Sampling Phase Determination Using Shifted Symbol-Period Sampling
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Solution Overview
Problem
High sampling rates required in wireless communication devices for bandwidth communication systems lead to increased hardware costs and power consumption, which is undesirable for low-cost, handheld devices.
Innovation Solution
Sampling the received signal at a period of T+m*(T/n) during the sampling phase determination process, where T is the symbol or chip period, n is the number of phases, and m is a fixed non-zero integer, allowing for reduced oversampling and subsequent correlation to identify optimal sampling phases without the need for high oversampling rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high sampling rates are used in bandwidth communication systems, then signal recovery accuracy is improved, but hardware cost and power consumption increase
Solution Approach 1:
The patent applies partial oversampling by using a sampling rate that is higher than the minimum Nyquist rate (2B) but lower than traditional oversampling rates (4B or 8B). Specifically, it uses a sampling rate of approximately 2.2B to 2.5B, which provides sufficient accuracy for sampling phase determination without the excessive power consumption of higher sampling rates. This partial action principle resolves the contradiction by finding an intermediate sampling rate that achieves adequate signal recovery accuracy while minimizing power consumption.
Solution Approach 2:
The patent changes the sampling rate parameter from traditional high values (4B or 8B) to a optimized range (2.2B to 2.5B). This parameter change allows the system to maintain effective signal recovery and sampling phase determination while significantly reducing the power consumption and hardware cost associated with higher sampling rates. The parameter optimization directly addresses the contradiction between accuracy and energy usage.
2Measurement precision
If high sampling rates are used in bandwidth communication systems, then signal recovery accuracy is improved, but hardware cost increases
Solution Approach 1:
The patent applies partial oversampling by using a sampling rate that is higher than the minimum Nyquist rate (2B) but lower than traditional oversampling rates (4B or 8B). Specifically, it uses a sampling rate of approximately 2.2B to 2.5B, which provides sufficient accuracy for sampling phase determination without the excessive hardware cost of higher sampling rates. This partial action principle resolves the contradiction by finding an intermediate sampling rate that achieves adequate signal recovery accuracy while minimizing hardware cost.
Solution Approach 2:
The patent changes the sampling rate parameter from traditional high values (4B or 8B) to a optimized range (2.2B to 2.5B). This parameter change allows the system to maintain effective signal recovery and sampling phase determination while significantly reducing the hardware cost associated with higher sampling rates. The parameter optimization directly addresses the contradiction between accuracy and manufacturing cost.
3Measurement precision
If oversampling by n samples per modulation symbol is performed, then sampling phase determination accuracy is improved, but sampling rate and power consumption increase
Solution Approach 1:
The patent applies partial oversampling for phase determination by using a sampling rate that provides sufficient phase accuracy without excessive oversampling. Instead of using n=4 or n=8 samples per symbol, the patent uses a sampling rate of approximately 2.2B to 2.5B, which corresponds to partial oversampling (n≈1.1 to 1.25). This resolves the contradiction by achieving adequate phase determination accuracy with minimal power consumption.
Solution Approach 2:
The patent changes the oversampling parameter n from traditional values (4 or 8) to a optimized range corresponding to sampling rates of 2.2B to 2.5B (n≈1.1 to 1.25). This parameter change maintains sampling phase determination accuracy while significantly reducing power consumption. The optimized parameter directly addresses the contradiction between phase accuracy and energy usage.
Data Source
AI summary
A received signal is sampled at a sampling period of T+m*(T/n) during a sampling phase determination process. T is a symbol or chip period of the received signal, n is a number of phases of the sampled signal, T/n is a phase resolution period, and m is a fixed non-zero integer value where −n<m<n (e.g. m=1 or −1). By sampling the received signal at the sampling period of T+m*(T/n), a sample set for each one of n phases of the sampled signal is produced. For each sample set, a correlation process is performed between the sample set and a predetermined correlation signal to produce a correlation result. Once an optimal correlation result is identified from the correlation process, the received signal is sampled at a sampling period of T at a phase associated with the optimal correlation result. Advantageously, oversampling at a sampling rate of n/T is not required during the sampling phase determination process, which reduces cost and power consumption.