Algorithm based new Tone Reservation method for mitigating PAPR in OFDM systems

There are abundant methods to mitigate PAPR in OFDM signals among which algorithm based tone reservation is of great popularity owing to its low complexity as well as decent BER. Here we have put forward a new distinct algorithm based Tone Reservation technique which is not only less complex and calculates its own threshold as well as PRT signal (unlike other algorithms requiring predetermined threshold and PRT) but also aptly modifies the data by bit by bit comparison with a modified copy of itself (algorithm modified) thus scaling the peaks as and providing a decent BER and good PAPR reduction.

A SURVEY OF PAPR REDUCTION IN OFDM SIGNALS

  In Radio waves, the digital data can be transmitted using Burst number of data using OFDM technique. So only an OFDM Technique is called attractive modulation techniques. In this OFDM signal transmission having so many disadvantages, one of the main disadvantages is a Peak average power which is due to combination of sinusoidal leads to high peak-to power ratio (PAPR).Due to High PAPR, which leads to poor (i.e) degrades the signal performance of power amplifier in transmission, this PAPR can be reduce using some of the following technique like, there are Clipping, Coding, Partial transmit sequence (PTS), Sequential Mapping(SM), Tone reservation (TR), Tone injection (TI), Interleaving, Nonlinear companding transform, & Hadamard transform etc.Various technique are available to reduce the Peak power and discuss detail about the merits and demerits .Â

End-to-End Learning of OFDM Waveforms with PAPR and ACLR Constraints

Orthogonal frequency-division multiplexing (OFDM) is widely used in modern wireless networks thanks to its efficient handling of multipath environment. However, it suffers from a poor peak-to-average power ratio (PAPR) which requires a large power backoff, degrading the power amplifier (PA) efficiency. In this work, we propose to use a neural network (NN) at the transmitter to learn a high-dimensional modulation scheme allowing to control the PAPR and adjacent channel leakage ratio (ACLR). On the receiver side, a NN-based receiver is implemented to carry out demapping of the transmitted bits. The two NNs operate on top of OFDM, and are jointly optimized in and end-to-end manner using a training algorithm that enforces constraints on the PAPR and ACLR. Simulation results show that the learned waveforms enable higher information rates than a tone reservation baseline, while satisfying predefined PAPR and ACLR targets

Blind Algorithm Development for Peak to Average Power Ratio Reduction in OFDM Systems under Frequency Selective Channels

One major drawback of orthogonal frequency division multiplexing (OFDM) system is peak to average power ratio (PAPR). This effect causes high power amplifier (HPA) to introduce intermodulation and out of band radiation as the signal goes through, thus degrades the performance of OFDM systems. This paper proposes blind algorithms which takes advantage of signal transformation technique and signal distortion technique. Simulation results show that at complementary cumulative distribution function (CCDF) level of 10-3 , the proposed algorithm achieved 3.2 dB PAPR improvement compared to discrete Fourier transform with interleaved frequency division multiple access (DFT-IFDMA) based algorithm. The bit error rate (BER) performance has degraded by 2 dB compared to the original OFDM signal with no distortion under frequency selective channel (FCS) at BER of 10-4 . These presented results, mark this algorithm as a better candidate for PAPR reduction algorithm in long term evolution (LTE) network. Under AWGN channels, the proposed algorithm performs better both in low and high signal power values. Under frequency selective channels, the existing and proposed algorithm converges after 10 dB of signal to noise power values. The low BER transmissions at low signal power values signify energy efficiency, ideal for portable wireless devices with limited battery power

A survey on OFDM-based elastic core optical networking

Orthogonal frequency-division multiplexing (OFDM) is a modulation technology that has been widely adopted in many new and emerging broadband wireless and wireline communication systems. Due to its capability to transmit a high-speed data stream using multiple spectral-overlapped lower-speed subcarriers, OFDM technology offers superior advantages of high spectrum efficiency, robustness against inter-carrier and inter-symbol interference, adaptability to server channel conditions, etc. In recent years, there have been intensive studies on optical OFDM (O-OFDM) transmission technologies, and it is considered a promising technology for future ultra-high-speed optical transmission. Based on O-OFDM technology, a novel elastic optical network architecture with immense flexibility and scalability in spectrum allocation and data rate accommodation could be built to support diverse services and the rapid growth of Internet traffic in the future. In this paper, we present a comprehensive survey on OFDM-based elastic optical network technologies, including basic principles of OFDM, O-OFDM technologies, the architectures of OFDM-based elastic core optical networks, and related key enabling technologies. The main advantages and issues of OFDM-based elastic core optical networks that are under research are also discussed