KR20040104386A - Discontinuous transmission detection method - Google Patents

Abstract

PURPOSE: A discontinuous transmission detection method is provided to identify an erroneous deletion of discontinuous transmission by maintaining symbol energy metric values for all discontinuous transmissions irrespectively of channel statuses. CONSTITUTION: A discontinuous transmission detection method determines whether a transmission frame associated with a checksum error is due to a discontinuous transmission. Soft symbols corresponding to the transmission frame are combined to obtain an energy term(207). The energy term is normalized to obtain a metric(208), so suppressing an effect of channel statues. The metric is compared with a threshold value to determine whether a non-continuous transmission or an erroneous deletion is generated(210). The normalization includes a dividing operation of the energy term by a normalization factor.

Description

Discontinuous transmission detection method

The present invention relates to wireless communication systems.

Communication systems, such as wireless systems, are designed to meet the various needs of subscribers. Service providers are constantly looking for ways to improve the overall performance of their communications systems. As wireless communications become more popular for subscribers to obtain data (eg, email or information from the Internet), communication systems must be capable of higher throughput and tightly controlled to maintain high quality services. The communication is performed according to any desired communication standard, such as the Universal Mobile Telecommunications Standard (UMTS) or the CDMA standard.

As known in the art and shown in FIG. 1, a given service coverage area 100 is divided into multiple cells 102 having a base station 104 associated with one or more cells. The scheduler of the base station (not shown) selects the user for transmission at a given time, and the adaptive modulation and coding allows selection of an appropriate transmission format (modulation and coding) for the current channel conditions seen by the user. In these systems there are two directions of data flow. Communication from the base station 104 to the mobile device 106 is considered flow in the downlink direction while communication at the mobile device starts and transmission to the base station is considered flow in the uplink direction.

In some cases, such as during the transmission of additional channels or digital control channels, the communication standard allows the mobile device to determine its own behavior on a frame-to-frame basis whether or not to send a packet of data to the base station. . In this situation, the mobile device does not inform the base station whether he sent the symbols that make up the frame. Instead, the base station itself must be resolved if the mobile device sent a frame.

To solve this, the base station generally receives the checksum value included in the end of the frame. If the base station receives a checksum that matches the expected checksum, then the base station can safely assume that the mobile device has received the frame and that the data in the frame is of good quality data.

If the received checksum does not match and causes a checksum error, the base station 104 cannot say that the mobile device has substantially sent a frame. One possible cause of the checksum error is a transmitted frame that is distorted during transmission by, for example, bad channel conditions. In other words, the mobile device attempted to transmit the frame but the frame was not correctly received by the base station. This cause is called "erasure".

Another possible cause of the checksum error is when the mobile device chooses not to send a frame at all: this cause is called "discontinuous transmission" or DTX. This may occur, for example, when the mobile device did not send any data to send to the base station. In this case, if the mobile device does not send any data, the base station has no way of knowing it. Since the base station decodes each frame while the mobile device is assumed to send frames continuously, the base station will virtually always detect a checksum error at the same time when no frame is sent.

Thus, when a checksum error occurs, the base station 104 may determine whether a non-existent frame (such as an error is generated by the distorted transmitted frame (delete) or the base station takes appropriate corrective action such as adjusting the transmit power of the mobile device). DTX) is needed to know if the detection was comparatively static.

One currently known DTX detection algorithm is based on symbol error rates. This approach is used for convolutional codes, re-encoding the estimated data bits generated by the convolutional decoder to produce the estimated symbols, and then estimating the estimated data to calculate the number of symbol errors. Comparing the symbols with the actual received symbols. If there are many errors, then the base station assumes that the mobile device did not send any symbols (i.e. DTX case) and makes more received symbols in error. If there are few errors, the base station assumes that the mobile device did not send the symbols and that the base station failed to decode them correctly back to the original data bits. The histograms of the respective symbol error rates of the DTX cases and deletion cases provide a guide to the threshold at which the DTX cases can be distinguished from the deletion cases. Ideally, these histograms are clearly separated into symbol error rates above the threshold corresponding to the DTX case and symbol error rates below the threshold corresponding to the erasure case. However, there are generally some overlaps where the given symbol error rate does not clearly indicate an erasure case or a DTX case. This overlap makes it possible to erroneously identify the DTX case as deletion or vice versa.

Another DTX combine approach measures pilot energy and classifies the checksum error generated by erasure when channel conditions are poor as indicated by the low measured pilot energy. The logic behind this approach is that there is a tendency for deletions to occur during these states. However, pilot energies also create a high probability of misidentifying the DTX case as an erase and can be lowered during the DTX cases.

Another DTX detection approach sums the absolute values of the symbols of the transmitted frame and compares this sum with a threshold. Since there are no symbols transmitted during the DTX case, the sum will theoretically represent an erasure case where it exceeds a given threshold. However, because of the large overlap between the values corresponding to the DTX cases and the erase cases, the sum is sensitive to channel conditions.

The performance of the DTX algorithm is based on the probability that the algorithm misclassifies the deletion as DTX (called P (D | E) or lost detection) and the probability of misclassifying the DTX as deletion (P (E | D) or false detection). Called). Regardless of the particular DTX detection method, the probability of one misclassification type increases the probability of another misclassification type.

What is needed is a way to reliably distinguish deletions from DTXs.

The present invention relates to a DTX detection method based on soft symbols received for a given frame. Soft symbols are typically obtained by taking the complex outputs of a spreader or multiplying them by complex conjugates of their corresponding channel estimates. This multiplication process scales the symbols simultaneously and derotates the symbols for the next maximum ratio combination. The method of the present invention divides the functions of soft symbols or soft symbols into a normalization factor that eliminates the scaling effect of this multiplication process on the soft symbols to obtain a normalized result. As a result, the expected value of the normalized metric does not depend on all levels of the pilot signal. The method of the present invention evaluates the normalized result rather than the denormalized result of the multiplication process to determine whether the checksum error for the frame is caused by the DTX state or the erase state.

In one embodiment, the same normalization factor is applied to all soft symbols in a given frame. This allows the high energy symbols to be weighted more than the low energy symbols and increases the accuracy in the detection erase cases.

By normalizing the function of the soft symbol values to remove the scaling effect of the channel estimates of the soft symbol values, the method of the present invention maximizes the effect of the channel conditions in the DTX case. In addition, because one normalization factor is applied to the soft symbols at the end of an embodiment of the inventive process, the method of the present invention prevents the associated weighting of symbols from the decoding process and provides an efficient channel sense symbol combination for the erasure case. Allow. As a result, the present invention provides a simple way to more accurately identify DTX cases and deletion cases.

1 is a view showing an operating environment of the present invention.

2 is a flow diagram of one embodiment of the present invention.

3 is a table comparing DTX detection performance in accordance with various methods.

4-6 are sample graphs showing DTX detection at different data transmission rates.

* Description of the symbols for the main parts of the drawings *

100: service coverage area 102: multiple cells

104: base station 106: mobile device

As mentioned above, one possible DTX detection algorithm detects a DTX case based on the sum of the sizes of all symbols of a given frame. This type of algorithm relies on evaluating the soft symbol frame decoded by the maximum ratio combination. Soft symbols are derived from two components multiplied together for (1) precursor symbols obtained after the despreading process and (2) each combined finger of the complex conjugate of their corresponding channel estimates. Typically, soft symbols are obtained in the decoding process by taking complex outputs from the spreader and then multiplying them by complex conjugates of their corresponding channel estimates. This multiplication process simultaneously scales and derotates the symbols for the next maximum ratio combination.

Channel estimation is obtained by monitoring the pilot signal from the mobile device. The base station is used to determine how strong the signal is and accumulate pilot signals through a filter over time to obtain the phase of the signal, and obtain derotate and scaling during decoding.

Since channel estimation can vary widely with changes in channel conditions, the soft symbol energy will also vary widely, making it difficult to identify a clearly identifiable energy range depending on the energy range caused by the DTX case. If the channel conditions are good (eg, if the channel exhibits high energy), the symbol energy will be higher than when the channel conditions are bad. As a result, a non-existent (DTX) frame on a high power channel may have the same symbol energy as a transmitted frame on a low power channel, making it easier to confuse actual data and noise in an attempt to distinguish between erase and DTX. do.

For example, assume that channel A has a channel estimate that is twice the size of channel B. It is also assumed that there is no data transmitted over the two channels (i.e., the frame being evaluated is a DTX frame). The soft symbol energy associated with the frame transmitted on channel A will then be twice as high as the soft symbol energy for the frame transmitted on channel B, even if all represent the same DTX case. In the DTX case, the strong channel estimation of channel A will multiply the noise of the channel by the point that the noise will have the same size as the erase frame sent over channel B even though the symbols are transmitted on channel A. This is true even when there are no symbols to be transmitted in the DTX case. This makes it difficult to distinguish between DTX cases and deletions between different channels.

The present invention solves this problem by significantly reducing the effects of channel conditions from all soft symbol energy values for the DTX case. In other words, the symbols from the DTX cases will have the same expected value for their calculated metric when the symbols are transmitted on channels with different channel estimates. In general, the method of the present invention involves normalizing the sum of soft symbols to remove all scaling efficiencies of channel conditions in a given DTX frame. In other words, normalization removes all scaling efficiencies of the maximum ratio combining process previously applied to obtain all soft symbol energy values. As a result of this normalization, the symbol energy metric for a given frame remains sufficiently the same for all DTX cases, regardless of channel estimates, making it easier to detect DTX cases from deletions.

The DTX detection algorithm according to the present invention relies on a calculated metric to distinguish between DTX and deletion cases. Equation 1 below illustrates one way of obtaining the metric. This equation normalizes the magnitude of the soft symbol energy in a given frame to significantly reduce the effects of channel conditions. The metric used to distinguish deletions from DTXs can be calculated as follows:

(Eq. 1)

As is known in the art, the symbols of a frame may arrive at the cell through multiplying transmission paths, or fingers, into symbols from each finger arriving at the base station 104 at slightly different times. Each precursor symbol of a finger is then multiplied by the complex conjugate of its corresponding channel estimate. The products of these precursor symbols and channel estimates are then combined to obtain the soft symbol energy for all the frames (ie, the denominator of equation 1), which is also referred to as the maximum ratio combination (MRC) energy term. Note that the combining process can be any constant ratio combining process and is not limited to MRC. In one embodiment, the base station ignores symbols from a finger with finger channel estimates that are considered too weak for consideration, and assigns a non-zero combination value to those weak fingers. The fingers considered in the soft symbol energy calculation are given a Boolean combination of two.

As described above, the maximum ratio combination processor used to calculate the soft symbol energy multiplies the precursor symbols by channel estimates corresponding to their symbols. Thus, good channel conditions will multiply any noise in the channel and cause this sum to be high and make the mobile device appear as if it has been sent in symbols even in the real case in the DTX state.

The method of the present invention compensates for this through the denominator. Again, note that the unequal value is equal to 1 for a given finger when the finger is used to generate soft symbols and equals zero when the finger is not used. Thus, one channel estimates the portion of the combining process used to calculate the denominator. The denominator of equation 1 is the normalization factor calculated by combining the effects of all channel estimates used to produce soft symbol energy. As can be seen in Figure 1, the normalization factor is equal to the sum of the finger combination channel estimation norms, each finger combination channel estimation norm being the square root of the sum of the squared norms of the finger channel estimates used to generate the soft symbols. Indicates. Since the soft symbol energy is obtained by multiplying the precursor symbols by the complex conjugates of these corresponding channel estimates, the numerator of equation 1 will be proportional to the denominator.

Dividing the soft symbol energy by normalizing the factor removes all scaling effects of the channel estimates on the metric and restores a value proportional to the actual symbol energy, which is inaccurate by all lengths of the received pilot. This reduces the variable of the metric in the DTX case and makes it easier to distinguish between deletions and DTXs. In particular, Equation 1 allows estimation of the actual received symbol energies and produces a metric that is not affected by channel conditions for DTX cases. For example, if a checksum error occurs and the metric is low or lacks symbol energy, this indicates that there are few or transmitted symbols indicating a DTX state. Conversely, when a checksum error occurs and the combined symbol energies are above the selected low level, this indicates that the symbols have been substantially transmitted by the mobile device. As with the particular case, the energy difference between the DTX case and the erase case is generally small and only detectable after summing all the large numbers of symbols. Thus, the combined symbol energies representing the erasure case will be at a relatively low level.

To simplify the calculation of the metric shown in equation 1, all terms in both the numerator and denominator of equation 1 can be squared to obtain the following metric:

(Eq. 2)

Although Equations 1 and 2 are not mathematically identical, they yield similar performance in the generation of a metric that accurately distinguishes between deletes and DTXs by generating a metric to make the DTX substantially constant regardless of channel conditions. Indicates. Equation 2 does not require any square root operation and makes calculations easier than Equation 1.

Equations 1 and 2 are both well defined and produce predictable metrics for the DTX case. More particularly, significantly reducing the effects of the channel states of the metric based only on symbol energy and detecting the DTX cases reduce the change in the metric that the DTX case will have. That is, since there are no symbols transmitted in the DTX case, any symbol energies above the low level will indicate that the checksum error is caused by erasure, not DTX, regardless of channel conditions.

2 is a flow diagram illustrating one embodiment of the method of the present invention. In this embodiment, the base station receives transmissions from the mobile device (block 200) and uncovers and spreads these transmissions separately for each finger to generate precursor symbols for each selected finger (block 202). . As noted above, the base station will ignore the fingers that are considered too weak for consideration (ie, fingers with unequal value 0).

Base station 104 derotates and scales precursor symbols for each finger individually (block 204) until all desired fingers have been derotated and scaled (block 205). If the base station has generated soft symbols for all selected fingers, the base station maximum ratio combines the soft symbols for the individual fingers to generate soft symbols (MRC). The soft symbols are then combined to obtain an energy term (block 207) and then normalized to obtain a metric (block 208). This metric discards all effects of channel conditions on soft symbols and is compared to the DTX detection threshold (block 210).

The embodiment shown in FIG. 2 normalizes the soft symbols at the end of the processor after the soft symbols are generated and summed. In another embodiment, the base station will execute the normalization process during the decoding process on its own rather than in a separate processor. To do this, the base station performs a derotate and scaling step (block 204) using the normalized channel estimate rather than the channel estimate itself. In such an embodiment, normalized channel estimation may remove the relative weight among the soft symbols because the soft symbols are normalized during the decoding process rather than at the end. However, such a processor also estimates an individual normalization step that may be desirable in certain applications.

3 is a table showing the performance characteristics of various DTX detection methods, including the method of the present invention. The table shows the effect of the data rates as well as the encoder types of efficiency. The DTX detector efficiency is calculated by the crossover probability, which is the probability of an error that the DTX detection threshold is set so that lost detection probabilities and false detections are equal; Cross probability is high and DTX detector performance is wrong. The crossing probability may change based on channel conditions, such as the speed of mobile device movement relative to the base station.

Performance is also measured by P (D | E) | P (E | D) = 0.1%, or by a threshold of 0.1%, which is the probability of an algorithm that incorrectly indicates the deletion case in the DTX case. This threshold is set to affect the probability of an error that incorrectly indicates the DTX case. For example, in pilot energy and symbol energy detection approaches, the probability of false erase indication is nearly 100% when p (E | D) is equal to 1%; In other words, this approach indicates that all checksum errors are substantially caused by DTX. While this is certain that some DTX cases are lost, it will be lost in the process that almost all cases of deletions intersect.

The method of the present invention has cross probability and false deletion detection probabilities that are very low by contrast and lower as the data rate increases. Higher data rates require increased power to transmit the symbols, and a comparison between lowering the high symbol energies in the erased case and the non-existent symbol energies in the DTX case makes it more apparent and easier to detect.

The desired threshold for separating the DTX case from the erase case is generally a constant result, which is another beneficial result regardless of the data transfer rate. 4 through 6 are error curves showing examples of thresholds for DTX and erasure classification error probabilities and various data rates. As can be seen in the figures, the threshold for separating DTXs from deletions can be selected to be the same for a wide range of data rates. Despite the erase histograms (indicative of improved DTX detection performance) that shift the higher data rates and other portions obtained in DTX, a threshold near 2.6 will produce reasonable results in all cases shown. This simplifies DTX detection because the detection method does not require a lookup table that includes different threshold values for different data rates. However, transmission rates based on lookup tables will also improve performance for certain applications.

As a result, the present invention provides a simple and accurate way to distinguish deletions from DTXs by maintaining the value of the symbol energy metric as constant as possible for all DTX cases, regardless of channel conditions. This information can provide accurate control and monitoring of communication system performance. For example, the system can increase the transmit power of the mobile device when deletion is detected, leaving the transmit power alone when the DTX is detected; The present invention assures that appropriate action is taken when the base station detects a checksum error. In addition, accurately distinguishing deletions from DTXs allows accurate calculation of the frame error rate, which is an important measure of communication system performance.

Although specific inventions have been described with reference to the illustrated embodiments, the specification is not meant to be construed in a limiting sense. While the invention has described various modifications of the illustrated embodiments as well as additional embodiments of the invention, it will be apparent to those skilled in the art with reference to the technology without departing from the spirit of the invention as set forth in the appended claims below. It is understood that it will be apparent. Thus, the method, system and parts thereof and the described method and system may be performed at different locations such as network elements, radio units, base stations, base station controllers, mobile switching centers and / or radar systems. In addition, as will be appreciated by those skilled in the art with the benefit of the present disclosure, the processing circuitry required to implement and use the described system may include specific integrated circuits, software driven processing circuitry, firmware, programmable logic devices, hardware, discrete It may be performed in the application of the components or arrangement of the above components. Those skilled in the art will readily appreciate that these and other modifications, arrangements, and methods may be made to the present invention without departing from the spirit and scope of the present invention without departing precisely from the typical applications described and described herein. Accordingly, it is contemplated that the appended claims will cover any such modifications or embodiments so as to fall within the true scope of the invention.

The present invention provides a simple and accurate method of distinguishing deletions from DTXs by maintaining the value of the symbol energy metric as constant as possible for all DTX cases, regardless of channel conditions.

Claims (10)

A method of determining whether a transmission frame associated with a checksum error is caused by a discontinuous transmission: Combining soft symbols corresponding to the transmission frame to obtain an energy term; Normalizing the energy term to obtain a metric, wherein the normalization removes the effect of channel conditions in the energy term; Comparing the metric to a threshold to determine if a discontinuous transmission or deletion has occurred. The method of claim 1, wherein normalizing comprises dividing the energy term by a normalization factor. 3. The method of claim 2, wherein the normalization factor is equal to the sum of finger-combined channel estimate norms. 4. The method of claim 3, wherein the soft symbols are received through a plurality of fingers, each finger having an associated finger channel estimate, and each finger-combined channel estimation norm is a squared finger channel estimate norm used to generate the soft symbols. The square root of the sum of the methods. The method of claim 1, wherein the energy term is calculated by summing squares of the soft symbols. 6. The method of claim 5, wherein normalizing comprises dividing the energy term by a normalization factor. 7. The method of claim 6, wherein the normalization factor is equal to the sum of finger-combined channel estimation norms. 8. The method of claim 7, wherein the soft symbols are received through a plurality of fingers, each finger having an associated finger channel estimate, each finger-combined channel estimation norm being a squared finger channel estimation norms used to generate the soft symbols. The square root of the sum of the methods. A method of determining whether a transmission frame associated with a checksum error is caused by a discontinuous transmission: Combining soft symbols corresponding to the transmission frame with a constant ratio combining by summating soft symbol values to obtain a metric, wherein the combining step normalizes channel estimation to remove the effect of the channel conditions of the metric The combination step is performed using; Comparing the metric with a threshold to determine if a discrete transmission state or deletion has occurred. 10. The method of claim 9, wherein the soft symbol values are squares of the soft symbols.