Polar Code Configuration for Block Shaping With Lower Decoding Latency
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Solution Overview
Problem
Existing wireless communication systems face challenges in managing signal attenuation and complexity in complex and dynamic environments, leading to inefficiencies in signal transmission and reception, increased processing resources, and poor user experience.
Innovation Solution
The use of Polar code construction and configuration for block-code-based shaping, specifically considering block length and shaping bit length, to optimize probabilistic amplitude shaping, reducing decoding complexity and latency, and minimizing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional coding schemes are used in wireless communication systems, then implementation is simpler, but signal transmission efficiency is lower and throughput is reduced
Solution Approach 1:
The information bits are divided into multiple blocks, with each block independently encoded using polar codes. This segmentation allows the system to achieve high throughput through efficient parallel processing while managing complexity by breaking down the overall encoding task into smaller, more manageable units
Solution Approach 2:
The system dynamically adjusts polar code parameters including block length, code rate, and kernel selection based on channel conditions and throughput requirements. By changing these parameters, the system optimizes transmission efficiency while adapting to varying complexity constraints in different operating scenarios
2Reliability
If advanced signal processing techniques are employed to overcome signal attenuation, then communication reliability improves, but processing resource consumption increases
Solution Approach 1:
The system performs preliminary channel estimation and polar code parameter selection before actual data transmission. By preparing encoding parameters and selecting appropriate code rates in advance based on channel conditions, the system ensures reliable communication while minimizing real-time processing resource consumption during active transmission
Solution Approach 2:
The polar code encoding process inherently provides error correction capabilities through its mathematical structure, eliminating the need for additional complex error correction mechanisms. The code's built-in redundancy and decoding properties enable reliable communication while keeping processing requirements manageable
3Speed
If higher data carrying capacity is achieved through increased modulation complexity, then transmission speed improves, but system complexity and power consumption increase
Solution Approach 1:
The system applies polar codes selectively to portions of the data stream rather than uniformly encoding all data with the same complexity level. By using different code rates and block lengths for different data portions based on their importance and channel conditions, the system achieves high transmission speed for critical data while reducing power consumption for less critical data
Data Source
AI summary
Certain aspects of the present disclosure provide techniques for Polar code construction and configuration for block-code-based shaping. An example method includes identifying a set of information bits for transmission, generating a set of log likelihood ratios (LLRs) corresponding to the set of information bits, segmenting the set of LLRs into a plurality of shaping blocks based, at least in part, on a shaping block length for the plurality of shaping blocks, decoding, according to a shaping code rate, the plurality of shaping blocks using a polar code to obtain a sequence of shaping bits, wherein the polar code used to decode the plurality of shaping blocks depends on the shaping code rate and the shaping block length, generating a sequence of shaped symbols from the sequence of shaping bits, transmitting the sequence of shaped symbols to a receiving device.