Mixed Data String Encoding for Compact RFID Tag Memory
Solution Overview
Problem
Current RFID and barcode encoding methods lack efficiency in compacting data and accessing specific data elements, particularly in mixed data strings, leading to increased bit usage and slower data transfer rates due to limitations in existing standards and encoding schemes.
Innovation Solution
A method that generates a character map for alphanumeric strings, identifies runs of like characters, and encodes them into binary substrings, allowing for reduced character maps and efficient decoding by parsing run fields to determine character types and lengths, thereby optimizing data encoding and access in RFID tags and barcodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If existing standard data formats (ISO/IEC 15961 and 15962) are used for encoding RFID tag data, then data can be stored in RFID tags, but the compaction efficiency is poor and the number of bits required to encode data is large
Solution Approach 1:
The data string is segmented into runs of consecutive characters of the same type (alphanumeric, numeric, etc.). Each run is independently encoded, allowing the system to exploit the statistical properties of each segment separately. This segmentation enables more efficient encoding by treating homogeneous character sequences as unified units rather than individual characters, thereby reducing the total number of bits required.
Solution Approach 2:
The encoding scheme dynamically changes parameters based on the data characteristics. When runs of like characters are detected, the encoder switches to a specialized run-length encoding mode that uses fewer bits. The system adapts its encoding parameters (character set size, bit allocation) according to the actual data composition, transitioning between different encoding modes to optimize compaction efficiency for each specific data pattern.
2Ease of operation
If the entire memory bank is read to access a desired data element, then complete data access is achieved, but the reading process is slowed down due to reading many useless bits
Solution Approach 1:
The data is pre-structured into runs of like characters with associated metadata indicating the position and length of each run. This preliminary organization allows the reading system to directly calculate the position of desired data elements without sequentially reading through intervening bits. The pre-computed run structure enables jump-to-position access, significantly reducing the time required to retrieve specific data elements from the memory bank.
3Adaptability or versatility
If Gen 2 air interface protocol is used for RFID communication, then standardized communication is achieved, but there is no good mechanism for accessing a variable amount of memory without requiring multiple operations
Solution Approach 1:
The patent introduces a new dimension to memory addressing by organizing data into runs with explicit position and length metadata. This additional structural dimension allows the system to specify memory access requests in terms of run positions rather than sequential byte addresses. The run-based addressing scheme enables variable-length memory access in a single operation by directly addressing the desired run's position and retrieving exactly that many bits, eliminating the need for multiple read operations to handle variable data lengths.
Data Source
AI summary
An encoding method comprises generating a character map of an alphanumeric character string, identifying runs of like character type symbols in sequential positions, and removing the runs of character type symbols from the character map. The center for the center infix run is determined, and the characters of each character type are encoded into binary encoded substrings. A decoding method comprises parsing the one or more run fields in the alphanumeric header to determine a number of characters of each type of a plurality of character types represented in the binary encoded string, generating a character map having a string of character type symbols representing the binary encoded string, including determining a reduced character map, centering the character type symbols for a center infix run about the center of the reduced character map, completing a final character map, and decoding each binary encoded string.