SNR ESTIMATION AND BIT ALLOCATION APPLIED IN LOGGING TELEMETRY EQUIPMENT
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- 英文论文题名：SNR ESTIMATION AND BIT ALLOCATION APPLIED IN LOGGING TELEMETRY EQUIPMENT
- 论文作者：Lan YANG ; Hao CHEN ; Xiu-ming WANG ; Liang TANG
- 英文论文作者：Lan YANG ; Hao CHEN ; Xiu-ming WANG ; Liang TANG ; Institute of Acoustics ; Chinese Academy of Sciences
- 年：2016
- 作者机构：Institute of Acoustics, Chinese Academy of Sciences;
- 英文论文关键词：Data transmission ; Cable channel ; SNR estimation ; Bit allocation
- 会议召开时间：2016-10-21
- 会议录名称：2016年全国压电和声波理论及器件应用研讨会论文摘要集
- 英文会议录名称：Abstract Book of 2016 Symposium on Piezoelectricity, Acoustic Waves and Device Applications
- 语种：英文
- 分类号：TN929.53
- 学会代码：AGLU
- 会议名称：2016年全国压电和声波理论及器件应用研讨会
- 会议地点：中国陕西西安
- 主办单位：中国力学学会、中国声学学会、IEEE UFFC分会
- 学会名称：中国力学学会
- 页数：2
- 文件大小：90k
- 原文格式：D
- 会议级别：全国
摘要
Background, Motivation and Objective Orthogonal Frequency Division Multiplexing(OFDM) is one of the multi-carrier modulation techniques, which has a high spectrum efficiency and resist the channel fading effects. It divides the whole channel bandwidth into many orthogonal sub-channels, which overlap each other and transmit data simultaneously. Consequently, logging high speed data communication system is realized by OFDM technique. SNR(Signal to Noise Ratio) is a significant parameter of communication, and it has a great impact on signal quality for communication systems. The SNR estimation of channel and bit allocation are the key techniques of OFDM. SNR of each sub-carriers needs to be estimated accurately. And each sub-channels are allocated different bits on the basis of SNR. This is beneficial to make the total bits of per symbol maximal and then achieve high transmission rate. Compared with wireless channels, cable channels, for instance logging cables, change slowly. In the partial time snippet, it is regarded as a time-invariant system. Accordingly, several detecting frames are transferred firstly to estimate the channel parameters. And then the system only sends data frames. Besides, due to various non-ideal factors there is colored noise in the actual cable channel. As a result, the SNR estimation method used in cable channels is different from that in wireless channel. Statement of Contribution/Methods All the SNR estimation algorithms can be divided into data-aimed(DA) algorithms and non-data-aimed(NDA) algorithms. NDA algorithms occupy the spectrum resources, which decrease the efficiency of spectrum. This paper selects the DA estimation algorithm. Many existing DA algorithms assumed that the channel was additive white Gaussian noise channel. Accurate estimation of SNR in the cable channel wasn't obtained by these methods. The logging cable is one of cable channels, which has colored noise and frequency-selective fading. Therefore, this paper proposes an improved algorithm to evaluate SNR of the logging cable. It combines MMSE SNR estimation algorithm with channel response difference SNR estimation algorithm. The algorithm uses the relativity of noise power between sub-carriers. Then, the bits of sub channels are allocated dynamically according to the SNR parameter. It is based on the formula of channel capacity. Results The figure shows the real values of the logging cable and the estimated values by the improved algorithm and channel response difference SNR estimation algorithm. Compared with the estimated values by channel response difference SNR estimation algorithm, the estimated values by the improved algorithm are closer to the real values. In the condition of certain bit error rate(BER), the adaptive allocation transmits more bits per symbol than the fixed bit allocation. When the system is designed to achieve certain high transmission speed, the adaptive allocation system has lower BER than the fixed bit allocation. Discussion and Conclusions The result shows that the improved algorithm used in the SNR estimation of logging cable obtain more smoothing and more accurate estimation. And the system using the adaptive allocation algorithm has better performance. These two algorithm has actual meaning for the design of real equipment.
Background, Motivation and Objective Orthogonal Frequency Division Multiplexing(OFDM) is one of the multi-carrier modulation techniques, which has a high spectrum efficiency and resist the channel fading effects. It divides the whole channel bandwidth into many orthogonal sub-channels, which overlap each other and transmit data simultaneously. Consequently, logging high speed data communication system is realized by OFDM technique. SNR(Signal to Noise Ratio) is a significant parameter of communication, and it has a great impact on signal quality for communication systems. The SNR estimation of channel and bit allocation are the key techniques of OFDM. SNR of each sub-carriers needs to be estimated accurately. And each sub-channels are allocated different bits on the basis of SNR. This is beneficial to make the total bits of per symbol maximal and then achieve high transmission rate. Compared with wireless channels, cable channels, for instance logging cables, change slowly. In the partial time snippet, it is regarded as a time-invariant system. Accordingly, several detecting frames are transferred firstly to estimate the channel parameters. And then the system only sends data frames. Besides, due to various non-ideal factors there is colored noise in the actual cable channel. As a result, the SNR estimation method used in cable channels is different from that in wireless channel. Statement of Contribution/Methods All the SNR estimation algorithms can be divided into data-aimed(DA) algorithms and non-data-aimed(NDA) algorithms. NDA algorithms occupy the spectrum resources, which decrease the efficiency of spectrum. This paper selects the DA estimation algorithm. Many existing DA algorithms assumed that the channel was additive white Gaussian noise channel. Accurate estimation of SNR in the cable channel wasn't obtained by these methods. The logging cable is one of cable channels, which has colored noise and frequency-selective fading. Therefore, this paper proposes an improved algorithm to evaluate SNR of the logging cable. It combines MMSE SNR estimation algorithm with channel response difference SNR estimation algorithm. The algorithm uses the relativity of noise power between sub-carriers. Then, the bits of sub channels are allocated dynamically according to the SNR parameter. It is based on the formula of channel capacity. Results The figure shows the real values of the logging cable and the estimated values by the improved algorithm and channel response difference SNR estimation algorithm. Compared with the estimated values by channel response difference SNR estimation algorithm, the estimated values by the improved algorithm are closer to the real values. In the condition of certain bit error rate(BER), the adaptive allocation transmits more bits per symbol than the fixed bit allocation. When the system is designed to achieve certain high transmission speed, the adaptive allocation system has lower BER than the fixed bit allocation. Discussion and Conclusions The result shows that the improved algorithm used in the SNR estimation of logging cable obtain more smoothing and more accurate estimation. And the system using the adaptive allocation algorithm has better performance. These two algorithm has actual meaning for the design of real equipment.
Background, Motivation and Objective Orthogonal Frequency Division Multiplexing(OFDM) is one of the multi-carrier modulation techniques, which has a high spectrum efficiency and resist the channel fading effects. It divides the whole channel bandwidth into many orthogonal sub-channels, which overlap each other and transmit data simultaneously. Consequently, logging high speed data communication system is realized by OFDM technique. SNR(Signal to Noise Ratio) is a significant parameter of communication, and it has a great impact on signal quality for communication systems. The SNR estimation of channel and bit allocation are the key techniques of OFDM. SNR of each sub-carriers needs to be estimated accurately. And each sub-channels are allocated different bits on the basis of SNR. This is beneficial to make the total bits of per symbol maximal and then achieve high transmission rate. Compared with wireless channels, cable channels, for instance logging cables, change slowly. In the partial time snippet, it is regarded as a time-invariant system. Accordingly, several detecting frames are transferred firstly to estimate the channel parameters. And then the system only sends data frames. Besides, due to various non-ideal factors there is colored noise in the actual cable channel. As a result, the SNR estimation method used in cable channels is different from that in wireless channel. Statement of Contribution/Methods All the SNR estimation algorithms can be divided into data-aimed(DA) algorithms and non-data-aimed(NDA) algorithms. NDA algorithms occupy the spectrum resources, which decrease the efficiency of spectrum. This paper selects the DA estimation algorithm. Many existing DA algorithms assumed that the channel was additive white Gaussian noise channel. Accurate estimation of SNR in the cable channel wasn't obtained by these methods. The logging cable is one of cable channels, which has colored noise and frequency-selective fading. Therefore, this paper proposes an improved algorithm to evaluate SNR of the logging cable. It combines MMSE SNR estimation algorithm with channel response difference SNR estimation algorithm. The algorithm uses the relativity of noise power between sub-carriers. Then, the bits of sub channels are allocated dynamically according to the SNR parameter. It is based on the formula of channel capacity. Results The figure shows the real values of the logging cable and the estimated values by the improved algorithm and channel response difference SNR estimation algorithm. Compared with the estimated values by channel response difference SNR estimation algorithm, the estimated values by the improved algorithm are closer to the real values. In the condition of certain bit error rate(BER), the adaptive allocation transmits more bits per symbol than the fixed bit allocation. When the system is designed to achieve certain high transmission speed, the adaptive allocation system has lower BER than the fixed bit allocation. Discussion and Conclusions The result shows that the improved algorithm used in the SNR estimation of logging cable obtain more smoothing and more accurate estimation. And the system using the adaptive allocation algorithm has better performance. These two algorithm has actual meaning for the design of real equipment.
引文