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Understanding and Mitigating PAPR in OFDM Systems

  • Writer: Venkateshu
    Venkateshu
  • Jun 16
  • 5 min read

Orthogonal Frequency Division Multiplexing (OFDM) is a cornerstone of modern wireless communication systems, offering robustness against multipath fading and high spectral efficiency. However, one of its key limitations is the high Peak-to-Average Power Ratio (PAPR), which negatively impacts system efficiency and hardware design. This article explores the origins and implications of PAPR in OFDM systems, followed by a deep dive into classical and emerging mitigation techniques that balance performance with practical implementation complexity.

 

1. Introduction

Orthogonal Frequency Division Multiplexing (OFDM) is a digital modulation technique that divides the total available bandwidth into many narrowband subcarriers. Each subcarrier is modulated with a low data rate stream using conventional modulation schemes like QAM or PSK.

 

OFDM is based on the well-known technique of Frequency Division Multiplexing (FDM). In FDM different streams of information are mapped onto separate parallel frequency channels. Each FDM channel is separated from the others by a frequency guard band to reduce interference between adjacent channels.

 

The OFDM scheme differs from traditional FDM in the following interrelated ways:

1. Multiple carriers (called subcarriers) carry the information stream,

2. The subcarriers are orthogonal to each other, and

3. A guard interval is added to each symbol to minimize the channel delay spread and intersymbol interference.

 

 

In an OFDM (Orthogonal Frequency Division Multiplexing) system, the process starts with your data – a bunch of bits. These bits are grouped and converted into symbols, which are basically numbers that carry both amplitude and phase. These symbols represent points on a modulation scheme like BPSK or QAM.

 

These data sent on a different frequency channel (called a subcarrier). All these data go into the IFFT (Inverse Fast Fourier Transform).

The IFFT takes total number of subcarriers(N), and it converts them into a time-domain signal – something that can be actually sent over the air. You can think of the IFFT as creating N sine waves at different frequencies, each carrying one of your symbols, and then adding them all together to make a single complex signal.

Each of those sine waves (subcarriers) is spaced so that it doesn't interfere with the others – they are orthogonal. The result is a block of N samples called an OFDM symbol.

Once that's done, a few more steps happen (like adding a guard interval), and the signal is transmitted over the radio channel.

 

On the receiving side, the reverse happens. A device uses the FFT (Fast Fourier Transform) to separate the signal back into the individual frequency components, so it can recover the original data bits you sent. 


 

 Benefits of OFDM

  • Robustness to multipath fading: Each subcarrier experiences flat fading, which simplifies equalization.

  • Spectral efficiency: Subcarriers are orthogonal, allowing overlapping spectra without inter-carrier interference (ICI).

  • Flexibility: Easily scalable to different bandwidths and data rates.

 

OFDM has become the modulation scheme of choice in numerous standards including 4G LTE, 5G NR, Wi-Fi, and DVB, due to its ability to handle frequency-selective fading and its support for high data rates. However, its multi-carrier nature causes high PAPR, posing challenges in the design of power amplifiers (PAs) and digital-to-analog converters (DACs).

 

How OFDM Results in High PAPR

What is PAPR?

For an OFDM signal x(t), the PAPR is defined as:

This measures how "peaky" the signal is—i.e., how much higher the peaks are compared to the average signal power.

Due to the superposition of multiple independently modulated subcarriers, the time-domain OFDM signal can have large peaks when the subcarriers constructively interfere. For example, in an 8-subcarrier OFDM system, if all carriers are in-phase:

Average power =A^2, so:

This shows even a small OFDM system can have significant PAPR.

 

PAPR Characteristics in OFDM

OFDM signals are composed of the sum of multiple subcarriers:

 When all subcarriers align constructively (in phase), the peak power can be up to N times the average, making PAPR as high as:

PAPRmax​=10 log10 N

This probability is low but non-negligible, especially in large-scale systems like 5G massive MIMO.

  

2. Why PAPR is a Problem


  • Power Amplifier Efficiency

    • PAs in wireless transmitters need to operate linearly to avoid signal distortion. A high PAPR forces the PA to operate in a back-off mode, reducing its efficiency and increasing power consumption.

  • Signal Clipping and Distortion

    • High PAPR can push the signal into the non-linear region of the PA, leading to:

    • In-band distortion: degrades BER performance.

    • Out-of-band radiation: causes adjacent channel interference.

  • Dynamic Range Requirements

    • High PAPR increases demands on DAC and ADC resolution and linearity, making hardware design more complex and costly.

  • Hardware Complexity

    • High PAPR increases the required dynamic range of ADCs and DACs, raising cost and design complexity.

 

 3. PAPR Mitigation Techniques


  1. Signal Distortion Techniques

Clipping and Filtering

Concept: Limit signal amplitude to a threshold and apply filtering to remove out-of-band components.

Example: Clipping level set to 3 dB above average power. Filtering reduces adjacent channel interference.

Pros: Simple to implement.

Cons: Causes in-band distortion and increases BER.

Peak Windowing

Concept: Apply window functions (e.g., Kaiser, Hamming) to smooth large peaks.

Example: Gaussian window applied to samples exceeding a threshold.

Pros: Less distortion than clipping.

Cons: Reduced spectral efficiency.

 

  1. Probabilistic Techniques

    Selective Mapping (SLM)

Concept: Generate multiple phase-rotated OFDM signals and select the one with the lowest PAPR.

Example: Four versions of OFDM signal generated with different phase vectors; one with lowest PAPR chosen.

Pros: No distortion.

Cons: Requires side information transmission.

Partial Transmit Sequence (PTS)

Concept: Divide input symbols into sub-blocks and apply independent phase shifts.

Example: Input divided into 4 sub-blocks; use exhaustive search over 4-phase values to minimize PAPR.

Pros: Good performance.

Cons: High complexity, side information needed.

  1. Coding Techniques

Block Coding

Concept: Encode input data using special codes that avoid high PAPR patterns.

Example: Use Golay complementary sequences known for low PAPR.

Pros: Adds error correction capability.

Cons: Reduces data rate.

Tone Reservation

Concept: Reserve a few subcarriers to generate a signal that cancels peaks.

Example: 5% of subcarriers used to generate anti-peaks.

Pros: No BER degradation.

Cons: Slight loss in spectral efficiency.

 

  1. Transform Techniques

Discrete Cosine Transform (DCT)

Concept: Apply DCT before IFFT to reduce time-domain correlation.

Example: Apply Type-II DCT to modulated data vector.

Pros: PAPR reduction up to 2–4 dB.

Cons: Additional complexity.

Companding

Concept: Use non-linear compression (e.g., µ-law) on the signal amplitude.

Example: Compress large amplitudes, expand small ones before IFFT; reverse at receiver.

Pros: Significant PAPR reduction.

Cons: Non-linear distortion.

 

4. Advanced and Hybrid Techniques

  • Machine Learning-Based Approaches

    • Concept: Train models (e.g., neural networks) to predict and minimize PAPR. A CNN learns mapping from input symbols to low-PAPR OFDM frames.

    • Pros: Adaptive and data-driven.

    • Cons: High training complexity.

  • Intelligent Reconfigurable Coding

    • Concept: Dynamically choose between coding strategies based on real-time metrics. Use SLM in good SNR, switch to companding in low SNR.

    • Pros: Environment-aware.

    • Cons: Requires channel estimation.

  • Deep Reinforcement Learning (DRL)

    • Concept: Model PAPR control as an MDP and use DRL to learn reduction policy. An agent learns to select phase vectors in PTS scheme.

    • Pros: Learns optimal actions.

    • Cons: Requires training time.

 

5. Practical Considerations

  • Standard Compliance: Techniques like SLM or PTS must preserve orthogonality and avoid excessive side information.

  • Implementation Complexity: Trade-offs between hardware feasibility and PAPR reduction.

  • Energy Efficiency: PAPR control becomes critical for battery-operated IoT and mobile devices.


6. Conclusion

While OFDM brings many advantages, high PAPR remains a central challenge, especially in next-generation systems. A range of mitigation techniques—ranging from classical methods like clipping to advanced AI-driven approaches—can be tailored for specific system constraints. The future lies in adaptive, hybrid, and context-aware methods that intelligently balance trade-offs in real time.

 

7 References


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