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Estimating bit error probability (bep) in an edge wireless systemRelated Patent Categories: Pulse Or Digital Communications, Receivers, Particular Pulse Demodulator Or DetectorEstimating bit error probability (bep) in an edge wireless system description/claimsThe Patent Description & Claims data below is from USPTO Patent Application 20060291591, Estimating bit error probability (bep) in an edge wireless system. Brief Patent Description - Full Patent Description - Patent Application Claims
BACKGROUND [0001] 1. Field [0002] The present disclosure relates generally to wireless communication devices and, more specifically, to a method for estimating the bit error probability (BEP) in a wireless channel between a base station and a mobile station. [0003] 2. Background [0004] As mobile telecommunications evolves, increasing speeds of data transmission to mobile stations enables new types of services to be offered to mobile subscribers. Usage of these services, in turn, generates a demand for ever increasing data rates. The European Telecommunications Standards Institute (ETSI) introduced the General Packet Radio Service (GPRS) as an initial standard to increase data rates by providing packet-switched data to mobile stations based on the Global System for Mobile communications (GSM). Then as an enhancement to GSM data services, ETSI promulgated the Enhanced Data rates for GSM Evolution (EDGE) standard, with a packet-switched portion called Enhanced GPRS (EGPRS). Together, EDGE and EGPRS are described in the TIA/EIA-136-370 standard published by the Telecommunications Industry Association (TIA). Further enhancements to high-speed data transmission based on GSM include the GSM/EDGE radio access network (GERAN) standard specified by the 3.sup.rd Generation Partnership Project (3GPP). The TIA has described the GERAN enhancements in the TIA/EIA-136-370-A revision to its EGPRS-136 standard. For simplicity, the EDGE, EGPRS, TIA/EIA-136-370 and TIA/EIA-136-370-A standards are collectively referred to herein as the "EDGE standard." [0005] The physical layer dedicated to packet data traffic in the EDGE standard is called the Packet Data Channel (PDCH). The physical layer of the EDGE standard is specified in ETSI standard TS 145.008 (3GPP TS 45.008). Both signaling and traffic channels are transmitted over the PDCH. One of the signaling channels is the Packet Associated Control Channel (PACCH). The traffic channel transmitted over the PDCH is called the Packet Data Traffic Channel (PDTCH). [0006] Unlike basic GSM, several of the higher-speed versions of GSM transmit data at multiple data rates. For example, data is transmitted at nine different data rates over the PDTCH. In a process called "link adaptation," the data rate over the wireless channel is adjusted based on the channel condition. When the channel condition is good and the signal-to-noise ratio of the wireless channel is high, data can be transmitted at higher data rates. Conversely, when the channel condition is poor and the signal-to-noise ratio is low, data must be transmitted at slower data rates. Transmitting data using a particular modulation and coding scheme (MCS) at a data rate that is too high for the channel's signal-to-noise ratio can result in a loss of data. Link adaptation increases overall data throughput by using the highest data rate that can dependably be supported using a particular MCS at the signal-to-noise ratio that momentarily exists on the wireless channel. The EDGE standard requires the mobile station periodically to report the channel condition in the PACCH to the base station. The condition of the channel between the base station and the mobile station is expressed in terms of the bit error probability (BEP). The BEP is the expected value of the actual Bit Error Rate (BER) of a signal received by the mobile station over the wireless channel. The base station then transmits data in the PDTCH to the mobile station at the appropriate data rate depending on the channel condition as indicated in the PACCH. [0007] Link adaptation can most effectively be performed when the mobile station reports a BEP that most accurately estimates the actual BER. One way to estimate the BEP is to attempt to calculate the BER itself. A "re-encoding" method is based on determining the number of bit errors that are corrected in the decoding process. Error control decoding, such as that performed by a convolutional decoder, attempts to correct bit errors that are introduced in the wireless channel. Frames that are output from the block deinterleaver and the convolutional decoder of the mobile station are re-encoded and re-interleaved. The resulting re-encoded bits are then compared to the bits received by the block deinterleaver to determine the number of corrected bit errors. The re-encoding method, however, yields inaccurate results because it relies on the assumption that the error control decoding corrects all of the errors that have been introduced by the wireless channel. Therefore, the BEP obtained using the re-encoding method varies depending on the degree of redundancy employed by the various MCS schemes used to transmit the bits over the wireless channel. Even with a poor channel condition, a high redundancy level of the data allows the error control decoding to decode all of the bits correctly and thus yields a more accurate estimated BER. On the other hand, if the channel condition is poor and redundancy level of the data is low, the error control decoding is unable to correct all of the erroneous bits, and an inaccurate estimate of the BER results. Thus, a better channel quality is required to estimate the BER accurately using a lower redundancy MCS scheme, such as MCS9, than using a higher redundancy MCS scheme, such as MCS5. [0008] FIG. 1 (prior art) compares the estimated BEP obtained using the re-encoding method on data from two channels modulated with different MCSs at different redundancy levels of the data. Less error is introduced by the channel modulated with a higher redundancy code. A curve 10 shows the relationship between the signal-to-noise ratio and the BEP of a channel modulated with Gaussian minimum shift keying (GMSK) at a redundancy level of 1.89. Another curve 11 shows the relationship between the signal-to-noise ratio and the BEP of a channel modulated with GMSK at a redundancy level of 1.0. The re-encoding method indicates that at higher noise levels the BEP of the channel modulated at a redundancy level of 1.0 is lower and thus less accurate than the BEP of the channel modulated at a redundancy level of 1.89. Thus, the estimated BEP at a given signal-to-noise ration is not independent of the redundancy level of the data, as required by the EDGE specification. [0009] FIG. 2 (prior art) compares the BEP obtained using the re-encoding method on data transmitted at three different redundancy levels and modulated with octal phase shift keying (8-PSK). A curve 12 shows the relationship between the signal-to-noise ratio and the BEP for a channel with a redundancy level of 2.70. A curve 13 shows the relationship between the signal-to-noise ratio and the BEP for a channel with a redundancy level of 1.32. A curve 14 shows the relationship between the signal-to-noise ratio and the BEP for a channel with a redundancy level of 1.0. Curves 12-14 show that the re-encoding method inaccurately indicates that the BEP decreases, and the channel condition improves, as the redundancy level decreases. [0010] A second way of estimating the BEP involves first measuring the signal-to-noise ratio of the radio frequency (RF) signal that carries the PDCH. The relationship between the measured signal-to-noise ratio and the BER of the PDCH received by the mobile station is empirically determined in a laboratory. The values of BER that vary as a function of the measured signal-to-noise ratio are then stored in a lookup table on the mobile station. This method requires the mobile station to have an estimator of the signal-to-noise ratio in the RF signal. The BEP is determined by using the estimated signal-to-noise ratio to look up the corresponding BER in the lookup table. The accuracy of the BEP in this method depends on the accuracy of the estimated signal-to-noise ratio of the RF signal. Where the channel condition is affected by signal interference and fading, an accurate determination of the signal-to-noise ratio of the RF signal can be difficult, and the BEP estimation is prone to inaccuracy. [0011] A method is sought for accurately determining the bit error probability (BEP) without requiring a direct estimation of the signal-to-noise ratio of the RF signal and without re-encoding the output of the convolutional decoder of the mobile station. Moreover, a method is sought for determining the BEP that is not influenced by the degree of redundancy in the modulation and coding scheme (MCS) used to transmit the data over the wireless channel. SUMMARY [0012] A distribution parameter mapping method estimates the bit error probability (BEP) of bits in a burst transmitted in a radio frequency (RF) signal from a base station to a mobile station using one of the nine modulation and coding schemes (MCSs) specified in the EDGE standard. The BEP estimated using the distribution parameter mapping method is not influenced by the degree of code redundancy in the particular MCS used to modulate data over the RF signal. The circuitry determines whether the multi-bit soft decisions that were equalized from demodulated I and Q samples of the burst most resemble a Gaussian distribution or a Rician distribution. The statistical parameters for the mean (.mu.) and the variance (.sigma.) are determined for soft decisions having a Gaussian distribution. The statistical parameters A and .sigma. are determined for soft decisions having a Rician distribution. The signal-to-noise ratio of the RF signal is represented by the ratio .mu./.sigma. for a Gaussian distribution of soft decisions and by the ratio A/.sigma. for a Rician distribution of soft decisions. The BEP for a burst having a Gaussian distribution of soft decisions is determined by mapping the ratio .mu./.sigma. to an empirically determined BEP in a Gaussian lookup table stored in non-volatile memory on the mobile station. For a Rician distribution, the ratio A/.sigma. is mapped to an empirically determined BEP in a Rician lookup table. The estimated BEPs for the four bursts of each radio block are then averaged, filtered and quantized into one of thirty-two levels according to the EDGE standard. The quantization level of the average BEP is then reported to the base station to permit the base station to transmit subsequent radio blocks using an MCS that is appropriate for the estimated BEP of the signal. [0013] Circuitry in a mobile station that performs distribution parameter mapping to estimate the BEP includes an equalizer, a distribution analyzer, a BEP estimator, lookup tables, an averager, a filter and a non-linear quantizer. The equalizer removes intersymbol interference from demodulated I and Q samples received in bursts from a demodulator in the mobile station. For each burst, the equalizer outputs a distribution of multi-bit soft decisions that are subsequently processed by the mobile station into single-bit hard decisions that comprise frames of data. The distribution analyzer receives the distribution of multi-bit soft decisions from the equalizer and determines the type of distribution that the distribution of multi-bit soft decisions resembles. For example, the distribution of multi-bit soft decisions can resemble a Gaussian distribution or a Rician distribution. The distribution analyzer outputs a distribution type identifier. [0014] The BEP estimator receives the distribution of multi-bit soft decisions from the equalizer, as well as the distribution type identifier from the distribution analyzer. The BEP estimator calculates various statistical parameters of the distribution of multi-bit soft decisions, depending on the type of distribution. When the soft decisions have a Gaussian distribution, the BEP estimator calculates the statistical parameters for the mean (.mu.) and the variance (.sigma.). When the soft decisions have a Rician distribution, the BEP estimator calculates the statistical parameters A and .sigma.. The BEP estimator also calculates the ratio .mu./.sigma. for a Guassian distribution and the ratio A/.sigma. for a Rician distribution. The ratios .mu./.sigma. and A/.sigma. correlate to the signal-to-noise ratios of the I and Q samples. [0015] The BEP estimator estimates the BEP of a burst containing a Gaussian distribution of multi-bit soft decisions by mapping the ratio .mu./.sigma. to an empirically determined BEP in a Guassian lookup table stored on the mobile station. The BEP of a burst containing a Rician distribution of multi-bit soft decisions is estimated by mapping the ratio A/.sigma. to an empirically determined BEP in a Rician lookup table stored on the mobile station. [0016] The averager then averages the estimated BEPs from four bursts and generates a MEAN_BEP. The filter filters the MEAN_BEP and outputs a filtered MEAN_BEP. The non-linear quantizer quantizes the filtered MEAN_BEP into one of thirty-two levels and outputs a value (MEAN_BEP_0 through MEAN_BEP_31) that represents the BEP of the four bursts on a logarithmic scale. [0017] Other embodiments and advantages are described in the detailed description below. This summary does not purport to define the invention. The invention is defined by the claims. BRIEF DESCRIPTION OF THE DRAWINGS [0018] The accompanying drawings, where like numerals indicate like components, illustrate embodiments of the invention. [0019] FIG. 1 (prior art) is a diagram plotting bit error probability (BEP) obtained using a re-encoding method at various signal-to-noise ratios of data modulated with two different GMSK modulation and coding schemes (MCSs), each with a different code redundancy level; [0020] FIG. 2 (prior art) is a diagram plotting BEP obtained using the re-encoding method at various signal-to-noise ratios of data modulated with three different 8-PSK MCSs, each with a different code redundancy level; [0021] FIG. 3 is a simplified block diagram of circuitry that determines BEP using distribution parameter mapping; Continue reading about Estimating bit error probability (bep) in an edge wireless system... 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