BER Estimation via Soft Bit Counting in Wireless Systems
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Solution Overview
Problem
Current methods for estimating bit error rate (BER) in transport channels of wireless communication systems are either computationally intensive due to re-encoding requirements or assume known noise distributions, which is not always feasible in real scenarios, leading to inaccuracies and high latency.
Innovation Solution
A method that estimates BER by counting erroneous soft bits in the outer tails of noise distributions and dividing by total bits, independent of decoder performance and noise distribution shape, using algorithms that select based on channel parameters like spreading factor and transport channel size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the straight forward (brute force) method is used for BER estimation, then measurement accuracy is improved, but computational complexity and latency increase due to re-encoding requirements
Solution Approach 1:
The patent extracts only the essential information needed for BER estimation from the decoded data, specifically counting erroneous bits without requiring full re-encoding. This selective extraction maintains measurement accuracy while dramatically reducing computational complexity by eliminating the intensive re-encoding process.
Solution Approach 2:
Instead of the conventional approach of encoding→transmitting→decoding→re-encoding for BER measurement, the patent inverts the process by performing BER estimation directly on the decoded data by counting errors, thereby avoiding the computationally intensive re-encoding step while maintaining measurement validity.
2Measurement precision
If the straight forward (brute force) method is used for BER estimation, then measurement accuracy is improved, but latency increases due to decoding stage position
Solution Approach 1:
The patent performs BER estimation as a preliminary action immediately after decoding, counting erroneous bits before any subsequent processing. This early measurement approach maintains accuracy while reducing latency by establishing the BER value at the earliest possible point in the processing chain.
3Device complexity
If the SNR to BER conversion method is used, then computational complexity is reduced, but measurement accuracy deteriorates when noise distribution is unknown
Solution Approach 1:
The patent employs a self-service approach where the system directly counts erroneous bits from the decoded data without requiring external assumptions about noise distribution characteristics. This self-contained method maintains measurement accuracy while keeping computational complexity low, as it neither requires complex SNR calculations nor assumptions about noise patterns.
4Measurement precision
If decoder-dependent BER estimation is performed, then measurement accuracy is improved, but adaptability deteriorates across different decoder types
Solution Approach 1:
The patent implements a universal BER estimation method that works across different decoder types by counting erroneous bits directly from decoded data. This approach is decoder-independent and can be applied universally to various coding schemes (convolutional, turbo, LDPC, polar codes) without requiring decoder-specific adjustments, thereby achieving both accuracy and adaptability.
Data Source
AI summary
There is provided a method of estimating a bit error rate in a transport channel of a wireless communication system. The method comprises the receiving a signal from a remote transmitter of the wireless communication system via a physical channel, the signal comprising data and noise forming a plurality of soft bits. The method further comprises the counting, during a period of time, a number of erroneous bits being those soft bits which have an amplitude below −2A or above +2A with A being the average amplitude of the soft bits received. Next, the number of erroneous bits is divided by a number of total bits received during said period of time in order to obtain the bit error rate. This method provides a way to estimate the BER value without knowing the exact shape of the noise distribution. In an embodiment a selection is made between two estimation algorithms.