The present invention is directed to methods for determining the orientation of a phased array antenna.
If phased arrays are used for cellular communications, they need to be mounted and installed on cell towers. In order to achieve proper RF-Planning performance, any RF-Planning tool needs to be aware of accurate values for the horizontal and vertical orientation of the phased array, i.e., the geographical direction of where the phased array panel is pointing at. However, due to practical complications that occur during installation, tower crew members are often unable to place the phased array exactly at the intended orientation. As a result, RF-Planning, network and system level simulations are performed based on inaccurate data, which in turn leads to unreliable simulation results. Network operators struggle with this problem to the extent that they acquire external, often expensive devices to indicate the correct orientation, with differing levels of accuracy.
In the following, a procedure which enables one to accurately determine the correct orientation of a phased array using successive beamforming is described.
In general, in one aspect, the invention features a method of determining an orientation of a phased array antenna. The method involves: positioning a communication device in front of the phased array antenna; with the phased array antenna, sequentially generating each beam pattern of a library of multiple beam patterns; for each of the sequentially generated beam patterns from the library of multiple beam patterns, and by using either the phased array antenna or the communication device, measuring a received signal parameter, wherein the received signal parameters for the library of multiple transmit beam patterns form a measured received signal vector for the phased array antenna; and determining the orientation of the phased array antenna by comparing the measured received signal vector for the phased array antenna to each of a plurality of calculated received signal vectors.
Other embodiments include one or more of the following features. The method also involves determining location coordinates for the communication device and for the phased array antenna. Each calculated received signal vector of the plurality of calculated received signal vectors corresponds to a different hypothesized orientation for the phased array antenna. The method also involves for each hypothesized orientation of a plurality of hypothesized orientations for the phased array antenna, using the beam library to compute the corresponding calculated received signal vector for that hypothesized orientation. The library of multiple beam patterns is a library of multiple transmit beam patterns or alternatively it is a library of multiple receive beam patterns. The communication device is a receiving device and measuring the received signal parameter is performed at the communication device or, alternatively, it is a transmitting device and measuring the received signal parameter is performed at the phased array antenna. Determining the orientation of the phased array antenna involves comparing the measured received signal vector for the phased array antenna to each calculated received signal vector of the plurality of calculated received signal vectors to determine an angle of departure or arrival for the phased array antenna. It also involves converting the angle of departure or arrival for the phased array to the orientation of the phased array antenna. Comparing the measured received signal vector for the phased array antenna to each calculated received signal vector of the plurality of calculated received signal vectors involves finding which calculated received signal vector among the plurality of calculated received signal vectors yields a best fit with the measured received signal vector. Comparing the measured received signal vector for the phased array antenna to each calculated received signal vector of the plurality of calculated received signal vectors involves employing a pattern matching algorithm. The pattern matching algorithm employs a least squares technique. The received signal parameter is RSRP (Reference Signal Received Power) or SINR (Signal-to-Interference plus Noise Ratio). The method further involves: defining the library of multiple different beam patterns; and storing the library of multiple different beam patterns.
The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.
The algorithm described herein determines the horizontal and vertical orientation of a phased array. Referring to
Referring to
After setting up the measurement device, the GPS coordinates of the phased array (GPSantenna) as well as the measurement device (GPSdevice) are obtained and recorded (step 102).
A phased array includes many antennas placed next to each other with a given spacing. Each antenna is equipped with a variable gain amplifier and a phase shifter. By setting different amplitude and phase values for each antenna, the outgoing signal will have different radiation patterns. In other words, the transmitted signal will have higher power at some angles and lower power at other angles. Similarly, the sensitivity of the array to a received signal will be higher at some angles and lower at other angles. In either case, the radiation pattern and the sensitivity pattern is referred to as a “Beam”. In this phase of the orientation finding procedure, a set of M beams, each generated through a distinct set of amplitude and phase shifts, is chosen (step 104). This set of beams is referred to as the “Beam Library”.
Conceptually, the algorithm will work with any arbitrary beam library. However, the performance of the orientation finding depends on the chosen beams. The following considerations should be taken into account to achieve better performance:
With the beam library defined, a measurement phase is implemented during which measurements are taken while using the phased array to sequentially generate each of the beams from the beam library (phase 108). This step can be performed in two different ways, depending on whether it is being performed in a transmit mode (Tx mode) or in a receive mode (Rx mode). In the Tx mode, the phased array acts as the transmitter; the measurement device acts as the receiver; and the beams of the beam library are successively applied to the transmit port of the phased array. In the Rx mode, the phased array acts as the receiver; the device acts as the transmitter; and the beams of the library are successively applied on the receive port of the phased array. Obviously, for the Rx mode the device needs to be capable of transmission.
In the Tx mode, all beams in the beam library are applied on the transmit port of the phased array one after another. After each beam is applied, the phased array transmits a probe signal which is received by the device and the received power of the probe signal is recorded. Hence, for each beam, there will be one power reading. At the end, after all beams from the beam library have been generated, all measured power values are used to form a vector P (steps 110).
In the Rx mode, the same as the Tx mode, the beams of the library are successively applied on the receive port of the phased array. The device sends a probe signal that is received by the phased array. And the power of the received probe signal is recorded to again form a vector P (steps 110).
If the phased array is used in an isolated setting, the signal that can be used for each of the above modes can be arbitrary. A suitable waveform to be used might be a simple tone. The frequency channel used for the transmission should be one without interference, i.e., no other transmitter in the vicinity of the phased array and the measurement device should be transmitting in the same frequency channel.
If the phased array is used in a cellular network, in the Tx mode, the cell specific reference signals can be used. Periodic reference signals are transmitted by base stations in cellular networks. In order to use the reference signal for orientation finding, the measurement device must be able to read the reference signal. Also, the device must be able to only listen to the reference signals coming from the cell that has the phased array whose orientation is to be found (all commercial mobile phones can do both tasks). The device then measures the power of the received reference signal, which is called RSRP (Reference Signal Received Power). The RSRP value can be used to create the vector P.
In the Rx-mode, a similar approach can be adopted where the device (a mobile phone will work here too) connects to the network and transmits a given signal. Along with the signal, the phone also transmits pilot signals. The cell measures the received power of the pilot signals.
In the next phase, the angle of arrival/departure of the signal (illustrated in
In order to obtain the angle of departure, a pattern recognition algorithm, such as the least squares estimation described below, is used (step 112).
To perform pattern recognition, a range of azimuth and elevation angle hypotheses for the angle of departure are defined (step 106). A hypothesis means the angle which is “guessed” to be the correct angle of departure in azimuth and elevation. The job of the pattern recognition algorithm is to determine which hypothesis is the most likely angle of departure. For instance, the hypothesis set for the orientation finding procedure can be chosen to be the set (−40, −39.5, −39, . . . , 0, 0.5, 1, . . . , 29.5, 30) degrees in azimuth and (0, 1, . . . , 10) degrees in elevation. Hence, the outcome of the pattern recognition will be one azimuth and one elevation angle value out of the above sets which the algorithm estimates to be the correct azimuth and elevation angles of departure. The range and granularity of the above sets is arbitrary, but the wider the range and finer the granularity, the more accurate the outcome can become.
For every possible hypothesis ({circumflex over (Ø)}, {circumflex over (θ)}), where {circumflex over (Ø)} and {circumflex over (θ)} represent the azimuth and elevation angle hypothesis, respectively, and for every beam i from the beam library, the array gain Gi({circumflex over (Ø)}, {circumflex over (θ)}) is calculated (step 108). Gi({circumflex over (Ø)}, {circumflex over (θ)}) is the phased array gain observed by beam i if the correct angle of departure was ({circumflex over (Ø)}, {circumflex over (θ)}). There are well known, standard mathematical formulae for performing such calculations that take the antenna characteristics and frequency as input.
Next, a vector G({circumflex over (Ø)}, {circumflex over (θ)})=(G1({circumflex over (Ø)}, {circumflex over (θ)}), G2({circumflex over (Ø)}, {circumflex over (θ)}), . . . . GM({circumflex over (Ø)}, {circumflex over (θ)})) is defined. It is simply the set of calculated array gains for the complete set of beams within the beam library.
To perform a least squares estimation, the scalars α({circumflex over (Ø)}, {circumflex over (θ)}) and β({circumflex over (Ø)}, {circumflex over (θ)}) for every hypothesis ({circumflex over (Ø)}, {circumflex over (θ)}) are calculated as follows:
where Pi is the measured RSRP using beam pattern i, and M is the total number of beam patterns used.
Then, an error calculation is performed. For every hypothesis ({circumflex over (Ø)}, {circumflex over (θ)}), the vector {circumflex over (P)}({circumflex over (Ø)}, {circumflex over (θ)}) and the error ε({circumflex over (Ø)}, {circumflex over (θ)}) are calculated as follows:
{circumflex over (P)}({circumflex over (Ø)},{circumflex over (θ)})=α({circumflex over (Ø)},{circumflex over (θ)})G({circumflex over (Ø)},{circumflex over (θ)})+β({circumflex over (Ø)},{circumflex over (θ)})
ε({circumflex over (Ø)},{circumflex over (θ)})=Σi(Pi−{circumflex over (P)}i({circumflex over (Ø)},{circumflex over (θ)}))2
Once these calculations are completed for all hypotheses, the hypothesis for which the error is the smallest is selected as the correct angle of departure referred to as ({circumflex over (Ø)}*, {circumflex over (θ)}*).
Using the GPS coordinates of the phased array and the measurement device, the geographical angle between the two with respect to geographic north (Øfinal for azimuth) and with respect to direction normal to the ground (θfinal for elevation) is determined (step 114).
This is done as follows.
To calculate azimuth, both GPS coordinates from Latitude-Longitude format are first transformed to UTM format to determine the Easting and Northing coordinates for both phased array and device. The outcome of this step will be: (Narray, Earray), and (Ndevice, Edevice). Note that the transform from GPS coordinates to UTM is a well-known standard method.
Then, ψ is calculated as follows:
To calculate elevation, the ground distance between the device and the phased array d, as well as the height difference between the two h are measured (refer to
Then, φ is calculated as follows:
The final values for the azimuth Øfinal and elevation θfinal orientation angles are derived as follows. All values are in degrees:
Øfinal=90−Ø*−ψ
θfinal=90−θ*−φ
After the final orientation values are derived, the system operator uses the derived orientation values to perform RF-planning, network and/or system level simulations for the phased array (step 116).
In the above-described embodiment, calculating the array gains for the beams of the beam library, operating the phased array, acquiring the measurements of received power, performing pattern recognition, and determining the orientation angles of the phased array may be computer or processor implemented or controlled. Indeed, for many of these operations it would be impractical to not implement them with the aid of a computer or processor system.
Other embodiments are within the following claims. For example, metrics other than RSRP could be used such as SINR (Signal-to-Interference plus Noise Ratio) among others. In addition, instead of using a least squares algorithm, one could use other pattern matching algorithms such as those based on cross-correlation, parameter estimation, or machine learning, to name a few.
In addition, the procedure can be performed while panel is in full operation mode and while traffic is being transmitted as usual. It can be applied to both FDD (Frequency Division Duplex) and TDD (Time Division Duplex) systems. In case of MIMO, one or multiple ports can be used for the algorithm.
An extension of the orientation finding mechanism, if used in a cellular network, is that instead of placing a measurement device somewhere close to the phased array, another cell can act as the device. That case is similar to the Rx mode except that instead of using a transmit device on the ground, one of the cells is used for this purpose.
Also, the procedure can be performed on multiple locations to increase certainty in final result. For example, one can perform the procedure in four different locations and the results examined to determine what is the best answer. In this case, assume that three out of four locations yield 30 degrees and one location yields 25 degrees. The procedure would output 30 degrees as the right answer.
In addition, for each location, a separate set of beam patterns and a different pattern matching algorithm can be used depending on the characteristics of that location.
Furthermore, to account for irregular channel impairments, each beam pattern can be applied multiple times. The final RSRP reading for beam pattern will be the average of all readings for that beam pattern.
This application claims the benefit under 35 U.S.C. 119(e) of Provisional Application Ser. No. 62/790,636, filed Jan. 10, 2019, entitled “Phased Array Orientation Finding,” the entire contents of which are incorporated herein by reference.
Number | Name | Date | Kind |
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10091662 | Bendlin et al. | Oct 2018 | B1 |
20150326300 | Fujii | Nov 2015 | A1 |
Number | Date | Country |
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108288991 | Jul 2018 | CN |
108710758 | Oct 2018 | CN |
Number | Date | Country | |
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20200227825 A1 | Jul 2020 | US |
Number | Date | Country | |
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62790636 | Jan 2019 | US |