Adaptive Modulation and Coding (AMC)

Adaptive Modulation and Coding (AMC) is a cornerstone technology in modern wireless communication systems, including 5G, enabling efficient and reliable data transmission. By dynamically adjusting the modulation scheme and coding rate in response to varying channel conditions, AMC enhances data throughput while ensuring robust performance in the presence of interference and noise.

AMC optimizes spectral and power efficiency by continuously adapting modulation and coding parameters to match the prevailing channel conditions. Unlike static transmission schemes that use fixed modulation and coding settings regardless of link quality, AMC dynamically modifies these parameters in real time. This adaptability is particularly valuable in mobile environments where channel conditions fluctuate due to user movement, interference, and physical obstructions.

Evolution of AMC in Wireless Communication

AMC has a rich history, evolving alongside advancements in wireless communication. Initially developed for military applications where reliability was crucial, adaptive techniques were later introduced into commercial wireless networks. With the advent of digital cellular networks in the 1990s, AMC became integral to mobile communication, progressing through multiple generations:

• 2G (GSM): Introduced fundamental adaptive coding techniques.
• 3G (UMTS): Enhanced AMC with advanced modulation schemes.
• 4G (LTE): Incorporated sophisticated AMC algorithms and OFDMA-based resource allocation.
• 5G (NR): Further refines AMC by leveraging massive MIMO and beamforming for dynamic channel adaptation.

AMC remains a key enabler of high-speed, resilient wireless communication, ensuring that data transmission remains efficient and reliable across diverse network conditions.

Idea of switching modulation according to SNR is called Adaptive Modulation

 We consider an AWGN channel 𝑦=𝑥+𝑛

SNR = Signal power / noise power

Capacity of above channel is

Capacity of 3 bps/Hz is achieved at SNR = 9 dB

Capacity of 5 bps/Hz is achieved at SNR = 15 dB

 we’ll take the following points:

SNR of -10 dB, 0 dB, 3 dB, 6 dB, 9 dB, 12 dB, 15 dB, and 20 dB.

We will calculate the capacity using the formula

We’ll also mark specific points, such as:

• A capacity of 3 bps/Hz achieved at an SNR of 9 dB.
• A capacity of 5 bps/Hz achieved at an SNR of 15 dB.

This graph illustrates the relationship between SNR (in dB) and capacity (in bps/Hz) with specific points marked for capacities of 3 bps/Hz and 5 bps/Hz at SNR values of 9 dB and 15 dB, respectively.

Practical Implementation of AMC in 5G

In 5G, various modulation schemes are used, such as Quadrature Amplitude Modulation (QAM). The order of QAM (denoted by M) determines the number of symbols and the bit rate:

• 4-QAM (QPSK)
• 16-QAM
• 64-QAM
• 256-QAM

Higher-order QAM schemes transmit more bits per symbol but require higher SNR to maintain reliable communication.

Here’s the graph representing Adaptive Modulation and Coding (AMC) based on the given SNR values and their corresponding capacities.

To elaborate on the graph depicting the relationship between SNR (Signal-to-Noise Ratio) and capacity (bits per second per Hertz, bps/Hz) in the context of Adaptive Modulation and Coding (AMC), we can include more details and multiple modulation schemes. This would illustrate how different SNR values influence the capacity and the choice of modulation schemes.

• 4-QAM:

SNR = 5 dB, Capacity = 2 bps/Hz

• 16-QAM:

SNR = 12 dB, Capacity = 4 bps/Hz

• 64-QAM:

SNR = 18 dB, Capacity = 6 bps/Hz

• 256-QAM:

SNR = 24 dB, Capacity = 8 bps/Hz

Graph now illustrates how different SNR values correspond to different capacities and modulation schemes in Adaptive Modulation and Coding (AMC). Here’s a detailed explanation:

1.     4-QAM

SNR = 5 dB: At this SNR, a capacity of 2 bps/Hz is achieved. This modulation scheme is suitable for lower SNRs due to its robustness against noise.

2.     16-QAM:

SNR = 12 dB: With an increase in SNR to 12 dB, a more complex modulation scheme like 16-QAM can be used, achieving a capacity of 4 bps/Hz. This scheme provides a higher data rate than 4-QAM but requires a better signal quality.

3.     64-QAM:

SNR = 18 dB: At an SNR of 18 dB, 64-QAM can be employed, offering a capacity of 6 bps/Hz. This modulation scheme provides even higher data rates but needs an even better SNR.

4.     256-QAM:

SNR = 24 dB: For very high SNRs (24 dB), 256-QAM can be used, achieving a capacity of 8 bps/Hz. This modulation scheme is highly efficient but requires excellent signal quality.

Adaptive Modulation and Coding (AMC): This process involves dynamically adjusting the modulation scheme based on the current SNR to optimize the data rate and maintain reliable communication.

• Trade-off: Higher-order modulation schemes (like 64-QAM and 256-QAM) provide higher data rates but require better signal quality (higher SNR).
• Flexibility: AMC provides flexibility in communication systems, allowing them to adapt to varying channel conditions to maintain optimal performance.

Coding Techniques

• Forward Error Correction (FEC) codes, such as Low-Density Parity-Check (LDPC) codes, are used to enhance reliability by adding redundant bits to the transmitted data.

The coding rate (r) is defined as:

k: Number of original data bits.

n: Total number of bits after encoding, including original data and redundant bits.

• The coding rate is always less than or equal to 1, and a lower rate implies more redundancy and higher error correction capability.
• Encoder adds parity bits to input message bits to reduce block error rate (BLER).
• Encoder should use large code-block lengths to guarantee a low BLER.

SNR uses capacity achieving Low Density Parity Check (LDPC) Codes

One popular type of FEC code is the Low-Density Parity-Check (LDPC) code. LDPC codes are used extensively in modern communication systems, including wireless and optical networks, because of their near-optimal performance and efficient decoding algorithms.

Capacity Achieving – provide low BLER with reasonable code block length at reasonable SNR offset from the capacity curve.

We’ll consider a scenario where we use different modulation schemes like BPSK, QPSK, 16QAM, and 256QAM and see how the LDPC codes can achieve lower error probabilities at different SNRs.

For this example, let’s consider the following:

We are using LDPC codes with a code block length of 𝑁=3000

We’ll plot the performance (BLER) for BPSK, QPSK, 16QAM, and 256QAM as functions of SNR ranging from -10 dB to 20 dB.

We’ll assume that the target BLER is   

The idea is to showcase how well LDPC codes can perform in achieving near-capacity rates at various SNRs with different modulation schemes, keeping the error rates low.

Description of the Graph:

• SNR (Signal-to-Noise Ratio) is plotted on the horizontal axis ranging from -10 dB to 20 dB.
• BLER (Block Error Rate) is plotted on the vertical axis on a logarithmic scale, indicating the probability of block errors.

1. As the complexity of the modulation increases (from BPSK to 256QAM), the required SNR to achieve a similar BLER also increases.
2. LDPC codes effectively help in approaching the Shannon limit, particularly noticeable at higher SNRs where the performance of these codes nears theoretical limits.

This graph is illustrative of how LDPC codes can be employed in different communication systems to optimize the trade-off between data rate and reliability, depending on the modulation scheme and the operational SNR environment. ​