically reducing the required computational cost.

This letter deals with an audio declipping problem and proposes a multiple matrix rank minimization approach. We assume that short-time audio signals satisfy the autoregressive (AR) model and formulate the declipping problem as a multiple matrix rank minimization problem. To solve this problem, an iterative algorithm is provided based on the iterative partial matrix shrinkage (IPMS) algorithm. Numerical examples show its efficiency.

We investigate through simulation simultaneous linear and nonlinear impairments using a realistic reconfigurable optical add drop multiplexer (ROADM) model while considering optical filtering and in-band coherent crosstalk at each ROADM and the nonlinear interfering effects from neighbor superchannels with the QPSK or 16QAM modulation format.

This letter deals with the signal declipping algorithm based on the matrix rank minimization approach, which can be applied to the signal restoration in linear systems. We focus on the null space of a low-rank matrix and provide a block adaptive algorithm of the matrix rank minimization approach to signal declipping based on the null space alternating optimization (NSAO) algorithm. Numerical examples show that the proposed algorithm is faster and has better performance than other algorithms.

This paper presents a new adaptive peak-to-average power ratio (PAPR) reduction method based on clipping and filtering (CF) for precoded orthogonal frequency division multiplexing (OFDM)-multiple-input multiple-output (MIMO) transmission. While the conventional CF method adds roughly the same interference power to each of the transmission streams, the proposed method suppresses the addition of interference power to the streams with good channel conditions. Since the sum capacity is dominated by the capacity of the streams under good channel conditions and the interference caused by the PAPR reduction process severely degrades the achievable capacity for these streams, the proposed method significantly improves the achievable sum capacity compared to the conventional CF method for a given PAPR. Simulation results show the capacity gain by using the proposed method compared to the conventional method.

This paper proposes an enhancement to a previously reported adaptive peak-to-average power ratio (PAPR) reduction method based on clipping and filtering (CF) for eigenmode multiple-input multiple-output (MIMO) — orthogonal frequency division multiplexing (OFDM) signals. We enhance the method to accommodate the case with adaptive modulation and channel coding (AMC). Since the PAPR reduction process degrades the signal-to-interference and noise power ratio (SINR), the AMC should take into account this degradation before PAPR reduction to select accurately the modulation scheme and coding rate (MCS) for each spatial stream. We use the lookup table-based prediction of SINR after PAPR reduction, in which the interference caused by the PAPR reduction is obtained as a function of the stream index, frequency block index, clipping threshold for PAPR reduction, and input backoff (IBO) of the power amplifier. Simulation results show that the proposed PAPR reduction method increases the average throughput compared to the conventional CF method for a given adjacent channel leakage power ratio (ACLR) when we assume practical AMC.

A partial transmit sequence with a clipping (PTS-Clipping) method can reduce considerably high peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signal. However, exhaustive searching operations are needed in order to find optimal phase factors. Signal distortions also occur because the clipping is a nonlinear operation. In this letter, we propose a new partial transmit sequence (PTS) scheme using a phase factor selection algorithm with preset thresholds. The proposed scheme achieves considerable savings for determining the optimum phase factors without the signal distortions.

The Noise Shaper of a full digital amplifier overflows randomly when the Modulation Index of PWM is higher than a certain value. The clipping from the overflow produces an abrupt increase of THD+N that limits MI or the maximum output power. In this paper, we discussed the reason of NS overflow and derived the critical value of MI. We proposed a compensation method for the clipping error and optimized compensation in the audio band. The measurement results show that the proposed method can increase the maximum output power by 6.4% at a 1% THD+N condition. The compensation is more important where the power supply voltage and speaker impedance are difficult to change as that in a car stereo or mobile.

A major drawback in OFDM systems is that the transmit-signal exhibits a high Peak-to-Average Power Ratio (PAPR) which causes nonlinear distortion at the output of power amplifier. To achieve high efficiency in OFDM systems, it is important to suppress PAPR of the transmit signal. In IEEE802.16e (mobile WiMAX) based systems, it is desirable to employ a simple PAPR reduction method such as clipping & filtering (C&F) or peak windowing (PW). The purpose of this paper is to evaluate PAPR reduction performance of C&F and PW and compare them in an IEEE802.16e based OFDM system. In addition, we also show a repeated PW method which reduces PAPR by repeatedly applying a smooth window function to the transmit signal. Computer simulation results show that the repeated PW can achieve almost the same PAPR reduction performance as that of the repeated C&F with significantly lower computational complexity.

Interleave-division multiple access (IDMA) inherits the peak-to-average power ratio (PAPR) problem especially with large number of multiple layers. Clipping transmission is a really simple and efficient method, but clipping noise is a tradeoff to its performance. Due to different weighting factors, an ordering technique is considered in this letter to recursively cancel the partial clipping noise at each detection. Simulation results show that the performance is close to that of unclipped IDMA chip in the high SNR region (8-9 dB).

OFDM combined with TDM (OFDM/TDM) can be used to reduce a high peak-to-average power ratio (PAPR) of OFDM, but the PAPR reduction is not sufficient. To further reduce the PAPR, an amplitude clipping can be applied. In this letter, we investigate the effect of clipping on OFDM/TDM with and without channel coding. It is shown that amplitude clipped OFDM/TDM has an advantage over clipped OFDM with respect to the PAPR.

The combination of deliberate clipping and an adaptive symbol selection scheme (ASSS) can be used to reduce the peak to average power ratio (PAPR) for Orthogonal Frequency Division Multiplexing (OFDM) signals. The probability density function (pdf) of a sample's amplitude of an adaptively selected OFDM signal without over-sampling has been considered to be approximately equal to the Rayleigh pdf. In this letter, we derive the exact pdf showing the relationship between the probability distribution of the sample's amplitude and the number of candidate OFDM symbols for ASSS. The use of the newly derived pdf can measure the effect of deliberate clipping on the adaptively selected OFDM signal more accurately.

A technique for suppressing the clipping noise of an analogue-to-digital converter (ADC) is proposed to realize a cognitive radio transceiver that offers high sensitivity carrier-sensing. When a large bandwidth cognitive radio transceiver performs carrier-sensing, it must receive a radio wave that includes many primary user transmissions. The radio wave may have high peak-to-average power ratio (PAPR) and clipping noise may be generated. Clipping noise becomes an obstacle to the achievement of high-sensitivity carrier-sensing. In the proposed technique, the original values of the samples clipped by an ADC are estimated by interpolation. Polynomial spline interpolation to the clipped signal is performed in the first step, and then SINC function interpolation is applied to the spline interpolated signal. The performance was evaluated using the signals with various PAPR. It has been found that suppression performance has a dependency on the number of samples clipped at once rather than on PAPR. Although there is an upper limit for the number of samples clipped at once that can be compensated with high accuracy, about 20 dB suppression of clipping noise was achieved with the medium degree of clipping.

This paper discusses the influence of the nonlinearity of analog-to-digital converters (ADCs) on the performance of orthogonal frequency division multiplexing (OFDM) receivers. We evaluate signal constellations and bit error rate performances while considering quantization errors and clippings. The optimum range for an ADC input amplitude is found as a result of the trade-off between quantization error and the effects of clipping. In addition, it is shown that the peak-to-average power ratio (PAPR) of the signal is not a good measure of the bit error rate (BER) performance, since the largest peaks occur only with very low probabilities. The relationship between the location of a subcarrier and its performance is studied. As a result, it is shown that the influence of the quantization error is identical for all subcarriers, while the effects of clipping depend on the subcarrier frequency. When clipping occurs, the BER performance of a subcarrier near the center frequency is worse than that near the edges.

Multicode code-division multiple access (MC-CDMA) and variable processing gain CDMA (VPG-CDMA) are very appealing techniques for achieving high bit-rate data transmission and providing significant capacity gain in wireless channels. This letter provides the peak-to-average power ratio (PAPR) reduction scheme by using a code selective allocation (CSA) in a MC VPG-CDMA system. From simulation results, the MC VPG-CDMA system experiences a reduced PAPR thanks to the CSA algorithm and maintains an acceptable performance degradation even if encountered with nonlinear distortions introduced by a level clipper.

One of the disadvantages of using OFDM is the larger peak to averaged power ratio (PAPR) of the time domain signal as compared with the conventional single carrier transmission method. The OFDM signal with larger PAPR will cause the undesirable spectrum re-growth and the larger degradation of bit error rate (BER) performance both due to the inter-modulation products occurring in the non-linear amplifier at the transmitter. The clipping method in conjunction with the Decision Aided Reconstruction (DAR) method is well known as one of the solutions to improve the BER performance with keeping the better PAPR performance. However, the DAR method is proposed to mitigate only the clipping noise and not for the inter-modulation noise. In this paper, we propose the Improved DAR (IDAR) method, which can mitigate both the clipping noise and inter-modulation noise on the basis of DAR method. The proposed method enables the efficient usage of transmission power amplifier at the transmitter with keeping the better PAPR and BER performances. This paper presents various computer simulation results to verify the performance of proposed IDAR method in the non-linear channel.

A DFT-Based method (DBM) has been proposed to compensate for the performance degradation caused by clipping distortion at the expense of bandwidth expansion. On the other hand, in any communication systems, conventional channel coding methods can be employed to improve performance. In this letter, the performance of the DBM and the channel coding methods (CCM) are compared. Furthermore, we introduce a hybrid system which outperforms both the DBM and the CCM.