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

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

Computationally Efficient Modified PTS for PAPR Reduction in MIMO-OFDM

Nowadays wireless communication has taken its leap for a high data rate using the multi-carrier transmission technique.Orthogonal frequency division multiplexing(OFDM) is one of such popular method for achieving this high information rate.OFDM has several advantages,but one of the main drawbacks is its high peak-to-average power ratio(PAPR).This is due to a large number of the subcarrier,which leads to distortion problem at receiver. An OFDM signal with the high PAPR requires power amplifier’s(PAs)with large dynamic ranges.Such PAs are less efficient,costly to manufacture and very much difficult to design.There have been a large number of techniques are available in the literature to reduce the PAPR, such as Partial transmit sequence,Selective mapping,Block Coding, Tone rejection,etc.However,the challenging part is that most of the PAPR reduction schemes come with high computational complexity.Recent PAPR reduction techniques such as partial transmit sequence(PTS)has been considered as most popular for PAPR reduction.This research work explores to find a solution for the PAPR reduction by using PTS technique, which has been implemented by using sub-blocks partitioning.In sub-block partition consists of OFDM data frame which is partitioned into several sub-blocks.An adjacent partitioning(AP)method can be perceived as the best of the existing partitioning method when the cost and PAPR reduction performance are considered together.A new technique is based on modified PTS using phase rotation and circular shifting to attain the overall reduction of PAPR in MIMO-OFDM system, but computational complexity does not decrease for the same.A Co-operative PTS technique which is mainly based on alternative PTS technique is applied.In this technique although a slight loss of PAPR reduction performance is there but with much lower computational complexity