THE NEW ADAPTIVE ACTIVE CONSTELLATION EXTENSION ALGORITHM FOR PAR MINIMIZATION IN OFDM SYSTEMS

Abstract-In this paper, the Peak-to-Average Ratio reduction in OFDM systems is implemented by the Adaptive Active Constellation Extension (ACE) technique which is more simple and attractive for practical downlink implementation purpose. However, in normal constellation method we cannot achieve the minimum PAR if the target clipping level is much below than the initial optimum value. To get the better of this problem, we proposed Active Constellation Algorithm with adaptive clipping control mechanism to get minimum PAR. Simulation results exhibits that the proposed algorithm reaches the minimum PAR for most severely low clipping signals to get minimum PAR

Design guidelines for spatial modulation

A new class of low-complexity, yet energyefficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO) has emerged. These systems are capable of exploiting the spatial dimensions (i.e. the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication whilst relying on a single-Radio Frequency (RF) chain. Moreover, SM may also be viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/ cooperative protocol design issues, and on their meritorious variants

Peak Power Reduction of OFDM Signals with Sign Adjustment

It has recently been shown that significant reduction in the peak to mean envelope power (PMEPR) can be obtained by altering the sign of each subcarrier in a multicarrier system with n subcarriers. However, finding the best sign not only requires a search over 2n possible signs but also may lead to a substantial rate loss for small size constellations. In this paper, we first propose a greedy algorithm to choose the signs based on p-norm minimization and prove that the resulting PMEPR is guaranteed to be less than c log n where c is a constant independent of n for any n. This approach has lower complexity in each iteration compared to the derandomization approach of while achieving similar PMEPR reduction. We further improve the performance of the proposed algorithm by enlarging the search space using pruning. Simulation results show that PMEPR of a multicarrier signal with 128 subcarriers can be reduced to within 1.6 dB of the PMEPR of a single carrier system. In the second part of the paper, we address the rate loss by proposing a block coding scheme in which only one sign vector is chosen for K different modulating vectors. The sign vector can be computed using the greedy algorithm in n iterations. We show that the multi-symbol encoding approach can reduce the rate loss by a factor of K while achieving the PMEPR of c logKn, i.e., only logarithmic growth in K. Simulation results show that the rate loss can be made smaller than %10 at the cost of only 1 db increase in the resulting PMEPR for a system with 128 subcarriers

Simplified Levenberg-Marquardt Algorithm based PAPR Reduction for OFDM System with Neural Network

In recent years, OFDM is the key transmission technique in the communication system. This is because of the high channel estimation, strong against multipath fading and increased spectral efficiency. Because of the independently modulated subcarriers, the Peak to Average Power Ratio (PAPR) is very high in OFDM systems. Previously we use a number of PAPR reduction schemes using clipping, adding windows etc. But in these methods we cannot achieve the optimum reduction or the BER performance is high or the system is very complex. On considering the BER performance and system complexity we employ a new method based on the Neural Network (NN). In this new method we achieve significant PAPR reduction with great BER improvement and complexity reduction. In the simulations we seen that the PAPR reduction and BER performance are very good. DOI: 10.17762/ijritcc2321-8169.15080

A Low-Complexity SLM PAPR Reduction Scheme for OFDMA

In orthogonal frequency division multiplexing (OFDM) systems, selected mapping (SLM) techniques are widely used to minimize the peak to average power ratio (PAPR). The candidate signals are generated in the time domain by linearly mixing the original time-domain transmitted signal with numerous cyclic shift equivalents to reduce the amount of Inverse Fast Fourier Transform (IFFT) operations in typical SLM systems. The weighting factors and number of cyclic shifts, on the other hand, should be carefully chosen to guarantee that the elements of the appropriate frequency domain phase rotation vectors are of equal magnitude. A low-complexity expression is chosen from among these options to create the proposed low-complexity scheme, which only requires one IFFT. In comparison to the existing SLM technique, the new SLM scheme achieves equivalent PAPR reduction performance with significantly less computing complexity. MATLAB tool is used for simulating the proposed work

A Low-Complexity SLM PAPR Reduction Scheme for OFDMA

In orthogonal frequency division multiplexing (OFDM) systems, selected mapping (SLM) techniques are widely used to minimize the peak to average power ratio (PAPR). The candidate signals are generated in the time domain by linearly mixing the original time-domain transmitted signal with numerous cyclic shift equivalents to reduce the amount of Inverse Fast Fourier Transform (IFFT) operations in typical SLM systems. The weighting factors and number of cyclic shifts, on the other hand, should be carefully chosen to guarantee that the elements of the appropriate frequency domain phase rotation vectors are of equal magnitude. A low-complexity expression is chosen from among these options to create the proposed low-complexity scheme, which only requires one IFFT. In comparison to the existing SLM technique, the new SLM scheme achieves equivalent PAPR reduction performance with significantly less computing complexity. MATLAB tool is used for simulating the proposed work