In this paper, two partial transmit sequence (PTS) schemes without side information (SI) are proposed for reducing peak-to-average power ratio of orthogonal frequency division multiplexing signals. The proposed schemes do not transmit SI identifying a rotating vector because identifiable phase offset is applied to the elements of each rotating vector. To extract SI from the received signal and recover the data sequence, the maximum likelihood (ML) detector is used. This ML detector exploits the Euclidean distance between the given signal constellation and the signal constellation rotated by the phase offset. By doing pairwise error probability (PEP) analysis, it is investigated how to choose good phase offsets for embedding SI. Also, the performance degradation caused by SI detection failure is analyzed based on PEP. Finally, through numerical analysis, it is shown that the BER performance of the proposed PTS schemes is not degraded compared with the conventional PTS with perfect SI.

In this letter, a blind reconstruction method of Bose-Chaudhuri-Hocquenghem (BCH) codes is proposed, which uses the property that all the codeword polynomials of a t-error correcting BCH code have the same 2t consecutive roots over Galois field. The proposed method inherently eliminates most of the erroneous codewords from the received codewords by utilizing the information about the starting position and length of consecutive roots of each received codeword. Therefore, the blind reconstruction performance is substantially improved and the simulation results confirm that the proposed method outperforms other blind reconstruction methods.

Partial transmit sequence (PTS) is a probabilistic peak-to-average power ratio (PAPR) reduction scheme for orthogonal frequency division multiplexing (OFDM) signals, but it requires an exhaustive search for the one with the minimum PAPR over all alternative OFDM signal vectors. In order to reduce such computational complexity, it was proposed that the PAPR value of each alternative OFDM signal vector is approximately estimated by using dominant time-domain samples selected based on a simple metric. In this paper, two new effective metrics for selecting dominant time-domain samples are proposed for low-complexity PTS scheme. For further lowering the computational complexity, two low-complexity PTS schemes are proposed by sorting the dominant time-domain samples in decreasing order of their metric values. Simulation results confirm that compared with the conventional PTS scheme, the proposed PTS schemes show identical PAPR reduction performance with substantially reduced computational complexity.

Partial transmit sequence (PTS), a well‐known peak‐to‐average power ratio (PAPR) reduction scheme for orthogonal frequency division multiplexing (OFDM) systems, has been actively investigated to reduce its high computational complexity. Ku et al . proposed a selection method of dominant time‐domain samples and by only using the selected samples, the PAPR of each alternative OFDM signal vector is calculated. This method clearly reduces the computational complexity but it is crucial to select proper time‐domain samples to achieve acceptable PAPR reduction performance. In this study, a new selection method of dominant time‐domain samples is proposed based on rotating samples of inverse fast Fourier transformed (IFFTed) subblocks to the local area on which the corresponding sample of the IFFTed first subblock is located. Moreover, pre‐exclusion of phase rotating vectors based on the above time‐domain sample rotation is proposed to further reduce the computational complexity. Numerical results confirm that the proposed PTS schemes substantially reduce the computational complexity with negligible degradation of PAPR reduction performance.

In the tone reservation (TR) scheme, it is known that finding the optimal peak reduction tone (PRT) set is equivalent to solving the secondary peak minimization problem. However, this problem cannot be solved for the practical number of tones because it is nondeterministic polynomial-time (NP)-hard. In this paper, two efficient methods for selecting a near optimal PRT set are proposed. The first method is a random search algorithm with reduced computational complexity based on the observation that the secondary peak value of the time domain kernel, which is obtained by inverse fast Fourier transforming the characteristic sequence of the PRT set, statistically tends to decrease as the variance of the time domain kernel decreases. The second method is a deterministic selection algorithm using the cyclic difference set. The near optimality of these methods is confirmed through the numerical analysis.

In this paper, a blind reconstruction method of Bose-Chaudhuri-Hocquenghem (BCH) and Reed-Solomon (RS) codes is proposed, which aims to reconstruct the generator polynomials of BCH and RS codes from the intercepted noisy bitstream in non-cooperative environments.The previous blind reconstruction methods try to select correct (or noiseless) codewords or extract code information from the received bitstream. However, they need to have sufficiently correct codewords for successful reconstruction. Therefore, the existing methods are highly dependent on the channel conditions because a sufficient number of correct codewords should be available for achieving good reconstruction performance.To overcome such high dependency on channel conditions, the proposed blind reconstruction method performs error correction of single-error codewords through the proposed single-error correction method (SCM).Then, both the correct codewords and the corrected single-error codewords are utilized for blind reconstruction. Specifically, the correct codewords are selected based on the algebraic property of BCH and RS codes that codeword polynomials have consecutive roots. At the same time, the codewords presumably with a single error are selected and corrected based on the fact that the most of BCH and RS codeword polynomials with either a single error or double errors do not have consecutive roots. Based on this fact, SCM is devised, which selects and corrects the codewords with a single error with high probability. Finally, it is verified that the proposed blind reconstruction method shows much better reconstruction performance by using only one-tenth of the received codewords compared to the existing best methods even under harsh channel conditions.