The present invention relates to mobile wireless communication; more particularly, the present invention relates to estimating a direct path (DP) distance within a multi-path environment between two mobile devices.
Within a communication system, a mobile communications device may be located using a Global Positioning System (GPS) receiver that takes positions and times from multiple satellites to accurately measure and determine distances. The mobile communications device compares its time with the time broadcast by at least three satellites whose positions are known and calculates its own position on the earth. However, the GPS system depends on expensive atomic clocks in the GPS transmitters to generate the precision measurements. Therefore, it is often impracticable to implement a satellite based GPS system to provide accurate positioning measurements in various environments.
The invention is illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements, and in which:
A mechanism for time of arrival (TOA) estimation is described. In the following detailed description of the present invention numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be apparent to one skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the present invention.
Reference in the specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
Embodiments may include packet exchanges between users of communication devices and access points in a Wireless Local Area Network (WLAN). For example, one or more mobile stations or an access point may operate in compliance with a wireless network standard such as ANSI/IEEE Std. 802.11, 1999 Edition, although this is not a limitation of the present invention. As used herein, the term “802.11” refers to any past, present, or future IEEE 802.11 standard, or extension thereto, including, but not limited to, the 1999 edition. Embodiments may be adapted to communicate in accordance with one or more protocols contemplated by various IEEE 802.16 standards for fixed or mobile wireless metropolitan area networks (WMANs). (WiMax Worldwide Interoperability for Microwave Access is not really part of the standard name, it's a certification for products that are compliant with 802.16 standards.) Note that the type of communication network and the type of multiple accesses employed by devices that emit RF signal energy are provided as examples only, and the various embodiments of the present invention are not limited to the embodiment shown in the figure.
Wireless communications device 10 includes a receiver 12 to receive a modulated signal from one or more antennas. The received modulated signal may be frequency down-converted, filtered, then converted to a baseband, digital signal. The frequency conversion may include Intermediate Frequency (IF) signals, but it should be noted that in an alternative embodiment the modulated RF signals may be directly down-converted without the use of IF mixers. The scope of the claims is intended to cover either embodiment of the receiver. The down converted signals may be converted to digital values by Analog-to-Digital Converters (ADCs).
Wireless communications device 10 further includes a transmitter 14 having a Digital-to-Analog Converter (DAC) that converts a digital value generated by the processor to an analog signal. The analog signal may be modulated, up-converted to RF frequencies and amplified using a power amplifier (with or without feedback control) to control the output power of the analog signal being transmitted from the antenna(s).
Although shown in a wireless communications device 10, embodiments of the present invention may be used in a variety of applications. It should be pointed out that the timing acquisition embodiments are not limited to wireless communication devices and include wire-line communication devices. The present invention may be incorporated into microcontrollers, general-purpose microprocessors, Digital Signal Processors (DSPs), Reduced Instruction Set Computing (RISC), Complex Instruction-Set Computing (CISC), among other electronic components. In particular, the present invention may be used in smart phones, communicators and Personal Digital Assistants (PDAs), medical or biotech equipment, automotive safety and protective equipment, and automotive products. However, it should be understood that the scope of the present invention is not limited to these examples.
Wireless communication systems typically operate over a channel that has more than one path from transmitter to the receiver. Such a channel is frequently referred to as a multi-path channel. These signals travel through various paths that may be caused by reflections from buildings, objects, or refraction. At the receiver end, these various signals are received with different attenuations and time delays associated with its travel path.
In a multi-path system, the receiver receives signals from different paths with different attenuations and delays and is expressed by:
where s(t) denotes a reference transmit ranging signal and y(t) the received signal at the receiver. M denotes the number of paths, Ai and τi denote attenuation and delay associated with the i-th path, respectively. Here, w(t) is the composite noise due to the impairment of the transmit/receiver, and channel. The DP signal is the first signal such that τi is the smallest since the DP signal takes the most direct path. However, the multi-path estimation algorithm above may classify noise as possible signal as well. For example, if τ1 is the shortest delay and A1 is very small, the algorithm may have overestimated the true number of paths and essentially attempts to fit the signal to the residual noise.
According to one embodiment, TOA techniques are implemented to determine the DP signal (τDP) in order to compute the direct path distance between the transmitter and receiver. The distance and TOA relationship is given by τDP=D/c, where D and c are the distance and the velocity of propagation, respectively. In such an embodiment, the DP distance within a multi-path environment is estimated when only one device (e.g., the receiver) has received data packets and the other side (e.g., the transmitter) has received time stamps only.
A process 320 is included to provide TOA/Multi-Path Reconstruction. For a two way ranging system, signals that travel from a first transceiver to a second transceiver have some similar properties as the signal travel from the second transceiver to the first transceiver (e.g., power attenuation, air travel time, etc). Thus, process 320 applies the symmetric property between the forward and reverse multi-path link to time-stamp information in order to re-construct the multi-path profile parameters for the other transceiver.
Range computation is provided at process 330 by utilizing the multi-path profiling information from processes 310 and 320 to compute the distance between the transceivers. Wireless location is provided at process 340 so that the location of the wireless radio unit can be determined with ranging to a number of different radios. In some embodiments, the process described herein or portions thereof may be performed by a mobile station, a processor, or an electronic system. The processes are not limited by the particular type of apparatus, software element, or system performing the method. The various actions may be performed in the order presented, or may be performed in a different order and in some embodiments, some actions listed in
TOA/Multi-Path Estimation
Frequency Offset Compensation
In process 410 a frequency offset compensation value is calculated to correct the frequency offset between a received signal and a reference signal, e.g., a signal from a remote modem. Signals are sensitive to carrier frequency offset between the transmitter and the receiver local oscillators, which may cause self interference, for example, between the subchannels, e.g., modulated subcarriers in an OFDM modulation format. Carrier frequency offset between transmitter and receiver local oscillators may be estimated and compensated at the receiver.
Let yn be the discrete sampled received data and n be the reference data at discrete time n. The relationship between the received signal and the reference signal may be represented as:
where A1 is the signal amplitude,1 τ1 is the delay taken to the nearest sample, ω is the frequency offset between the received signal and the reference signal, and en is the noise sampled at time n.
To estimate the frequency offset, the following least-square cost function is minimized:
(Â, {circumflex over (ω)})=min(A, ω)|∥yn−ASn ×exp(jωn) ∥2 ,
where ({circumflex over (A,)}, {circumflex over (ω) represent “estimated values” for amplitude and frequency offset. The cross-product zn=yn sn* can be defined. Note that the value for zn does not have to be recomputed for each hypothesized frequency value that is used. )}
The estimated amplitude is given by:
and the estimated frequency offset may be obtained by a searching algorithm using:
{circumflex over (107 )}=arg min/ωΣ|ti n|2 ti −|Â|2 Σ|n|2 .
The estimated frequency offset is then applied to the received signal for frequency offset correction.
Parameter Estimation by Multi-path Decomposition
Once the frequency offset is compensated, the multi-path signals are estimated (both DP and indirect path) and specific properties in the signals are observed to select the DP signal. Further, the process estimates the dominant multi-path component sequentially to achieve a fast solution. The process of estimating the multi-path profile for TOA estimation is not limited to the proposed multi-path decomposition method. It will be understood other approaches can also be used with the TOA estimation mechanism, such as optimal multi-path join-estimation.
The decomposition process 420 sequentially estimates multi-paths based on the energy ratio of the signal component and the noise component (ESNR). With the ESNR generated for each of the multi-path signals, the decomposition process arranges the signal components from the strongest ESNR to the weakest ESNR. Since a low ESNR may result in poor estimation performance, the decomposition executed in process 420 accounts for low ESNR issues in accordance with the present invention. Accordingly, the attenuated receive signals obstructed by objects and/or the non-LOS signal energy/power that is substantially greater than that of the LOS signal is accounted for in process 420.
In the decomposition algorithm, {circumflex over (y )}i(t) represents the signal used for estimating the i-th path component. During the decomposition process for the i-th path, the strongest signal ŷi (t) is estimated and removed from the residual signals. The estimation problem is formulated by an iterative process with first letting r(t)=y(t), then
The final estimate becomes:
Again, note that Z(ω) is only computed once per minimization. Note that the iteration is repeated with: r(t)=r(t)−Ai*s(t−τi).
The decomposition associated with process 420 may be generalized to an M-path example without a specific signal strength relationship between paths. The determination of the number of paths M, and the selection of the DP signal is illustrated in preparation for the final estimation of TOA for the DP signal. Let A1>A2>A3 . . . , and by way of example, assume that the DP signal is the third strongest signal, i.e., YLOS(t)=A3S(t −τ3).
In this example the DP signal has a smaller ESNR than either of the two other indirect paths. The mechanism for selecting the number of paths M and the DP signal is described later, but assume that these parameters are known. The decomposition algorithm first estimates the strongest signal component y1(t)=A1S(t−τ1) and stores the information. The value Y1(t) is removed from y(t) and the remaining signal becomes residual error r(t)=y(t)−ŷ1(t). After separating the 1(t) from the received signal y(t), the second strongest signal component 2(t) is then estimated from r(t). The same procedure is repeated for the i-th path until i=M. The time-of-arrival information ωLOS is obtained from YLOS(t)=ALOS S(t −ωLOS ), where LOS =3 in this example.
As previously stated, the decomposition associated with process 420 sequentially estimates multi-paths based on ESNR. As shown in
Process 420 continues by sequentially estimating the remaining multi-paths based on ESNR. In this example, the second component 504 is the remaining multi-path signal having the strongest ESNR. This second path signal (second component 504) is then removed and the residual noise of the remaining components further drops by a few dB. As shown in the figure, the third component 506 is the component selected from the remaining components as having the strongest ESNR. After removing the third component 506, the residual noise of the remaining components drops an additional few dB.
Now returning to
Multi-Path Reconstruction
Referring back to
When the transmitter and receiver are reversed (e.g., the transmitter becomes the receiver and the receiver becomes the transmitter as shown in
Based on this description it can be concluded that the multi-path profile (the paths/ray-traces, etc.) from point-A to point-B is the same as from point-B to point-A (from the multi-path observed by point-A and B). Therefore, the number of paths from point A and point B are the same as from point B and point A, the paths/ray-traces from point A and point B are the same as from point B and point A, the delay (traveling time) of each path from point A and point B is the same as from point B and point A, and the relative delay between paths from point A and point B are the same as from point B and point A.
If the multi-path profile from point A to point B and some basic information from point B to point A (such as a time-stamp associated with the strongest path) are known, the multi-path profile (from point B to point A) can be reconstructed using the multi-path symmetry property. Consequently, time stamp information is implemented to reconstruct the multi-path information.
According to one embodiment, the time stamp information is the time at which the strongest path is received. In a further embodiment, the time stamp information is generated by recording a time-stamp of a packet transmitted from a device. Particularly, the receiver 12 is turned on during transmission of the packet, while turning off low-noise amplifiers. The low-noise amplifiers may be turned off because the signal is strong without the amplifiers
The multi-path reconstruction process can be generalized to M-path scenario without specific signal strength relationship between paths. An example with a specific signal strength relationship can be used to explain the process. In this example, A1 >A2>A3, ω1 >ω2 >ω3, where the DP signal is the third strongest signal, e.g., YLOS (t)=A3 S(t −ω3). Further, the DP signal is smaller than two other non—DP paths. The selection of the number of path M, and the DP signal is critical for the final estimation of TOA for the DP signal. The selection of M and DP signal is performed according to the multi-path estimation process 310 described above.
The multi-path profiling information that was computed from the previous stage includes: (a) the number of paths M; (b) the DP signal among the M paths is known (e.g., DP=3); and (c) signal strength relationship and TOA associated with each path, e.g., A1 >A2 >A3,ω1, >ω2 >ω3 . The basic concept is to use the relative time offset information between the strongest path and the DP path from one unit to reconstruct the same information for the other unit using the available time-stamp associated with the strongest path.
According to one embodiment, the multi-path estimation process includes applying the multi-path estimation process, or other multi-path estimation algorithms, to the wireless data received by the first radio unit (point A to B) and estimating the multi-path profile information for each path (i.e., A1,A2,A3, ω1,ω2, ω3 ). Subsequently, the TOA difference between the strongest path and the DP path (e.g., Δω=ω1 −ω3) is estimated.
Assuming the TOA difference between the strongest and DP paths are the same (e.g.,) based on the multi-path symmetric property. Given that the time stamp associated with the strongest path at the second radio unit (point B to A) is known (e.g., ωi .), the TOA for the DP path becomes ω3 =ω1 −Δω. Once the information associated with the DP for both wireless radio units becomes available (ω3 and ω3), the range between the two wireless radio units can be computed, as will be explained in process 330 below.
Note that the above example only illustrates re-constructing the path information using multi-path symmetry property. The information calculated using the TOA technique will be used for ranging/location application. Other multi-path profile information can be re-constructed for different applications if needed. Further, the multi-path reconstruction using symmetry property can apply to other multi-path estimation algorithms and is not limited to the TOA/multi-path estimation process discussed above. Some examples include forward and reverse link in the wireless communication multi-input multi-output (MIMO) and smart antenna applications.
Range Computation
Referring back to
First, Unit #1 receives its own transmit packet immediately (e.g., t1 =O ) and the response packet from Unit #2 at a time D (
Next, Unit #2 receives Unit #1's transmit packet after a delay (t4 =d 12/c ) associated the propagation path (distance),
Based on the multi-path symmetric property described in the previous example, the TOA for the DP path at unit #2 is t4 =d 12/c =ω3 =ω1 −Δω. Given t1 , t2 , t3 , and t4, the distance d12 between unit#1 and unit #2 can be computed by d12 =(m1 −m2) /2, where, m1 =t3 −t1 =D+d 12/c m2 =t2 −t4 =D−d 12/c Once the m1 and m2 values are known, the two unknowns D and d12 can be solved (c is the speed of radio wave and is known).
Wireless Location
Referring back to
Referring to
√{square root over ((X−X1 )2 +(y−y1)2 )}=d1m
√{square root over ((X−X2)2+(y−y2)2 )}=d2m
√{square root over ((X−X3)2+(y−y3)2 )}=d3m
The above-described mechanism enables a mobile to use its own algorithm to estimate multi-path information using TOA techniques without the involvement of access points. Consequently, the client may estimate its range from the access point using the estimations, or simply estimate its location. Note that instead of computing the location at the client/mobile side, for different applications or usage models the location may also be computed at the AP/base-station side or at the network server using a similar triangular method.
Whereas many alterations and modifications of the present invention will no doubt become apparent to a person of ordinary skill in the art after having read the foregoing description, it is to be understood that any particular embodiment shown and described by way of illustration is in no way intended to be considered limiting. Therefore, references to details of various embodiments are not intended to limit the scope of the claims, which in themselves recite only those features regarded as essential to the invention.