A low complexity SI sequence estimator for pilot-aided SLM–OFDM systems

Selected mapping (SLM) is a well-known method for reducing peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. However, as a consequence of implementing SLM, OFDM receivers often require estimation of some side information (SI) in order to achieve successful data recovery. Existing SI estimation schemes have very high computational complexities that put additional constraints on limited resources and increase system complexity. To address this problem, an alternative SLM approach that facilitates estimation of SI in the form of phase detection is presented. Simulations show that this modified SLM approach produces similar PAPR reduction performance when compared to conventional SLM. With no amplifier distortion and in the presence of non-linear power amplifier distortion, the proposed SI estimation approach achieves similar data recovery performance as both standard SLM–OFDM (with perfect SI estimation) and also when SI estimation is implemented through the use of an existing frequency-domain correlation (FDC) decision metric. In addition, the proposed method significantly reduces computational complexity compared with the FDC scheme and an ML estimation scheme

A joint OFDM PAPR reduction and data decoding scheme with no SI estimation

The need for side information (SI) estimation poses a major challenge when selected mapping (SLM) is implemented to reduce peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. Recent studies on pilot-assisted SI estimation procedures suggest that it is possible to determine the SI without the need for SI transmission. However, SI estimation adds to computational complexity and implementation challenges of practical SLM-OFDM receivers. To address these technical issues, this paper presents the use of a pilot-assisted cluster-based phase modulation and demodulation procedure called embedded coded modulation (ECM). The ECM technique uses a slightly modified SLM approach to reduce PAPR and to enable data recovery with no SI transmission and no SI estimation. In the presence of some non-linear amplifier distortion, it is shown that the ECM method achieves similar data decoding performance as conventional SLM-OFDM receiver that assumed a perfectly known SI and when the SI is estimated using a frequency-domain correlation approach. However, when the number of OFDM subcarriers is small and due to the clustering in ECM, the modified SLM produces a smaller PAPR reduction gain compared with conventional SLM

A Simplified Scheme of Estimation and Cancellation of Companding Noise for Companded Multicarrier Transmission Systems

Nonlinear companding transform is an efficient method to reduce the high peak-to-average power ratio (PAPR) of multicarrier transmission systems. However, the introduced companding noise greatly degrades the bit-error-rate (BER) performance of the companded multicarrier systems. In this paper, a simplified but effective scheme of estimation and cancellation of companding noise for the companded multicarrier transmission system is proposed. By expressing the companded signals as the summation of original signals added with a companding noise component, and subtracting this estimated companding noise from the received signals, the BER performance of the overall system can be significantly improved. Simulation results well confirm the great advantages of the proposed scheme over other conventional decompanding or no decompanding schemes under various situations

On PAPR Reduction of OFDM using Partial Transmit Sequence with Intelligent Optimization Algorithms

In recent time, the demand for multimedia data services over wireless links has grown up rapidly. Orthogonal Frequency Division Multiplexing (OFDM) forms the basis for all 3G and beyond wireless communication standards due to its efficient frequency utilization permitting near ideal data rate and ubiquitous coverage with high mobility. OFDM signals are prone to high peak-to-average-power ratio (PAPR). Unfortunately, the high PAPR inherent to OFDM signal envelopes occasionally drives high power amplifiers (HPAs) to operate in the nonlinear region of their characteristic leading out-of-band radiation, reduction in efficiency of communication system etc. A plethora of research has been devoted to reducing the performance degradation due to the PAPR problem inherent to OFDM systems. Advanced techniques such as partial transmit sequences (PTS) and selected mapping (SLM) have been considered most promising for PAPR reduction. Such techniques are seen to be efficient for distortion-less signal processing but suffer from computational complexity and often requires transmission of extra information in terms of several side information (SI) bits leading to loss in effective data rate. This thesis investigates the PAPR problem using Partial Transmit Sequence (PTS) scheme, where optimization is achieved with evolutionary bio-inspired metaheuristic stochastic algorithms. The phase factor optimization in PTS is used for PAPR reduction. At first, swarm intelligence based Firefly PTS (FF-PTS) algorithm is proposed which delivers improved PAPR performance with reduced searching complexity. Following this, Cuckoo Search based PTS (CS-PTS) technique is presented, which offers good PAPR performance in terms of solution quality and convergence speed. Lastly, Improved Harmony search based PTS (IHS-PTS) is introduced, which provides improved PAPR. The algorithm has simple structure with a very few parameters for larger PTS sub-blocks. The PAPR performance of the proposed technique with different parameters is also verified through extensive computer simulations. Furthermore, complexity analysis of algorithms demonstrates that the proposed schemes offer significant complexity reduction when compared to standard PAPR reduction techniques. Findings have been validated through extensive simulation tests

NORM Technique based PAPR Reduction in MC-CDMA Systems

Multicarrier code division multiple access (MC-CDMA) is one of the promising technologies for future-generation wireless networks. It offers high data rates, protection against frequency-selective fading and efficient utilization of the spectrum. The peak to average power ratio (PAPR) is very high in MCCDMA systems. The partial transmit sequence technique (PTS) and the selective mapping technique (SLM) reduce the PAPR with more computational complexity. In this study, the NORM technique was used for PAPR reduction in MC-CDMA systems. The performance of NORM was analyzed with PTS and SLM in terms of cumulative complementary distribution, power saving gain, amplifier efficiency, computational complexity and bit error rate. Simulation results showed that NORM has better PAPR reduction with less computational complexity

Reduction of Peak to Average Power Ratio using Selective Mapping Technique of an OFDM Signal: An Analysis

Orthogonal Frequency Division Multiplexing (OFDM) is a optimistic and very popular modulation technique in multicarrier domain which is quite promising regarding the issues of interferences present in next generation mobile communication systems. It deployed in the area where high data rate and low latency required while efficiency will be as better as possible. The critical problem in OFDM system is maintaining low PAPR (peak to average power ratio) because it reduces the performance of system. There are several techniques which are used to overcome problem of high PAPR in OFDM modulation system. One of the techniques is Selective Mapping (SLM) which comes in distortion less criteria. In this paper analysis of PAPR reduction of an OFDM system for distortion less transmission criterion is shown. We have also used some mathematical equations to calculate and simulate its performance. It’s also shown that SLM method grants the user a better PAPR reduction while having high complex circuitry