Correction of received signal and interference estimates

[0001] The present invention relates to telecommunications, and in particular, to accurate estimation and correction of signal levels and interference levels in a CDMA or other spread spectrum system.

[0002] A spread spectrum system is a wideband system in which the entire frequency bandwidth of the system is available to each user all the time. The system expands or spreads the bandwidth of the transmitted information much more than the minimum bandwidth required to transmit the baseband data. The spreading of the data is performed using a spreading sequence, sometimes called a spreading code. Each user in the frequency bandwidth is distinguished from other users by the allocation of different spreading codes to each. Code Division Multiple Access (CDMA) systems are one kind of spread spectrum system.

[0003] Just as a CDMA transmitter spreads a signal across a bandwidth, a CDMA receiver compresses or de-spreads the received signal bandwidth in order to recover the original information. Since different users employ different spreading codes their respective transmissions can be separately decoded at a receiving station.

[0004] Spread spectrum systems have a number of advantages. First, CDMA receivers can diversity combine separate multi-paths using a RAKE receiver. A RAKE receiver enhances the capture of the received signal energy by allocating one of a number of parallel demodulators (referred to as “fingers”) to each of the strongest components of the received multipath signal. The outputs of all the RAKE fingers are combined (taking the best from each finger) after a corresponding delay compensation to construct an optimum received signal.

[0005] Second, CDMA systems tolerate interference up to a certain threshold limit. The introduction of additional active mobile radio transmissions to the CDMA system increases the overall level of interference at the cell site receivers (base stations) receiving CDMA signals from the mobile radio transmitters. Since all users employ the same frequency bandwidth, it is important that no one user dominates the bandwidth with high relative power transmission. The particular level of interference introduced by each mobile's transmission depends on its received power level at the cell site, its timing synchronization relative to other sites at the cell site, and its specific cross-correlation with other transmitted CDMA signals. For that reason, power control is very important in CDMA systems. Typically, power control attempts to achieve a constant mean power level for each mobile user received at a base station taking into account the transmission power at the mobile and the pathloss from the mobile to the base station.

[0006] The CDMA base stations control mobile transmit power of each mobile user based on Signal-to-Interference Ratio (SIR) measurements of mobile transmission received at the base station. The SIR is defined as the ratio of the data bit energy (E_b) to the interference (including noise) power spectral density (I_o).

[0007] SIR measurements are compared with a reference E_b/I_o, value, and depending on the result, the mobile is ordered to increase or decrease its transmit power by some predetermined amount, (e.g., 1 dB). Other kinds of SIR measurements can be used to adjust the reference E_b/I_o level in order to achieve a specified frame error rate at the base station.

[0008] Thus, to ensure that no mobile station dominates the bandwidth by using excessive power levels, the system measures or determines E_b and I_o values for each mobile. Based on those measurements, the system instructs the mobiles to adjust their power levels to appropriate, non-dominating values.

[0009] An estimation of data bit energy E_b can be performed after de-spreading and RAKE combining in the receiver. Depending on the SIR measurement application, it may be performed using a short or a long averaging period. A short averaging period is used when the E_b value is measured using only pilot preamble symbols transmitted at the beginning of each time slot within a data frame. For long-term SIR measurements, E_b values obtained for the pilot preamble and for each individual data symbol are averaged over the time slot period, and E_b values obtained from all slots are averaged at the end of the frame to produce the final long term E_b measurement value.

[0010] In both short and long term SIR measurement, the interference power I_o may be averaged over a number of frames. More specifically, I_o may be obtained by correlating the input signal multiple times with an uncorrelated (in the ideal case, orthogonal) spreading code or with time-shifted versions of the original spreading code used at the transmitter and averaging the multiple, squared, absolute correlation values over the number of frames.

[0011] The accuracy of the received signal level, interference level and received signal energy measurements and estimations are very important in the CDMA system to ensure good signal quality and maximum system capacity. Commonly-assigned U.S. Pat. No. 6,229,842, “Adaptive Path Selection Threshold Setting for DS-CDMA Receivers,” by Schulist et al is a prior method of interference level measurements. It, however, exhibits larger errors as increases, as shown in the graph of FIG. 1. As shown in FIG. 1, as increases, measurement error of the received interference level is dramatic. It is likely caused mainly by non-zero auto-correlation of the spread sequence, namely pn (K)·pn (K+t)¹0 when t¹0 where pn (K) is the spreading code for sample index K and pn (K+t) is the spreading code for an incremented (non-zero) sample index. The mean error shown in FIG. 1 depends on the received signal level and increases as increases.

[0012] An Ericsson-internal document “Base Station Demodulator,” by Ning He, illustrates and describes the specific structure of a demodulator that may form the basis for SIR measurement, estimation and correction in the present CDMA system. “Base Station Demodulator” also describes, beginning for example at page 23 and continuing, power and interference estimations and corrections. The measurement of received signal level provided by the methods described in that publication saturates at low values, as shown in FIG. 2. FIG. 2 illustrates that the relation between actual and estimated SIR is approximately linear for input values above about 10 dB; however, below 10 dB, the SIR measurement values saturate.

[0013] Saturation of SIR values is problematic in that the measured SIR value will be used by the base station to instruct the mobile to adjust its transmission power levels. Where the measurements linearly track the ideal SIR, the instructions from the base station will accurately reflect proper adjustments for the true input signal strength. But, at levels where the curve is saturated, the base station may provide power level adjustment instructions that bear little relation to the true input signal levels. At worst, the saturation can cause an unstable power control loop for certain input signal levels.

[0014] In the case of FIG. 2, the measurement error of the received signal level is caused mainly by the noise/interference component in the measurement. The mean error depends on the interference level and increases as E_b/I_o decreases.

[0015] A combination of the signal measurements (FIG. 1 and interference measurements (FIG. 2) yields an SIR with saturation problems at both the upper and lower input values, as shown in FIG. 3. There, linearization between actual and measured SIR values is poor across most of the curve, but especially so below about 5 dB and above about 20 dB.

[0016] U.S. patent application Ser. No. 09/038,067 (filed Mar. 11, 1998), describes a piece-wise linearization method for correcting SIR measurements. Its method is quite sensitive in the saturation regions. In an example embodiment of that disclosure, an SIR correction function includes a linear part and a non-linear part, with the non-linear part corresponding to an inverse of an exponential function that approximates a non-linear portion of a curve corresponding to measured SIR values. In a second example embodiment, the linear part of the SIR correction function further includes first and second linear components to improve the accuracy of the correction function in certain situations. The parameters in the correction function in both of the first and second example embodiments are selected to minimize error between corrected SIR values and corresponding actual or ideal SIR values.

[0017] The present invention provides an alternative method of correcting SIR values in which the signal strength value and interference value are corrected separately. Since the errors associated with signal strength measurements and those associated with interference estimates derive from different sources, independent correction is found to provide improved overall SIR correction. Thus, unlike “Base Station Demodulation” where SIR per se is corrected (see for example equation 34 therein) and “Correction of signal-to-interference ratio measurements” by Popovic, where SIR per se is also corrected (see for example equations 3 and 4 and associated text), the present invention corrects the SIR by first correcting signal and interference values independently and then combining the corrected signal and corrected interference into a corrected SIR.

[0028] FIG. 7 illustrates an example CDMA cellular radio telephone system in which the present invention may be employed. In general, the CDMA system 11 employs spread spectrum techniques to modulate and de-modulate communications between the mobile stations MS and base stations BS₁, BS₂, . . . BS_n. The system control and switch 12 controls the communications between the base station BS₁, BS₂ . . . BS₉ to other networks 10 including, for example, public switch telephone networks, the Internet, etc. The system control and switch 12 also facilitates communications between the base stations BS₁, BS₂, . . . BS_n.

[0029] As is well known, each base station BS₁, BS₂, . . . BS_n generally services an assigned geographical cell area. As the mobile stations MS move in and out of the various cells, they will establish communications with the associated base stations for communication with the other networks 10 and other mobile stations MS. When a mobile station enters the geographical area assigned to a particular base station, for example, base station BS₂ in FIG. 7, the mobile station establishes communication with the base station BS₂. As described previously, one function of the base station BS₂ and system 12 in facilitating communications within a particular cell is to ensure that transmission power levels at the base station BS₂ are relatively uniform among the various mobile stations communicating within the cell. For this purpose, the base station BS₂ takes frequent measurements of received signal strength for each mobile station in its geographic area and provides the associated mobile stations with the power control information. The power control information instructs the mobile station to increase or decrease power levels in order to relatively unify the power level of any particular mobile station with those of the other mobile stations in the cell vis-a-vis the received signal strength at the base station BS₂. The way in which the received signal strength and measured interference are obtained by the base station BS₂ is not particularly critical to the present invention. An example method of how these signal and interference values may be measured in the first instance is described, for example, in “Base Station Demodulator: Releases R2 & R3 & R4” by Ning He.

[0030] As shown in FIG. 8, a de-modulator 23 of, for example, a base station BS2, will receive signals from a mobile station via antennas 20-21 and radio receiver 22. In the preferred embodiment, the receiver will take the form of a well-known RAKE receiver in which a signal from a mobile station is collected from a number of RAKE receiver fingers and combined in the RAKE receiver. Thus, in the RAKE finger receivers, signal energy from the multiple paths are detected by a searcher unit 24 and are collected in order to exploit the multi-path characteristics of the transmission channels. The de-modulator 23 also includes a de-spreading function which transforms the desired receive signal from the wide band representation associated with spread spectrum to narrow band representation suitable for signal information retrieval.

[0031] The signal detector 26 of the de-modulator 23 at the base station BS measure the received power level by compiling and processing the relative logical channel power levels delivered from the fingers of the RAKE receiver in each slot. The interference detector 27 may obtain I_o by correlating the input signal a multiple number of times with an un-correlated (in the preferred case, orthogonal) spreading code and averaging the multiple, squared, absolute correlation values over the number of frames. Alternatively, I_o may be obtained by correlating the input signal multiple times with time-shifted versions of the original spreading code used at the transmitter and, again, averaging the multiple, squared, absolute correlation values over the number of frames.

[0032] At block 28 of the de-modulator 23, the measured E_b values from E_b detector 26 and the measured I_o values from I_o detector 27 are combined into the E_b/I_o (SIR) value. The SIR values in the respective detectors are corrected in accordance with further aspects of the present invention described below, with respect to FIG. 9. There, the SIR correction function begins at step 30. At step 31, K_i and K_s constants are determined and depend on the spreading code employed. The values K_i and K_s can be carried out by, for example, simulation in order to determine their constant values. That is, the values K_i and K_s depend upon the measured SIR curve, the shape of which is the function of the spreading factor and the number of values used for non-coherent averaging. The parameters K_i and K_s are determined to minimize the maximum absolute error between the ideal and corrected SIR curves and can be determined using manual tests and observation or using available numerical optimization algorithms.

[0033] At step 32, the receive signal strength E_b is measured at the E_b detector 26. At step 23, the interference level I_o is measured or estimated at the I_o detector 27.

[0034] At step 34, the interference value I_o is corrected by the factor K_i·E_b in accordance with the equation:
I_corr=I_o−K_i·E_b,

• • [0035] where E_b is the received signal level, I_o is the measured interference level, and K_i is a constant depending only on the spreading code and determined by simulation. FIG. 4 illustrates a graph of the measured relative interference power I_corr after correction versus the actual interference power. One can see from FIG. 4 that the corrected interference power closely tracks the actual interference power along a wide range of input signal values.

[0036] In a similar manner, the received signal strength E_b is corrected at step 35 of FIG. 9 in accordance with the equation:
E_corr=E_b−K_s·I_corr,

• • [0037] where I_corr is the corrected interference level from the above equation, K_s is a constant depending only on the spreading code and determined by simulation, and E_b is the measured signal strength at the base station. FIG. 5 is a graph of the measured relative signal power E_corr after correction at step 35 versus the actual relative signal power. One can see that the corrected signal strength closely tracks the actual received signal power along a wide range of input signal strengths.

[0038] At step 36, the SIR value E_corr/I_corr is calculated using the values obtained at steps 34 and 35. That is, instead of a measured SIR value being corrected per se, the signal value per se and the interference value per se are corrected in accordance with steps 34 and 35 and the SIR value is then, thereafter, obtained at step 36. FIG. 6 is a graph of the SIR value obtained at step 36 after correction versus the actual SIR value. As one can see from FIG. 6, the corrected SIR value closely mirrors the actual SIR value along a wide range of input signal values.

[0039] In comparison to FIG. 3, where the measured SIR value deviates significantly from the actual SIR value, and provides substantial saturation portions in the high and low SIR regions, FIG. 6 shows marked improvements in the linear tracking of the corrected SIR value versus the actual SIR value. In particular, as shown in FIG. 6, the saturation regions at the upper and lower ends of the curve of FIG. 3 have been essentially removed. Thus, more precise and reliable power control can be provided in accordance with the present invention than can be provided by the embodiment of FIG. 3.

[0040] Even compared to the SIR correction measurements of U.S. patent application Ser. No. 09/038,067, where the SIR value is corrected as a whole rather than as its respective components, one can see good improvement in the linearity of the after correction SIR values. This is shown, for example, by comparing FIG. 6 of the present invention (where the corrected SIR value closely tracks and smoothly tracks the actual SIR value) to the similar curve in FIG. 6 of U.S. application Ser. No. 09/038,067 (where saturation regions have been well-compensated but some non-smooth irregularity remains).

[0041] It is thus apparent that, since signal power and interference measurements have associated errors caused by different sources, it is advantageous to correct them independently of each other prior to combination into a corrected SIR value, rather than calculating the SIR value and thereafter providing correction techniques.

[0042] While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not to be limited to the disclosed embodiment, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.