Probabilistic Amplitude Shaping Under Energy-Constrained Encoding
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Solution Overview
Problem
Existing wireless communication technologies face challenges in efficiently encoding and decoding data with high computational and storage complexity, particularly in achieving optimal throughput, latency, and quality of service (QoS) parameters, especially with the transition to 5G networks requiring advanced modulation and coding schemes.
Innovation Solution
Implementing an energy-based arithmetic coding (AC) encoding method for probabilistic amplitude shaping (PAS) that reduces computational and storage complexity by using energy-based AC encoding and decoding methods to achieve a desired amplitude distribution, such as Gaussian or Maxwell-Boltzmann distributions, through iterative selection of energy transition values and subintervals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional encoding and decoding schemes are used to support advanced modulation and coding schemes (up to 1024-QAM and 4096-QAM), then throughput and spectral efficiency are improved, but computational complexity and storage requirements increase significantly
Solution Approach 1:
The patent changes the fundamental parameter of how amplitude levels are selected in QAM modulation. Instead of using traditional uniform or geometric amplitude distributions, the patent employs probabilistic amplitude shaping that assigns different probabilities to different amplitude levels based on their energy consumption. This parameter change allows the system to achieve near-capacity performance with reduced computational complexity by focusing computational resources on the most probable amplitude transitions.
Solution Approach 2:
The patent introduces dynamic adaptation in the encoding process through iterative selection of amplitude symbols based on transition probabilities. The encoder dynamically adjusts which amplitude levels to use based on the current state and desired energy consumption, rather than following a fixed mapping scheme. This dynamic approach enables the system to adapt to varying channel conditions and QoS requirements while maintaining lower computational complexity.
2Productivity
If traditional encoding and decoding schemes are used to support advanced modulation and coding schemes, then spectral efficiency is improved, but storage requirements increase significantly
Solution Approach 1:
The patent fundamentally changes the amplitude distribution parameter from uniform/geometric to probabilistic shaping. This parameter change reduces storage requirements by eliminating the need to store complex lookup tables for traditional high-order QAM mappings. Instead, the system stores simplified probability distribution parameters that can be used to generate amplitude sequences on-the-fly, significantly reducing memory requirements while maintaining high spectral efficiency.
3Reliability
If complex modulation and coding schemes are implemented to meet growing demands for mobile broadband connectivity, then throughput and reliability are improved, but energy consumption increases
Solution Approach 1:
The patent directly addresses energy consumption by changing the amplitude distribution parameter to a probabilistic model that explicitly considers energy costs. The system assigns lower probabilities to high-energy amplitude transitions and higher probabilities to low-energy transitions, thereby reducing average energy consumption while maintaining reliable communication through the structured probabilistic framework.
Solution Approach 2:
The patent enables dynamic energy management by allowing the system to adapt amplitude selection in real-time based on energy constraints and channel conditions. The iterative encoding process dynamically adjusts amplitude probabilities to meet energy targets, providing a flexible mechanism to balance reliability and energy consumption according to specific application requirements.
4Productivity
If traditional encoding schemes are used, then implementation is straightforward, but the system cannot achieve optimal throughput, latency, and QoS parameters in 5G networks
Solution Approach 1:
The patent segments the encoding process into distinct stages: information bit generation, probabilistic amplitude shaping through iterative selection, and sequence generation. This segmentation allows each stage to be optimized independently and facilitates parallel implementation, reducing overall computational complexity while achieving optimal 5G performance requirements.
Data Source
AI summary
This disclosure provides methods, devices and systems for encoding data for wireless communication to achieve an amplitude distribution. One implementation includes a method in which probabilistic amplitude shaping is constrained by a maximum energy and a sequence length, and encoding iterations select energy transition values based on transition probabilities. Another implementation includes a method in which probabilistic amplitude shaping has a first step that defines a specific energy of an output sequence and uses subsequent encoding iterations to select energy transition values based on transition probabilities and within the specific energy. The methods generate output sequences defining amplitude symbols that are used to encode data for transmission.