Interference Network Coding with Sliding-Window Superposition Decoding
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Solution Overview
Problem
Existing communication systems face performance degradation in dense wireless networks due to strong interference, as they typically treat interference as noise, leading to suboptimal performance compared to simultaneous decoding, which requires high-complexity multiuser sequence detection.
Innovation Solution
The sliding-window superposition coding (SWSC) technique decomposes data streams into substreams, encodes them across multiple blocks, superimposes codewords, and uses low-complexity decoding within a sliding window, allowing for simultaneous decoding performance without high-complexity multiuser detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If simultaneous decoding is used to achieve optimal performance in dense wireless networks, then the data rate and reliability are improved, but the computational complexity increases significantly due to high-complexity multiuser sequence detection
Solution Approach 1:
The patent segments the data stream into multiple substreams and applies rate splitting, where each substream is encoded separately with different power levels. This segmentation allows the receiver to decode substreams sequentially rather than performing complex joint detection of all users simultaneously, thereby achieving near-optimal performance with reduced computational complexity
Solution Approach 2:
The patent changes the power allocation parameter by assigning different power levels to different substreams based on channel conditions and interference levels. This parameter optimization enables the system to achieve better performance while maintaining lower decoding complexity by prioritizing the decoding of stronger substreams first
2Device complexity
If interference is treated as noise to reduce decoding complexity, then the computational complexity is reduced, but the performance degrades significantly in high signal-to-noise ratio conditions
Solution Approach 1:
The patent introduces an intermediary approach by using rate splitting and superposition coding, where the received signal is decomposed into multiple layers corresponding to different substreams. The receiver sequentially decodes these layers, treating decoded substreams as known signals for subsequent decoding steps, thereby avoiding the need to treat all interference as noise while maintaining manageable complexity
Solution Approach 2:
The patent employs dynamic decoding strategies where the receiver adapts its decoding order and power allocation based on instantaneous channel conditions and interference levels. This dynamic approach allows the system to switch between treating certain signals as interference and decoding them sequentially, optimizing performance while controlling complexity
Data Source
AI summary
The disclosed techniques allow for transmitting a signal stream from a sender to a receiver in an environment including multiple senders and receivers. The technique for the sender decomposes a data stream from the sender into multiple substreams, encodes a substream by a codeword, further superimposes multiple codewords to form a signal stream in an asynchronous manner, and transmits the signal stream to the receiver. A codeword can span over multiple blocks. The receiver receives a first codeword stream from a first sender, receives a second codeword stream from a second sender, the two codeword streams may be received at the same time as one signal, and decodes the first codeword stream and second codeword stream over a sliding window of multiple blocks.