This invention relates generally to communications and, more particularly, to wireless systems.
Current and emerging standards for commercial wireless communication systems based on the Code Division Multiple Access CDMA technology (e.g. IS-95, CDMA2000, UMTS) include a sophisticated scheme for control of reverse link transmit power. The overall power control scheme for the reverse link is organized in two layers. The inner layer is called Reverse Inner Loop Power Control (RILPC), while the outer layer is called Reverse-link Outer Loop Power Control (ROLPC).
The inner layer, RILPC, typically requires the base station receiver to periodically obtain some measure of the SNR being received on a given connection, compare it with a target SNR and send a one-bit feedback to the mobile transmitter. The mobile transmitter lowers (raises) its transmit power by a fixed amount (in the dB domain) if the feedback bit indicates that the measured SNR was higher (lower) than the target SNR. As such, RILPC performs the task of varying the transmit power level of the mobile in such a manner that the SNR at the base station receiver for a given connection is close to the target SNR.
The outer layer, ROLPC, is responsible for varying the above-mentioned target SNR so that an end-user receives their desired quality metrics. In a prevailing fading environment, the target SNR needs to be adjusted continually to deliver the desired quality metrics to the end-user. Typically, the ROLPC monitors the quality metric to obtain a reliable estimate of the same and then raises or lowers the target SNR depending upon whether the estimate is worse than or better than the target quality metric.
One quality metric is bit error rate (BER), which is a “post-decoding” quality metric, i.e., it requires decoding the received signal. This is referred to herein as “post-decoding BER-based ROLPC.” Assuming frame-based transmission, one way of obtaining a BER estimate is to use the log-likelihood ratios for information bits. These log-likelihood ratios are produced by certain decoders as part of the frame decoding process and can be used to estimate an instantaneous BER. The instantaneous BER estimate can be further filtered, or averaged, to obtain a more reliable BER estimate that can be used by ROLPC to adjust the SNR target. Unfortunately, approaches along these lines require strong filtering or averaging over a long period of time, which introduces significant delays in the process of generating BER estimates. Consequently, an ROLPC that uses such techniques to generate BER estimates would be slow to change the target SNR.
An alternative to strong filtering, or averaging over a long period of time, is to use, e.g., the instantaneous BER (generated every frame) or process the instantaneous values through a weak filtering scheme (or average them over a short period of time) before comparing them with the target BER. Such a scheme would be able to quickly change the target SNR.
We have observed that even in a steady environment where the statistical nature of the signal fluctuations do not change with time, even the use of an instantaneous BER estimate cannot always set the target SNR at a level where the actual average BER is close to the desired BER. This is because, by its nature, this scheme ensures that in a steady state the median value of the instantaneous BER will be close to the target BER. However, in a typical fading environment characterized by wide signal fluctuations, the difference between the mean and median values of BER can be significant, even exceeding an order of magnitude. Moreover, this difference depends on the underlying fading environment, which determines the depth and correlation properties of signal fluctuations in the communications channel. As a consequence, when the desired end-user quality metric is the mean or average BER, this scheme often fails to achieve its objective.
Therefore, and in accordance with the invention, in performing post-decoding based ROLPC, a user metric target is varied as a function of a “signature” of the communications channel.
In an embodiment of the invention, a base station employs an ROLPC technique using post-decoding BER as the user metric target. The ROLPC technique uses either instantaneous or weakly filtered values of BER for comparison with the target BER value for adjusting a target SNR. The target BER value is varied as a function of a second order statistic (e.g. variance, standard deviation) of the received SNR. The second order statistic of the received SNR is representative of a signature of the communications channel.
In another embodiment of the invention, a base station uses a 2nd order statistic, e.g., standard deviation (variance), to identify, or act as a signature of, a particular cellular (wireless) communications environment. The signature is used to set a target symbol error rate appropriate for the current environment. The (Eb/N0)T target is adjusted as a function of a comparison of the symbol error count with a dynamically adjusted SER target. The base station monitors the standard deviation of the symbol error count of a received signal (transmitted from a mobile station). The (Eb/N0)T target is adjusted as a function of the value of the standard deviation. The adjusted (Eb/N0)T target is used to provide power control. As a result, the inventive concept provides a technique to control FER in a variety of cellular communications environments and, at the same time, keep the performance benefits of a SER based technique.
Before describing the inventive concept, a short description of a fixed symbol error rate (SER) target ROLPC technique is provided. Following this section, the performance results of a simulation of the Fixed SER target ROLPC technique is shown upon which the inventive concept is based. After this performance-related section, the inventive concept is presented.
Fixed SER Target ROLPC
The core of this technique, assuming only full rate frames have been received and that no erasures have occurred, is described below. (It should be noted that dealing with partial rate frames and frame erasures leading to the loss of the rate estimate can be done in a number of ways. For example, partial rate frames could use smaller step sizes for making changes in the (Eb/N0)T target, and, if the rate information is unavailable because of a frame erasure, the last available rate parameter may be used as an estimate for the current frame rate.)
The following definitions are used:
The Fixed SER target ROLPC technique adjusts the (Eb/N0)T target in the following manner:
dn=SEn−TSE; (1)
sgn(dn)=Sign of dn; (2)
if dn=0 then let Ln=0; (3)
Else if Ak-1<|dn|≦Ak for some k>0, Let Ln=Mk; (4)
(TE
if((TE
if(TE
In step (1) of the above technique, initially the variable, dn, is set equal to the difference between the symbol error count generated by the nth frame, SEn, and the target symbol error rate for the nth frame, TSE. In step (2), the function sgn(dn) is set equal to the sign of the variable, dn. In step (3), if the value of the variable, dn is equal to zero, then the variable, Ln, is also set equal to zero and execution proceeds to step (5), described below. However, if the value of the variable, dn, is not equal to zero, then the magnitude of the variable dn is compared to a plurality of intervals, Ak, in step (4). The parameters A0
=0, A1, . . . , AK-1 and AK=∞, define intervals such that if the magnitude of the difference between the actual symbol error count SEn and the target TSE falls in the, say, kth interval, the variable Ln is set equal to the corresponding weight Mk (illustrative values for these variables are given below). In step (5), the (Eb/N0)T target is updated for the next frame, n+1, by adjusting the current (Eb/N0)T target by the basic step size Δ multiplied, as shown, by the value of the variable Ln. This allows one to make large or small changes in the (Eb/N0)T target depending on the magnitude of the difference between the actual symbol error count and the symbol error target. In steps (6) and (7), the (Eb/N0)T target for the next frame is limited by the respective upper and lower limit values.
Performance of Fixed SER Target ROLPC
An illustrative set of performance results of a simulation of the Fixed SER target ROLPC technique under different fading conditions and at different values of the (fixed) SER target TSE are shown in
This simulation used the following set of parameters values:
And incorporated the following list of assumptions.
An Adaptive SER Based ROLPC
As a result of the above observations on the performance of the Fixed SER target ROLPC approach in different communications environments, a symbol error count based ROLPC technique with adaptive SER targets is presented. As a result, the inventive concept provides an SE count based ROLPC technique that achieves desired FER under different fading conditions.
Turning now to
In accordance with the inventive concept, base station 201 performs adaptive SE count based ROLPC on the received signal 211 from mobile station 210.
Before describing the details of the adaptive SE count based ROLPC technique, the core of this approach is described below and shown in
The Adaptive SER based ROLPC technique monitors the following additional variables:
The following are definitions for some key relationships.
Referring to
{overscore (SERn)}=(1−α){overscore (SERn−1)}+αSEn;
{overscore (SER2n)}=(1−α){overscore (SER2n−1)}+αSE2n; and
{overscore (TSE
In accordance with the inventive concept, in step 65 the SER target, TSE, is set using the updated monitored variables. The new SER target thus set is used for the SER comparison for the next frame. In step 65, the following equations are used to set the value of the SER target, TSE, in accordance with the inventive concept:
To prevent wild variations of the symbol error target, upper and lower limits, Smax and Smin, may be placed on TSE (shown below). Similarly, the estimate {overscore (CVn)} may be bounded to limit its fluctuation.
The technique described above uses the coefficient of variation of the symbol error count to set the symbol error target. It should be noted that a similar scheme can be devised for setting the SE target using the standard deviation or the variance of the symbol error count.
Having described the general concept, an illustrative detailed description of an adaptive SER based ROLPC technique in accordance with the principles of the invention is now presented. The following definitions are used (some of these definitions are similar to those used in the above-described Fixed SER target ROLPC technique and are repeated here for convenience):
The following signal values are supplied by the receiver of the base station:
In accordance with the Adaptive SE count based ROLPC technique, the base station processor carries out the computations shown below to update the symbol error target and the (Eb/N0)T target after the base station receiver has just finished processing a frame (and provided current values for R and SEn). It should be noted that for simplicity, the subscript n, representing the nth frame has been dropped from some of the variables, e.g., the variable SEn is shown as SE.
If R>0; (100)
{
SE←SE×R; (101)
d=SE−TSE; (102)
sgn(d)=sign of d; (103)
If d=0, let L=0; (104)
Else {find k such that Ak-1<|d|≦Ak, let L=Mk;} (105)
TE
{overscore (SER)}←(1−α/βR){overscore (SER)}+(α/βR)SE; (107)
{overscore (SER2)}←(1−α/βR){overscore (SER2)}+(α/βR)SE2; (108)
{overscore (TSE
TSE=Sref(FER—target)g({overscore (CV)}/f({overscore (TSE)}), FER—target); (111)
if TSE>Smin, TSE=Smax; (112)
if TSE<Smin, TSE=Smin; (113)
Last—good—rate=R; (114)
}
Else (i.e., if R equals 0 because of frame erasure)
{
R=Last—good—rate (115)
TE
}
If TE
If TE
In step (100) of the above technique, the value of R, received from the base station receiver, is evaluated. A value of R greater than zero is representative of no erasure of the current received frame, while a value of R equal to zero indicates an erasure has occurred. If the value of R is equal to zero, then steps (115) and (116) are performed. In this case, the value of R is set equal to the value of the variable Last—good—rate in step (115). In step (116), the value of the (Eb/N0)T target is updated for the next frame, n+1, by adjusting the current (Eb/N0)T target by δR (as noted above, these are δ1, δ2, δ4, δ8, where R is either 1, 2, 4, or 8). Execution proceeds with step (117), described below. However, if at step (100) the value of R is greater than zero, steps (101) through (114) are performed.
In step (101), the symbol error count, SE, for the current frame is multiplied by the value of R to provide an adjusted value for the symbol error count, SE. In step (102), the variable, d, is set equal to the difference between the value of SE and the target symbol error count for the nth frame, TSE. In step (103), the function sgn(d) is set equal to the sign of the variable, d. In step (104), if the value of the variable, d, is equal to zero, then the variable, L, is also set equal to zero and execution proceeds to step (106), described below. However, if the value of the variable, d, is not equal to zero, then the magnitude of the variable d is compared to a plurality of intervals, Ak, in step (105). The parameters A0=0, A1, . . . , AK-1 and AK=∞, define intervals such that if the magnitude of the difference between the actual symbol error count SE and the target TSE falls in the, say, kth interval, the variable L is set equal to the corresponding weight Mk. In step (106), the (Eb/N0)T target is updated for the next frame, n+1, by adjusting the current (Eb/N0)T target by the basic step size Δ multiplied, as shown, by the value of the variables L and divided by the value of the de-emphasis factor βR (as noted above, these are β1, β2, β4, β8, where R is either 1, 2, 4, or 8). Steps (107), (108) and (109) update the above-described monitored variables. Steps (110) and (111) set the value of the SE count target, TSE, in accordance with the inventive concept. In steps (112) and (113), the SE count target, TSE, is limited by the respective maximum and minimum values. In step (114), the value of the variable Last—good—rate is set equal to the value of R.
In steps (117) and (118), the (Eb/N0)T target for the next frame is limited by the respective upper and lower limit values.
Performance of Adaptive SER Based ROLPC
Simulation results are presented to show how effectively the SE count based ROLPC with adaptive SER targets performs in different environments. Again, it should be noted that in these simulations full rate frames alone are used and that it is assumed that the rate information is never lost because of erasures. The same set of fading environments that were used to study the performance of the basic algorithm with a constant SER target are assumed. The parameters of the adaptive algorithm used in the simulation runs were as follows:
Table 1, below, shows the performance of the proposed SER based algorithm under a variety of fading conditions caused by different mobile speeds.
Table 1 above shows the FER ranging between the narrow range of 1% and 2.2% for the fading environments considered. Thus, indicating that the proposed SE count based algorithm with adaptive SER targets does an admirable job of controlling the FER under widely varying fading conditions. Moreover, its speed is limited only by the speed of the IIR (infinite impulse response) filter used for variable monitoring. When the filter constant, α, is at 0.2, the time constant associated with these filters is around 100 ms (milli-seconds) which should provide adequate speed for environment tracking. As such, the proposed technique with adaptive SER targets can control the FER very well without being encumbered by a slow tracking speed as the FER based ROLPC. It should be noted that, in effect, the Adaptive SE count Based ROLPC approach uses the coefficient of variation of the SE count as a “signature” of the environment and uses this signature to set the SER target appropriately. Similar schemes which use the standard deviation or the variance of the SER as signatures of the environment are also possible.
Other variations are also possible. For example, in the example above, it was assumed that the mobile station is communicating with a single base station. However, when the mobile station is in soft-handoff (communicating with multiple base stations), the symbol error count based control described herein may be performed within MSC 205. In particular, MSC 205 receives received frame information (including symbol error count) from each base station involved in soft-handoff with the mobile station. As known in the art, MSC 205 comprises a frame handler (not shown). The frame handler selects the received frame that has the best quality according to some predetermined criterion. (As just one simple example, the frame with the lowest symbol error count. However, other criteria can be used.) MSC 205 then performs the above-described a symbol error count based ROLPC technique with adaptive SER targets using the selected frame and transmits the results back to the base stations. As yet another alternative, each base station can perform its own SE count based control, in accordance with the principles of the invention, using their respective received frames.
An Adaptive BER Based ROLPC
Base station 201 comprises RAKE receiver 705, MAP (Maximum A-posteriori Probability) decoder 710, BER estimate generator 730, controller 715, look-up table 720 and transmitter 725. RAKE receiver 705 receives the uplink signal for demodulation and provides a symbol stream to MAP decoder 710. (Alternatively, a Log-MAP, or soft output Viterbi (SOVA) decoder can also be used, as is known in the art.) MAP decoder 710 produces a stream of “soft outputs” 711 associated with the information bits of the received frame. The soft output, Λ1, associated with information bit, i, is the log-likelihood ratio associated with it. That is:
The information bit error probabilities are averaged over a frame to produce the bit error rate estimate, BER-I, for that frame. As described further below, controller 715 performs bit error rate based ROLPC with adaptive compensation and adjusts a target SNR, (Eb/N0)T, for use in the ROLPC. In particular, controller 715 determines the standard deviation of the measured SNR (Eb/N0), σEb/N0, and uses the value of σEb/N0 to retrieve an adjustment value, Δ, from look-up table 720. Controller 715 uses the adjustment value, Δ, to adjust the target BER and then performs ROLPC. Controller 715 controls transmitter 725 for providing the earlier-described RILPC feedback signal to mobile station 210 for controlling the transmit signal level of mobile station 210. (As noted earlier, when the mobile station receives this feedback signal, the mobile transmitter lowers (raises) its transmit power by a fixed amount (in the dB domain) if the feedback bit indicates that the measured SNR (Eb/N0) was higher (lower) than the target SNR.)
In the discussion so far, the units for the quantity BER was assumed to be expressed in its normal units. In the illustrative method described below, the quantity BER is expressed in dB units, which are often more convenient in wireless applications. An illustrative method for use by controller 715 for performing bit error rate based ROLPC with adaptive compensation is shown in
In step 805, it is assumed that BER estimate generator 730 forms an estimate of the instantaneous BER (BER-I) once for every received frame (as described earlier) and passes it to controller 715. In step 810, controller 715 performs adaptive compensation of a target BER as a function of the communications channel characteristics and determines an adjusted value of the target BER, i.e., BER-TC. Illustratively, controller 715 determines the standard deviation of the measured SNR (Eb/N0), σEb/N0, and uses the value of σ Eb/N0 to retrieve an adjustment value, Δ, from look-up table 720. Controller 715 uses the adjustment value, Δ, to determine BER-TC. In step 815, controller 715 compares the value of BER-I to the value of BER-Tc. If the value of BER-I is worse than the value of BER-Tc, the target SNR is raised in step 820, e.g., by ΔSNR. Alternatively, if the value of BER-I is better than the value of BER-Tc, the target SNR is lowered in step 825, e.g., by ΔSNR.
As noted above, in step 810 of
The following definitions are now made (some of which were mentioned above):
It is assumed that
The value of σEb/N0 is illustratively evaluated anew every frame as follows. The measured Eb/N0 is filtered through an infinite impulse response (IIR) filter (not shown) to obtain an estimate of the current mean value of Eb/N0, i.e., avg(Eb/N0). Similarly, suitable IIR filtering of the square of the Eb/N0 values provides an estimate of the current mean value of the square of [Eb/N0]2, i.e., avg([Eb/N0]2). (IIR filtering is known in the art and is not described herein). (In other words, Then, σEb/N0 is given by:
σEb/N0=√{square root over (avg([Eb/N0]2)−(avg(Eb/N0))2)}{square root over (avg([Eb/N0]2)−(avg(Eb/N0))2)}. (10)
As can be observed from the definitions above, the target BER set in step 810 of
BER-TC=BER-TI,−Δ; where (11)
Δ=f(σEb/N0). (12)
As shown in
Values for the above-mentioned look-up table (i.e., the mapping of the relationship between Δ and σ Eb/N0) can be determined a priori either analytically or via simulations. For example, with respect to a simulation, different fading environments are characterized by Doppler frequency, and the number and relative strengths of multipaths. For each fading environment, different fixed BER target levels are used in conjunction with the ROLPC to determine the resulting average value of the BER and σEb/N0. From this exercise, for each fading environment the BER target value for which the average value of BER was closest to BER-T is determined. As defined above, Δ denotes the difference (in dB) between this BER target value and BER-T. In addition, the corresponding value of the standard deviation of σEb/N0 is noted. Next, a scatter-plot of these values of Δ and the corresponding values of σEb/N0 is created. Using suitable curve-fitting techniques, the relationship between σEb/N0 and A is obtained (equation (12)) and from which either look-up table entries can be generated; or an equation, which can be calculated in real-time, can be determined.
As a result of the above, a BER-based ROLPC with adaptive compensation for the BER target has been described which accounts for the discrepancies in the mean and median of BER.
It should be noted that one can easily add some features to the basic algorithm described above to make it better suited for practical implementation. For instance, one can place upper and lower limits on SNR-T to prevent wild fluctuations in the same. Also, the amount by which SNR-T is adjusted after each comparison between BER-I and BER-TC can be made dependent on the size of the difference between BER-TC and BER-I. This would allow for rapid adjustments when the SNR target is far from where it is needed to be to achieve the desired BER.
Another equivalent way to modify the metric target value (albeit indirectly) is to change the relative magnitudes of the up and down step sizes of the SNR target as a function of the signature of the environment. For example, a value of BER-I is compared with a value of BER-TI at the end of every received frame. When the value of BER-I is found to be greater than, or equal to, the value of BER-TI, the SNR target value is raised by an amount Δup dB. Conversely, if the value of BER-I is less than the value of BER-TI, the SNR target is lowered by an amount Δdown dB. The ratio
is varied as a function of the signature of the environment. This may be done, for instance, by keeping the value of Δup fixed and varying the value of Δdown as a function of the environment signature; or by keeping the value of Δdown fixed and varying the value of Δup as a function of the environment signature. (The former example is illustrated in the flow chart shown in
As already noted above, the foregoing merely illustrates the principles of the invention and it will thus be appreciated that those skilled in the art will be able to devise numerous alternative arrangements which, although not explicitly described herein, embody the principles of the invention and are within its spirit and scope. For example, although the inventive concept was illustrated herein as being implemented with discrete functional building blocks, e.g., a controller, etc., the functions of any one or more of those building blocks can be carried out using one or more appropriately programmed processors, e.g., a digital signal processor; discrete circuit elements; integrated circuits; etc. In addition, the inventive concept is applicable to other cellular access schemes besides IS-95 or UMTS, power control of other signals received by the base station, and power control by the mobile station of signals received from the base station.
This is a Continuation-In-Part of application Ser. No. 09/052,696 filed Mar. 31, 1998 now U.S. Pat. No. 6,434,124. Related subject matter is disclosed in the co-pending, commonly assigned, U.S. Patent application of Rege, entitled “A Non-Adaptive Symbol Error Count Based Technique for CDMA Reverse Link Outer Loop Power Control,” application Ser. No. 09/052,581, filed on Mar. 31, 1998.
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Number | Date | Country | |
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Child | 09514608 | US |