The presented invention claims new method to transmit the quantized information value in wireless or wired communication, with reduced effective quantization error. The invention has a specific application but not limited to the mobile positioning in 3GPP Long Term Evolution (LTE) system that is one of the candidates for the 4-th generation wireless system.
In a communication system, an information value is often sent from one communication node (transmitter) to another communication node (receiver), via either a wired or a wireless channel. Due to the limited word length in a data packet where the information value is put in for the transmission, the information value is often quantized to a limited number of digits, or equivalently translated to a value range index that represents the value range which the information value falls into. For example, a general mapping table of N rows for such translation upon information value x is shown in Table 1. The information value to be quantized is assumed to be between a0 (inclusively) and aN (non-inclusively). The whole quantization range is denoted as [a0, aN). This quantization range is segmented into N contiguous value ranges by (N−1) values ai for 1, where ai for all 0≤i≤N are known to both transmitter and receiver, and meanwhile satisfies a0<a1<a2< . . . <aN-1<aN. Then if the value x falls into the value range [am, am+1) for some m satisfying 0≤m≤N−1, the corresponding value range index m is used to represent the quantized value x and is sent from the transmitter to the receiver.
On the receiver side that receives the value range index m, the receiver knows the value being quantized is within value range of [am, am+1), it can pick any value
In order to reduce the quantization error |
This is to say, the quantization resolution or the maximum quantization error can be reduced to be the original divided by k if the scaling factor k is used to scale the value x before the quantization on the transmitter side, and is used to de-scale (i.e., the operation performed at the receiver that is opposite to the scaling operation performed at the transmitter) the quantized value that is received by the receiver on the receiver side. However, the drawback of this solution is that the effective quantization range is also reduced to be the original divided by k, i.e., if the quantization function Q(⋅) allows the input to be within range [a0, aN), the quantization with scaling factor k only allows the value x to be within range of
In order to reduce the quantization error while avoiding the quantization range being reduced, a new method is proposed in this application. In this new method, the quantization with scaling is not done over the whole range of [a0, aN). Instead, it is performed upon a small value range of [ai, ai+1) for i satisfying 0≤i≤N−1. In addition, the scaling factor that is applied in one value range can be different from the scaling factor that is applied in a different value range. The quantization function Q(⋅) that is applied in each value range can be based on a new quantization mapping table, or a floating-to-integer converter.
The present invention has an application in mobile positioning in wireless communication, in which the location of a mobile station can be derived from the timing measurements that are measured by the mobile station and reported by the mobile station to the network server that calculates the location of the mobile station. The quantization is applied to those timing measurements when they are transmitted from the mobile station to the network server.
Even though the claimed method is designed for timing measurement reports in mobile positioning, the same principle can be used in any wireless or wired messaging containing quantization quantities for other purposes.
These and other implementations and examples of this design in software and hardware are described in greater details in the attached drawings, the detailed description and the claims.
According to the claimed method for quantization of an information value x, when the value x falls into a first value range [am, am+1) of a first quantization mapping table with a first value range index m that satisfies 0≤m≤N−1, the quantization function Q(⋅) with scaling is applied upon value of x−am, i.e., the recovered quantization value
where the scaling factor km is associated with the value range of [am, am+1) in the first quantization mapping table, which includes the information as shown in Table 2, and can be different from the scaling factors applied in other value ranges in the first quantization mapping table. Because the scaling is not performed upon the entire quantization range [a0, aN) of the first quantization mapping table, the entire quantization range [a0, aN) is not reduced. Meanwhile, the quantization resolution or maximum quantization error in the first value range [am, am+1) is reduced to be the original divided by km.
In one embodiment of this application, the quantization function Q(km·(x−am)) can be implemented based on a second mapping table as shown in Table 3, where the quantization range of the second mapping table is segmented into M contiguous value ranges [bj, bj+1) for all j satisfying 0≤j≤M−1. This second mapping table translates the value of km·(x−am) into a second value range index.
Then in order to transmit an information value x,
On the receiver side, upon receiving both the first value range index m and the second value range index m′, the receiver identifies the first value range [am, am+1) in the first mapping table and the associated scaling factor km according to the received first value range index m, and identifies the second value range [bm′, bm′+1) in the second mapping table according to the received second value range index m′. Next, the receiver recovers the quantized value
where y is any value satisfying bm′≤y<bm′+1.
In another embodiment of this application, the quantization function Q(km·(x−am)) can also be implemented based on a floating-to-integer converter that converts a floating number to an integer number by using a floor function └z┘, which equals to the largest integer that is smaller than or equal to z. To be more specific, in order to the transmit an information value x,
Application to RSTD Quantization in OTDOA Positioning
In the 3GPP Long Term Evolution (LTE) standardization, the observed time difference of arrival (OTDOA) solution is specified to support mobile positioning. As shown in
It has been well known that the RSTD quantization error has an impact on the positioning accuracy. In 3GPP LTE specification, the RSTD quantization is done according to a quantization mapping table, which is shown in Table 4. The unit Ts in Table 4 equals to one time sample duration in LTE. The quantization resolution in Table 4 is 1 Ts if RSTD value falls inside [−4096 Ts, 4096 Ts], or 5 Ts otherwise. It can be seen that the Table 4 is a specific instance of Table 1, by assigning a0 and aN in Table 1 to be negative infinity and positive infinity, respectively. Although the inequality signs are mismatched between two tables (≤ vs. <, and ≥ vs. >), this difference between the two tables does not affect the applicability of the claimed method to RSTD quantization reporting.
According to the claimed method, a quantization scaling factor is associated with each value range in Table 4. Note that the scaling factors for the value ranges within [−4096 Ts, 4096 Ts] can be the same; the scaling factors for the value ranges outside of [−4096 Ts, 4096 Ts] can also be the same but can be different from the scaling factors for the value ranges within [−4096 Ts, 4096 Ts]. For example, the scaling factor for the value ranges within [−4096 Ts, 4096 Ts] can be one real number k(1), while the scaling factor for the value ranges outside [−4096 Ts, 4096 Ts] can be another real number k(2), e.g., k(2)=5·k(1) with k(1) chosen from {2,4,8,10,12} and etc.
According to the present application, a second mapping table is generated below as a specific instance of Table 3.
In Table 5, Δ=bM/M and bM≥max(k(1),5k(2)). The mobile station can perform the quantization with scaling based on this second mapping table in the steps as described earlier in this application.
According to the present application, the mobile station can perform the quantization with scaling based on floating-to-integer conversion in steps as described earlier in this application.
In the 3GPP Long Term Evolution (LTE) standardization, the enhanced cell-ID (ECID) based solution is specified to support mobile positioning. In ECID, the position of a mobile station is roughly known by the network according to the location of the base station that serves the mobile station. Beyond that, the location of the mobile station can be further refined based on the estimated distance between the mobile station and the serving base station, which can be derived according to the round-trip propagation time between the mobile station and the serving base station. In order to obtain the round-trip propagation time, the serving base station firstly transmits a downlink signal that is received by the mobile station. Upon receiving the downlink signal, the mobile station transmits an uplink signal and reports to the base station the time difference between the time instance of receiving the downlink signal and the time instance of transmitting the uplink signal, i.e., Rx-Tx time difference. Once receiving the uplink signal, the base station measures the time difference between the time instance of transmitting the downlink signal and time instance of receiving the uplink signal, i.e., Tx-Rx time difference. The round-trip propagation time is calculated by the base station or the network server as the difference between Tx-Rx time difference measured by the serving base station and Rx-Tx time difference reported by the mobile station.
In the report of Rx-Tx time difference, the mobile station quantizes the Rx-Tx time difference according to the mapping table in Table 6. The unit Ts in Table 6 equals to one time sample duration in LTE. The quantization resolution in Table 6 is 2 Ts if Rx-Tx time difference falls inside [0 Ts, 4096 Ts], or 8 Ts otherwise. It can be seen that the Table 6 is a specific instance of Table 1, by assigning a0 and aN in Table 1 to be 0 and positive infinity, respectively. Therefore, the claimed methods of quantization with scaling factor based on a second mapping table or based on a floating-to-integer converter can be applied in the steps as described earlier in this application.
In implementation, the above described methods and their variations may be implemented as computer software instructions or firmware instructions. Such instructions may be stored in an article with one or more machine-readable storage devices connected to one or more computers or integrated circuits or digital processors such as digital signal processors and microprocessors. In a communication system of 3GPP LTE, the claimed method and related operation flow and process may be implemented in form of software instructions or firmware instructions for execution by a processor in the transmitter and receiver or the transmission and reception controller. In operation, the instructions are executed by one or more processors to cause the transmitter and receiver or the transmission and reception controller to perform the described functions and operations.
Filing Document | Filing Date | Country | Kind |
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PCT/US2016/056295 | 10/10/2016 | WO | 00 |
Number | Date | Country | |
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62239697 | Oct 2015 | US |