KR101293514B1 - Discontinuous transmission detection method - Google Patents

Abstract

The DTX detection method evaluates soft symbols from the decoding process to evaluate whether the checksum error is caused by the erased state or the DTX state. The method of the present invention is a function of software symbols or software symbols by normalizing a factor that significantly reduces the effect of the overall magnitude of the channel estimates used to calculate soft symbols and recovering a value proportional to the received symbol energy. Divide The method then evaluates this value over the denormalized value to determine if the checksum for the frame is caused by the DTX state or the erase state. Normalization of soft symbols to obtain a metric proportional to the actual symbol energy significantly reduces the effect of the overall channel level on DTX detection and makes it easier to identify between DTX cases and erase cases.

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 with 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 auxiliary channels or digital control channels, the communication standard allows the mobile device to determine on a frame-to-frame basis in accordance with its own determination of whether to send a packet of data to the base station. do. In this situation, the mobile device does not inform the base station whether it sent the symbols that make up the frame. Instead, the base station itself must find out if the mobile device sent a frame.

To this end, 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.

If the received checksum does not match and causes a checksum error, the base station 104 cannot tell whether the mobile device actually sent a frame. One possible cause of the checksum error is a transmission frame that is distorted during transmission due to, 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 is chosen 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 have any data to send to the base station. Even in this case where 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 assuming that the mobile device continues to send frames, the base station will virtually always detect a checksum error at a time when no frame is transmitted.

Thus, when a checksum error occurs, the base station 104 determines whether the error is caused by a distorted transmission frame (delete) or a non-existent frame (DTX) in order to take appropriate corrective action, such as adjusting the transmit power of the mobile device. ) Is needed to know if it was detected incorrectly.

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 symbols to calculate the number of symbol errors. Comparing 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 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 the erase cases provide a guide to the threshold at which the DTX cases can be distinguished from the erase 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 erase 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 misidentify the DTX case as erased and vice versa.

Another DTX detection approach measures pilot energy and classifies checksum errors caused by cancellation when the channel conditions are poor, as represented by low measured pilot energy. The logic behind this approach is that there is a tendency for erases to occur during these states. However, pilot energies also create a high likelihood of misidentifying the DTX case as erase and can be lowered during the DTX cases.

Another DTX detection approach sums the absolute values of the symbols in the transmission frame and compares this sum with a threshold value. Since there are no symbols transmitted during the DTX case, the sum will theoretically indicate the erase case if it exceeds a given threshold. However, the D sum is sensitive to channel conditions and causes a large overlap between values corresponding to DTX cases and erase cases.

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

What is needed is a way to reliably distinguish erases 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 the despreader and multiplying them by the complex conjugates of their corresponding channel estimates. This multiplication process scales the symbols simultaneously and de-rotates the symbols for the next maximum ratio combination. The method of the present invention divides the function of soft symbols or soft symbols by 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 higher energy symbols to be weighted more than lower energy symbols and increases the accuracy in detecting erase cases.

By normalizing the ability 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 greatly reduces the effect of channel conditions in the DTX case. Furthermore, because one normalization factor is applied to soft symbols at the end of the process of the present invention in one embodiment, the method of the present invention preserves the relative weight among the symbols from the decoding process, thus making it efficient for the erase case. Allow channel sensitive symbol combinations. As a result, the present invention provides a simple method of more accurately identifying DTX cases and erase cases.

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

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 rates.

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. The soft symbols are derived from two components multiplied together for (1) precursor symbols obtained after the despreading process and (2) each combination 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 accumulates a pilot signal through the filter over time to determine how strong the signal is and to obtain the phase of the signal, which is used to perform derotate and scaling during decoding.

Since channel estimation can vary widely with channel state changes, the soft symbol energy will also vary widely, making it difficult to identify a clearly identifiable energy range as 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 (DTX) frame that does not exist on a high power channel may have the same symbol energy as a transmitted frame on a low power channel, confusing the actual data and noise in an attempt to distinguish between erase and DTX. Make it easy.

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 on either channel (i.e., the frame being evaluated is a DTX frame). Then, the soft symbol energy associated with the frame transmitted on channel A will 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, a strong channel estimate of channel A may multiply the noise in the channel by a point that will have the same magnitude as the erased frame transmitted over channel B even if there are no symbols transmitted over channel A. This is true even if there are no symbols to be transmitted in the DTX case. This makes it difficult to distinguish between cancellation and DTX cases among different channels.

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

The DTX detection algorithm according to the present invention relies on the calculated metric to distinguish between the DTX case and the erased case. 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 greatly reduce the effects of channel conditions. The metric used to distinguish the cancellations from the DTXs can be calculated as follows:

(Equation 1)

As is known in the art, symbols in a frame may arrive at a cell through multiple transmission paths, or fingers, with symbols from each finger arriving at base station 104 a slightly different number of 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 fingers with finger channel estimates that are considered too weak for consideration and assigns a Boolean combination of zero to those weak fingers. Fingers considered in the soft symbol energy calculation are given a Boolean combination of one.

As described above, the maximum ratio combining process used to calculate the soft symbol energy multiplies the precursor symbols with the channel estimates corresponding to their symbols. Thus, good channel conditions will multiply any noise in the channel and will cause this sum to be high and, in fact, even when in the DTX state, make the mobile device appear to have sent symbols.

The method of the present invention compensates for this through denominators. Again, note that the Boolean combination value for a given finger is equal to 1 when the finger is used to generate soft symbols and equals zero if the finger is not used. Thus, it is assumed that only the channel is part of the combining process used to calculate the denominator. The denominator of equation 1 is a normalization factor calculated by combining the effects of all channel estimates used to produce soft symbol energy. As can be seen in Equation 1, the normalization factor is equal to the sum of the finger combination channel estimation norms, and each finger combination channel estimation norm is 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 calculated by multiplying the complex symbols with 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 the normalization factor removes all scaling effects of the channel estimates on the metric and restores a value proportional to the actual symbol energy, without error by the overall strength of the received pilot. This reduces the change in 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 reflects a low metric or no symbol energy, this reflects the fact that fewer symbols are sent or no symbols are transmitted, 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 a practical matter, 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 erase case will be at a relatively low level.

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

(Equation 2)

Although Equations 1 and 2 are not mathematically identical, they exhibit similar performance in generating a metric that accurately distinguishes between DTXs and cancellations by creating a metric for a substantially constant DTX regardless of channel conditions. 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 to be transmitted in the DTX case, any symbol energies above the low level will indicate that the checksum error is caused by erasure rather than DTX regardless of channel conditions.

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

Base station 104 then derotates and scales precursor symbols for each finger individually (block 204) until all of the desired fingers are derotated and scaled (block 205). If the base station has generated soft symbols for all of the selected fingers, then 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 removes the overall effect of channel conditions on soft symbols and is compared with 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 itself rather than in a separate process. 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 weighting of the soft symbols because the soft symbols are normalized during the decoding process rather than at the end. However, such a processor also eliminates individual normalization steps 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 also shows the effect on the performance of the data rates as well as the encoder types. DTX detector performance is assessed by crossover probability, which is the probability of an error in which the DTX detection threshold is set so that missed detections equal false detections; The higher the crossing probability, the worse the DTX detector performance. The crossing probability may vary 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 misrepresents the erase case in the DTX case. The point at which this threshold is set affects 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 erasure indication is nearly 100% when p (E | D) is equal to 1%; In other words, this approach indicates that all checksum errors are caused by the DTX substantially. While this is certain that some DTX cases will be lost, the tradeoff is that almost all erase cases will be lost in the process.

The method of the present invention has very low crossover probabilities and false erase detection probabilities which, in contrast, are very low and much 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 produces more clearly and makes detection easier.

Another preferred result of the present invention is that the desired threshold for separating the DTX case from the erase case is generally the same regardless of the data transfer rate. 4 through 6 are error curves showing examples of DTX and erase classification error probabilities and thresholds for various data rates. As can be seen in the figures, the threshold for separating DTXs from erases can be selected to be the same for a wide range of data rates. Despite the erased histograms (indicative of improved DTX detection performance) moving 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 even further because the detection method does not necessarily require a lookup table that includes different threshold values for different data rates. However, transmission rates based on lookup tables may also improve performance for certain applications.

As a result, the present invention provides a simple and accurate method of distinguishing cancellations 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 an erase is detected, leaving the transmit power 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 cancellations 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 present 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 changes, arrangements, and methods may be created in the present invention without departing from the spirit and scope of the present invention without departing precisely from the representative 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.

Description of the Related Art [0002]
100: service coverage area 102: multiple cells
104: base station 106: mobile device

Claims (12)

A method for determining whether a transmission frame associated with a checksum error is caused by a discontinuous transmission,
Combining at the base station soft symbols corresponding to the transmission frame to obtain an energy term;
In a base station, normalizing the energy term by dividing the energy term by a normalization factor to obtain a metric, wherein the normalization factor is a sum of finger-combined channel estimate norms. Wherein the normalization removes the effect of channel conditions in the energy term; And
At the base station, comparing the metric with a threshold to determine whether discontinuous transmission or erasure has occurred. delete delete The method of claim 1,
The soft symbols are received via a plurality of fingers, each finger having an associated finger channel estimate, each finger-combined channel estimation norm comprising a square root of the sum of squares of the finger channel estimation norms used to generate the soft symbols. How to decide. delete delete A method for determining whether a transmission frame associated with a checksum error is caused by a discontinuous transmission,
At the base station, combining the soft symbols corresponding to the transmission frame, including summing squares of soft symbols to obtain an energy term;
In a base station, normalizing the energy term by dividing the energy term by a normalization factor to obtain a metric, wherein the normalization factor is equal to the sum of squared values of finger-combined channel estimation norms, and the normalization is in the energy term. Normalizing, eliminating the effect of channel states of; And
At the base station, comparing the metric with a threshold to determine whether discontinuous transmission or cancellation has occurred. The method of claim 7, wherein
The soft symbols are received via a plurality of fingers, each finger having an associated finger channel estimate, each finger-combined channel estimation norm comprising a square root of the sum of squares of the finger channel estimation norms used to generate the soft symbols. How to decide. The method of claim 1,
Combining the soft symbols uses a constant ratio combination. The method of claim 1,
And the soft symbol values are squares of the soft symbols. In the base station,
At least one processor, wherein the processor determines whether a transmission frame associated with a checksum error is caused by discontinuous transmission;
Combining soft symbols corresponding to the transmission frame to obtain an energy term;
Normalizing the energy term by dividing the energy term by a normalization factor to obtain a metric, wherein the normalization factor is equal to the sum of the finger-combined channel estimation norms, and the normalization determines the effect of the channel states in the energy term. Removing, the normalization step; And
And comparing the metric with a threshold to determine whether discontinuous transmission or cancellation has occurred. In the base station,
At least one processor, wherein the processor determines whether a transmission frame associated with a checksum error is caused by discontinuous transmission;
Combining the soft symbols corresponding to the transmission frame including sum of squares of soft symbols to obtain an energy term;
Normalizing the energy term by dividing the energy term by a normalization factor to obtain a metric, wherein the normalization factor is equal to the sum of squared values of finger-combined channel estimation norms, and the normalization is a channel state in the energy term. The normalization step of eliminating the effect of the; And
And comparing the metric with a threshold to determine whether discontinuous transmission or cancellation has occurred.

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