Filbert H. Juwono

PAPR reduction using Huffman coding combined with clipping and filtering for OFDM transmitter

Orthogonal Frequency Division Multiplexing (OFDM) technique has some drawbacks. One of them is high peak-to-average power ratio (PAPR). This paper proposes a technique to reduce the PAPR using Huffman coding combined with clipping and filtering (CF). The simulation results show that using the combination of Huffman and CF methods is more effective than using each method separately. By using 52 subcarriers and QPSK modulation, about 7 dB PAPR reduction is achieved.

Joint Smoothed l0-Norm DOA Estimation Algorithm for Multiple Measurement Vectors in MIMO Radar

Direction-of-arrival (DOA) estimation is usually confronted with a multiple measurement vector (MMV) case. In this paper, a novel fast sparse DOA estimation algorithm, named the joint smoothed l0-norm algorithm, is proposed for multiple measurement vectors in multiple-input multiple-output (MIMO) radar. To eliminate the white or colored Gaussian noises, the new method first obtains a low-complexity high-order cumulants based data matrix. Then, the proposed algorithm designs a joint smoothed function tailored for the MMV case, based on which joint smoothed l0-norm sparse representation framework is constructed. Finally, for the MMV-based joint smoothed function, the corresponding gradient-based sparse signal reconstruction is designed, thus the DOA estimation can be achieved. The proposed method is a fast sparse representation algorithm, which can solve the MMV problem and perform well for both white and colored Gaussian noises. The proposed joint algorithm is about two orders of magnitude faster than the l1-norm minimization based methods, such as l1-SVD (singular value decomposition), RV (real-valued) l1-SVD and RV l1-SRACV (sparse representation array covariance vectors), and achieves better DOA estimation performance.

The Effectiveness of Using Source Coding to Reduce PAPR in OFDM System

Large peak-to-average power ratio (PAPR) is one of drawbacks in orthogonal frequency division multiplexing (OFDM) system. Several methods have been proposed to reduce the PAPR. The use of source coding such as Huffman coding and run length encoding (RLE) offers significant PAPR reduction. It is found that the use of Huffman coding yields better reduction about 1 dB than RLE. In addition, by using Huffman coding yields out-of-band spectrum 0.5 dB lower than RLE.

Reweighted smoothed l0-norm based DOA estimation for MIMO radar

The DOA estimation problem for monostatic MIMO radar is considered.A reweighted smoothed l0-norm minimization framework with a reweighted continuous function is designed for DOA estimation.The proposed method is about two orders of magnitude faster than conventional l1-norm minimization based DOA algorithms.The proposed method provides better angle estimation performance than l1-SVD, reweighted l1-SVD, RV l1-SRACV, RD-Capon and RD-ESPRIT algorithms. In this paper, a reweighted smoothed l0-norm algorithm is proposed for direction-of-arrival (DOA) estimation in monostatic multiple-input multiple-output (MIMO) radar. The proposed method firstly performs the vectorization operation on the covariance matrix, which is calculated from the latest received data matrix obtained by a reduced dimensional transformation. Then a weighted matrix is introduced to transform the covariance estimation errors into a Gaussian white vector, and the proposed method further constructs the other reweighted vector to enhance sparse solution. Finally, a reweighted smoothed l0-norm minimization framework with a reweighted continuous function is designed, based on which the sparse solution is obtained by using a decreasing parameter sequence and the steepest ascent algorithm. Consequently, DOA estimation is accomplished by searching the spectrum of the solution. Compared with the conventional l1-norm minimization based methods, the proposed reweighted smoothed l0-norm algorithm significantly reduces the computation time of DOA estimation. The proposed method is about two orders of magnitude faster than the l1-SVD, reweighted l1-SVD and RV l1-SRACV algorithms. Meanwhile, it provides higher spatial angular resolution and better angle estimation performance. Simulation results are used to verify the effectiveness and advantages of the proposed method.

Modification of dummy sub-carriers method to reduce PAPR in OFDM system

Orthogonal Frequency Division Multiplexing (OFDM) has been employed in many wireless standards. However, one of the drawbacks of OFDM is high peak-to-average power ratio (PAPR). We propose modification of dummy sub-carriers to reduce the PAPR. We use random dummy signal and multiplication factor to yield better PAPR. The PAPR reduction of about 4 dB at probability of 10−2 is achieved by using 2 dummy sub-carriers.

Cyclic shift resolution effects on OFDM system employing cyclic-SLM with delayed correlation and matched filter

Large peak-to-average power ratio (PAPR) is the major issue in orthogonal frequency-division multiplexing (OFDM) systems. Selective mapping (SLM) has been commonly employed to reduce the PAPR. However, SLM requires side information (SI) which reduce the bandwidth efficiency. A low-complexity cyclic SLM (C-SLM) scheme without SI which uses delay correlation and matched filter, called C-SLM-DC-MF, has been proposed in the literature. This paper examines the effects of cyclic shift resolution of the OFDM system with C-SLM-DC-MF scheme on the system performance, in terms of PAPR reduction, accuracy, and bit error rate (BER). Simulation results show that higher resolution leads to lower PAPR reduction but better accuracy and BER performance.