WO2020068039A1 - Multi-radio simultaneous frequency scanning - Google Patents

Multi-radio simultaneous frequency scanning Download PDF

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Publication number
WO2020068039A1
WO2020068039A1 PCT/US2018/052452 US2018052452W WO2020068039A1 WO 2020068039 A1 WO2020068039 A1 WO 2020068039A1 US 2018052452 W US2018052452 W US 2018052452W WO 2020068039 A1 WO2020068039 A1 WO 2020068039A1
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Prior art keywords
rat
samples
ss
detector
fdrs
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PCT/US2018/052452
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French (fr)
Inventor
Javad Razavilar
Yuanye WANG
Gwang-Hyun Gho
Hoang Nguyen
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Javad Razavilar
Wang Yuanye
Gho Gwang Hyun
Hoang Nguyen
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Priority to PCT/US2018/052452 priority Critical patent/WO2020068039A1/en
Publication of WO2020068039A1 publication Critical patent/WO2020068039A1/en

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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/38Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving
    • H04B1/40Circuits
    • H04B1/403Circuits using the same oscillator for generating both the transmitter frequency and the receiver local oscillator frequency
    • H04B1/406Circuits using the same oscillator for generating both the transmitter frequency and the receiver local oscillator frequency with more than one transmission mode, e.g. analog and digital modes
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/005Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission adapting radio receivers, transmitters andtransceivers for operation on two or more bands, i.e. frequency ranges
    • H04B1/0053Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission adapting radio receivers, transmitters andtransceivers for operation on two or more bands, i.e. frequency ranges with common antenna for more than one band
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/02Transmitters
    • H04B1/04Circuits
    • H04B1/0458Arrangements for matching and coupling between power amplifier and antenna or between amplifying stages
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/06Receivers
    • H04B1/16Circuits
    • H04B1/18Input circuits, e.g. for coupling to an antenna or a transmission line

Abstract

A wireless communication device can include an antenna to transduce signals at first and second spectral bandwidths to electrical signals, sampler circuitry to receive the electrical signals and produce samples of the electrical signals at a specified sample rate, a first radio access technology (RAT) detector to determine whether a first synchronization signal (SS) of a first RAT is present in the samples, a second RAT detector in parallel with the first RAT, the second RAT detector to determine whether a second SS of a second RAT is present in the samples, and controller circuitry to adjust a spectral bandwidth of the of the antenna and the specified sample rate of the sampler circuitry based on signals from the first RAT detector and the second RAT detector indicating whether the first SS and the second SS are present in the samples, respectively.

Description

MULTI-RADIO SIMULTANEOUS FREQUENCY SCANNING TECHNICAL FIELD

[0001] Embodiments regard wireless communication systems. Some embodiments regard signal detection methods for radio access technologies (RATs). BACKGROUND

[0002] Modem radio access technologies realized via cellular

communications air-interface standards typically require the mobile radio transceiver to have the capability to autonomously scan frequency bands during initial access acquisition to detect the presence of a base station transmitter within its range. One example of such radio access technology (RAT) is the third-generation partnership project (3 GPP) long term evolution (LIE) standard, which has been commercially deployed widely as a 4th-generation cellular technology. Another example is the New Radio (NR) standard, which is being developed also by 3 GPP and positioned as a 5th-generation RAT.

BRIEF DESCRIPTION OF THE DRAWINGS

[0003] In the drawings, which are not necessarily drawn to scale, like numerals may describe similar components in different views. Like numerals having different letter suffixes may represent different instances of similar components. The drawings illustrate generally, by way of example, but not by way of limitation, various embodiments discussed in the present document.

[0004] FIG. 1 illustrates, by way of example, a diagram of an embodiment of a system for detection of multiple RATs.

[0005] FIG. 2 illustrates, by way of example, a diagram of an embodiment of a detailed version of FIG. 1 by exposing internal signal processing steps and components for RAT1 detector and R AT2 detector of FIG. 1.

[0006] FIGS. 3-5 illustrate, by way of example, diagrams of embodiments of different filters for different synchronization signals (SSs).

l [0007] FIG. 6 illustrates, by way of example, a graph of an embodiment of amplitude vs time for an example RAT SS signal.

[0008] FIG. 7 illustrates, by way of example, a graph of an example of the metric sn as determined based on the received samples rn from FIG. 6.

[0009] FIG. 8 illustrates a block diagram of an example machine upon which any one or more of the techniques (e.g., methodologies) discussed herein can be performed.

DETAILED DESCRIPTION

[0010] To enable a mobile transceiver to detect the presence of a nearby base station, a RAT is designed to detect a unique set of synchronization signals (SSs). For example, in the case of LTE, each base station (commonly referred to as an enhanced Node B, eNodeB, or eNB) transmits a specific signal known as the primary synchronization signal (PSS) at a known periodicity. However, the PSS is provided at a radio frequency (RF) that is not known beforehand to an LTE mobile transceiver (the device that includes the transceiver is commonly referred to as user equipment, or UE, in third generation partnership project (3 GPP) terminology). In the case of NR, each base station (referred to as a gNB) transmits a specific signal known as the NR primary synchronization signal (NR-PSS) at a known periodicity, but at a radio frequency not known

beforehand to the NR mobile transceiver (NR UE).

[0011] The frequency scanner (RAT detector) is typically located inside the baseband m odul ator/ demodulator (modem) of the transceiver, but can be located elsewhere. As the number of RAT s commercially deployed grows over time, a cellular modem can benefit from supporting multiple RATs, rather than just a single RAT, such as to remain commercially and technologically competitive. This means that the modem can detect SSs from multiple RATs. As such the computational complexity, along with the demand for battery power

consumption, has the potential to grow with the number of RATs supported. On the other hand, commercial and technological competitiveness also requires low battery consumption. An efficient method for multi -RAT frequency scanning is a means to that end and that is the topic of embodiments herein. [0012] Embodiments regard an architecture and method to efficiently detect signals from base stations of different RATs, such as RATs that are designed to co-exist in a frequency band. Frequency bands that support co-existence of multiple RATs are common. For example, 4G LTE and 5G NR are designed to co-exist in numerous frequency bands in the range between 600 MFIz and 6000 MHz.

[0013] Embodiments can enable efficient and simultaneous scanning for both LTE and NR in co-existence frequency bands like these. Note that co existence in frequency means that at a frequency in a given geographical area, one of several RATs may be operating, but the said RAT is not a priori determined to the modem. A multi-RAT detector of embodiments can help determine the RAT to which the device can connect.

[0014] The inventors are unaware of any prior solutions that perform simultaneous scanning of multiple RATs using a fast Fourier transform (FFT). A modem designed to support multiple RATs can function by scanning for each RAT individually in a sequential order. Within the same modem, a frequency scanner can be designed specifically for each RAT, and when multiple RATs are supported, their respective frequency scanners are invoked in a sequential order to perform frequency scanning.

[0015] A disadvantage of frequency scanning for multiple RATs

sequentially or disjointly can include computational inefficiency when scanning in frequency bands shared by the different RATs supported. This leads to higher battery consumption and shorter battery life. Another disadvantage of the sequential or disjoint frequency scanning is a potential delay in cell detection, leading to a worse user experience than can otherwise be achieved.

[0016] Embodiments can use a same set of received data samples already transformed into frequency domain (via an FFT) and perform detection of multiple RATs simultaneously. This simultaneous detection shortens the scan time and reduces battery consumption via computational savings and shortening of RF chain on durations, thereby improving the user experience.

[0017] Time-domain signal correlation (or equivalently filtering) can be an important process performed inside a signal detector. Time-domain correlation can be implemented with discrete-time Fourier transform (DFT) of the received signal, point-by-point multiplication of the received signal and the known synchronization signal in frequency domain, and an inverse discrete-time Fourier transform (ID FT) of the product. The efficiency of such transform-based implementation of the correlation operation can be gained by using the fast Fourier transform (FFT) to implement the DFT and IDFT.

[0018] An advantage of embodiments can include speeding up a multi -RAT frequency scan phase. The multi -RAT frequency scan phase can be performed when the phone is powered on, in co-existence frequency bands. When the modem supports both LTE and NR, frequency scan speed can become more pressing than for LTE alone. Embodiments can be implemented to achieve that goal.

[0019] FIG. 1 illustrates, by way of example, a diagram of an embodiment of a system 100 for detection of multiple RATs. The system 100, as illustrated, includes an antenna 102, a tuner and sampler circuitry 104, a buffer 106, multiple RAT detectors 114 and 116, a cell records device 118, and controller circuitry 120. The system 100 illustrates, generally, the principle of simultaneous scanning for multiple RAT synchronization signals (SS’s). For ease of description and comprehension, the principle is described for two RATs.

However, embodiments do not preclude applying the subject matter to more than two RATs.

[0020] The antenna 102 transduces an electromagnetic wave incident thereon into an electrical signal. The antenna 102 can include one or more antennas, such as can be configured in an antenna array.

[0021] The tuner and sampler circuitry 104 receives the electrical signals and periodically provi des a sample of the signals (a value corresponding to the voltage amplitude of the electrical signal). The tuner and sampler circuitry 104 can include one or more impedance devices (e g., resistors, capacitors, inductors, or the like) and an analog-to-digital converter (ADC) or the like. A sample rate of the tuner and sampler circuitry 104 can be variable. The tuner and sampler circuitry 104 can adjust an impedance of circuitry thereof, such as to adjust a center frequency of signals which can be transduced by the antenna 102.

[0022] The buffer 106 receives the samples from the tuner and sampler circuitry 104. The samples include old samples 108 and new samples 110. The old samples 108 can include Mi-l samples from a previous block. The new samples 110 can include N-Mi+l new samples. After the new samples are received, an FFT of the samples 108 and 110 can be performed. The frequency domain representation (FDRS) of the samples 112 (e.g., FFT of the sample) can be recorded in the buffer 106 and then provided to the RAT detectors 114, 1 16. In one or more embodiments, the frequency domain representation of the samples 1 12 can be provided to the RAT detectors 114, 116 without first storing them in the buffer 106.

[0023] The RAT detectors 114, 116 determine, based on the frequency domain representation of the samples 112 whether the samples 108, 110 correspond to a RAT to be detected by the RAT detector 114, 116. More details regarding the operations of the RAT detectors 114, 116 are provided regarding FIGS. 2-8.

[0024] The cell records device 118 includes data indicating cell

identifications (IDs) of respective base stations, a frequency or range of frequencies over which the base stations communicate, or the like. The RAT detectors 114, 116 provide data to the cell records device 118 to determine which cell has been detected. The RAT detectors 114, 116 can indicate (e.g., using one or more bits) a communication technology that they are configured to detect. The cell records device 118 can lookup, based on the ID or the technology from the RAT detectors 114, 116, an ID of a cell associated with the signals.

[0025] The controller circuitry 120 configures the sample rate of the tuner and sampler circuitry 104 and the frequency at which a signal incident on the antenna 102 is efficiently transduced. The controller circuitry 120 can configure the tuner and sampler circuitry 104 to receive signals at a specific frequency or range of frequencies and sampl e the received signals at a specified rate. For example, the frequency or sample rate can be different for a first RAT (e.g., a RAT detector configured to detect LTE) than for a second RAT (e.g., a RAT detector configured to detect new radio (NR)).

[0026] The controller circuitry 120 can retain, in its memory, a record of frequency bands and a set of indicators to indicate which RAT(s) are designed to co-exist in each frequency band. If only one RAT is supported in a given frequency band, the controller circuitry 120 can turn on only the corresponding RAT detector 114, 116. When both RAT1 and RAT2 are supported in a frequency band or are potentially present at radio channels within a frequency band, the central controller circuitry 120 can turns on both RAT detectors 114, 116 and they operate on the same input signal concurrently. The determination of whether either, none of, or both RATs operate in a given frequency band can be carried out by the central controller circuitry 120 based on synchronization frequency raster defined for each RAT. The central controller circuitry 120 can determine whether either, none of, or both RATs are potentially operating at a frequency channel, or synchronization raster point, within a frequency band that supports co-existence of the RATs.

[0027] In one or more embodiments the controller circuitry 120 can be implemented using circuitry, such as a central processing unit (CPU), graphics processing unit (GPU), field programmable gate array (FPGA), or other circuitry, such as can include one or more transistors, resistors, capacitors, inductors, diodes, rectifiers, regulators, logic gates (e.g , AND, OR, XOR, negate, buffer, or the like), multiplexers, switches, or the like configured to perform operati ons of the controller circuitry 120. In one or more embodiments, the controller circuitry 120 can be implemented using the circuitry, software, firmware, or a combination thereof.

[0028] FIG. 2 illustrates, by way of example, a diagram of an embodiment of a detailed version of FIG. 1 with exposed internal signal processing steps and components for RATI detector 114 and RAT2 detector 116.

[0029] Each of the RAT detectors 114, 116 can perform similar operations. The difference between the RAT detectors 114, 1 16 is in the SS 226 A, 226B and the corresponding filter 222 A, 222B. Different RATs have different SSs 226A- 226B and spectral bandwidths. Thus, the filters 222A, 222B are different for different RAT detectors 114, 116.

[0030] The frequency domain representation of the samples 112 can be provided to each of the RAT detectors 114, 116. The frequency domain representation of the samples 112 can be filtered by the filter 222 A, 222B. The filtered samples from the filter 222A, 222B can be provided to a multiplier

224A, 224B and a time domain transform (inverse FFT) operation, performed by a time domain transform unit 232A, 232B. The output of the time domain transform 232 A, 232B can include a linear convolution of the samples 234 A,

234B and linear convolution of the samples 236 A, 236B. The output of the time domain transform 232 A, 232B can be provided to the detector 244 A, 244B as an input.

[0031] The multiplier 224A, 224B can produce a product of a frequency domain representation of the SS 226 A, 226B and the filtered samples from the filter 222 A, 222B. The SS 226 A, 226B can be padded with zeros 228 A, 228B to make the input to the frequency domain transform 230 A, 230B (FFT) of length N. The output of the multiplier 224A, 224B can be provided to a time domain transform unit 238 A, 238B. The output of the time domain transform unit 238 A, 238B can include a linear convolution of samples 240A, 240B and additional samples 242 A, 242B.

[0032] The frequency domain representation of the samples 112 can be used to perform linear convolution of two sequences by first zero-padding the sequences in time domai n. If one of the sequences is compl ex-conj ugated and reversed in time (e.g., the SS 226A, 226B or the filtered samples from the filter 222A, 222B), then the linear convolution is equivalent to the correlation of the two original sequences.

[0033] In one or more embodiments, the FFT of the samples 112 can be used to perform correlation of the received sequence of samples 108 and 110 with the

SS’s 226A, 226B of two RATs concurrently. The correlation can include the SS

226A, 226B conjugated and in reverse order. The correlation process operates on the received samples block-by-block, where each block includes N samples.

Suppose the RATl SS 226 A has a length of Ml samples and RAT2 SS 226B has a length of M2 samples in time domain, where M2 <Ml . The block length can be chosen to be N samples, where A is larger than both Ml and M2. For efficient implementations of the FFT, N can be an integer power of 2.

[0034] A block of N samples 108, 1 10 is stored in a first-in-first-out (FIFO) buffer and a size-AFFT operation is performed on the samples 108, 110 to create the FFT of the samples 112. To obtain the next block, the oldest A Ml+l samples are shifted out of the buffer 106 and the next A Ml +1 received samples 110 are shifted into the buffer 106. Thus, Ml- l newest samples of the previous block become the oldest Ml- 1 samples 108 of the current block. The same set of signal processing steps can be performed on each block of data samples.

[0035] Within each RAT detector 114, 116, out of the N samples of the output of each IFFT operation performed by a time domain transform unit 232A, 232B, N M1+1 samples corresponding to a linear convolution of the samples 234 A, 234B are retained and appended to the previ ous l inear convolution of the samples 236 A, 236B obtained from processing of the previous block. As the concatenation continues, each of the RAT detectors 114, 116 is fed a stream of samples as if they are obtained from direct time-domain correlation between the corresponding SS and the time-domain received samples. This enables the RAT detector 1 14, 116 to detect the arrival time of the transmitted SS when such SS is indeed present in the received signal. Note that the number of linear convolution samples to keep (iV Ml+l) is determined by Ml, the length of the longest SS 226A, 226B among all the RATs to be detected by the RAT detectors 114, 116.

[0036] Embodiments do not impose any condition on the values of Ml and Ml and the ratio between them. The value of each of these variables relates to the spectral bandwidth and the time duration of the corresponding SS 226 A, 226B and the sample rate sufficient large to capture its spectral content.

[0037] The FFT operation 230 A, 230B on each local SS 226 A, 226B can be performed only once and the result can be stored in memory (e.g., non-volatile memory) for repeated use. Hence, the computational complexity associated with the FFT operation 230 is negligible.

[0038] To enable each detector 244 A, 244B to make highly reliable decisions, they are provided with two input signals: one input is a time domain version of the received samples filtered by the RAT filter 222A, 222B, and the other input is a time domain version of the correlation (output of time domain transform unit 238A-238B) between the filter output and the local SS 226A- 226B. The filter 222A, 222B can be used when the sample rate is wider than the bandwidth of the SS, so that the samples input to the detector 244 A, 244B are only limited to the part of the spectral band in which the SS 226A-226B is transmitted. [0039] When the sampling bandwidth is larger than the minimum required to capture both RAT1 SS and RAT2 SS spectral regions, the RAT1 filter 222 A and RAT2 filter 222B can be performed in a complementary manner as to achieve computational savings. Filtering can be achieved in frequency domain by multiplying the frequency domain representation of the samples 1 12 with a set of filter coefficients in the filters 222 A, 222B.

[0040] FIGS. 3-5 illustrate, by way of example, diagrams of embodiments of different filters for different SSs. The“Tapering G’ and“Tapering 2” indicate regions in which the received signal is suppressed. The regions of the spectral band contain neither RATI SS nor RAT2 SS. These regions are common for both RATs, so a common set of filter coefficients apply in these spectral regions. In addition to the common tapering, RAT-specific tapering,“RATI Tapering” and“RAT2 Tapering”, can be applied to achieve the filtered signal for each RAT. As illustrated in FIG. 3,“RAT1 tapering” applies frequency-domain filter coefficients to parts of the band to allow only RAT1 SS to pass when present. Similarly,“RAT2 tapering” applies frequency-domain filter coefficients to other parts of the band to allow only RAT2 SS to pass when present. Complementary filtering can be applied when hypothetical spectral supports for the SS’s completely overlap (FIG. 3), partially overlap (FIG. 4), or are disjoint (FIG. 5).

[0041] With each detector 244A-244B as shown in FIG. 2 being provided with two inputs as explained above, highly reliable detection methods can be devised to make a decision at each time step as to whether an SS 226A, 226B is present. An example of such detection method is the generalized likelihood ratio test (GLRT), where the squared magnitude of the correlator output is compared to a scaled version of the sliding-window sum the squared magnitude of the filter output.

[0042] In a binary hypothesis test, if a test statistic, sometimes called a decision statistic, is greater than (or equal to) a threshold, a first decision is made and if the test statistic is less than (or equal to) the threshold, a second decision is made. The GLRT is a generalized version of the binary hypothesis test.

[0043] In one or more embodiments, the detector 244 A, 244B can implement a detection m ethod that is a specialization of the GLRT. Let rn denote the sequence output from the IFFT operation performed by a time domain transform unit 232 A, 232B following the RAT filter 222A, 222B, where n denotes the sample index; this sequence is one of the two inputs to the detector 244 A, 244B shown in FIG. 2.

[0044] This description is general in nature and can be applied to any signal detector. Let s = [so, si, ... , si-iE denote the time-domain sequence of the SS

226A, 226B, where L denotes the length of the time-domain sequence of samples. For convenience, the SS 226A, 226B can be normalized such that s has unit magnitude (i.e. |js|| = 1, sometimes called a normalized magnitude). Also, let

Figure imgf000012_0001

[0045] At each time, n, a GLRT -based decision can be made as in Equation 1 :

Figure imgf000012_0002

[0046] where H\ is the hypothesis that says the SS 226 A, 226B sequence, s, is present in and aligned with the received sequence r n, Ho is the null hypothesis which says s is not present in or is not aligned with r n, and a is a threshold parameter, which can be varied to trade-off between false-alarm (false-positive) and missed-detection probabi liti es. Note that on the left-hand side of the deci sion

Figure imgf000012_0003
S sH rn !\ 2

is the output of a correlator in FIG. 2, i.e., the output of the time domain transform unit 238 A, 238B (e.g., implementing an IFFT) following the corresponding point-by-point multiplier 224A, 224B; in other words,

Figure imgf000012_0004
is an input to the corresponding 244 A, 244B.

[0047] Computational efficiency can be realized by noting that the decision rule of Equation 1 can be expressed in an equivalent form as Equation 2:

Figure imgf000012_0005

[0048] Where sn is defined by Equation 3 :

Figure imgf000013_0001

[0049] When the detection rule in Equation 1 above favors Ho, the associated statistics can be discarded to save memory space and any subsequent processing that would be unnecessary. When the detection rule in Equation 1 above favors Hi, the associated decision statistic Sn defined in Equation 3 can be evaluated and saved along with the index n for further processing. A benefit of this process is that the detection rule in Equation 1 does not require any arithmetic division during runtime, while the arithmetic division in Equation 3 is executed only in instances when detection rule in Equation 1 favors H\ . The number of times such division is performed is proportional to the false-alarm probability, which can be made very small by controlling the threshold a.

[0050] The sequence Sn can be fed to a peak detector, which looks for locations of time index n where Sn exhibi ts local peaks; such peaks indicate with a high probability that the SS is present at the corresponding times in the received sample sequence.

[0051] FIG. 6 illustrates, by way of example, a graph 600 of an embodiment of amplitude vs time for an example RAT SS signal. The graph of FIG. 6 illustrates the efficacy of the decision metric Sn. Even when the received signal is powerful in regions where the SS is not present (the“interference” regions), the metric does not tend to make more false alarms in these regions than in region where the SS is present (“SS signal”). This indicates the ability of Sn to effectively discriminate between the desired signal and undesired samples. This property provides great benefits in very commonly occurring scenarios such as time-division duplexing channels, where uplink transmissions from a nearby cellular phone can be much more powerful than downlink SS. Also, the high peak makes it effective to drop other stati stics where decision rule in Equation 1 favors Ho, or equivalently Sn is below the threshold a. To tradeoff between false-alarm and detection probabilities (by controlling a), it is useful to note that the false-alarm probability per decision is given by Equation 4: Pf = 1 - F(a(L - 1); 2,2 (L - 1)) = (a + l)1 1 Equation

4

[0052] where F(x; n, m) is the cumulative density function (CDF) of the central -distribution and L is the length of the given SS. The detection probability is given by Equation 5 :

Pd = 1 - F(a(L - 1); 2,2 (L - 1), l) Equation 5

[0053] where F(x; n, m , 1) is the CDF of the non-central /'-distribution; the non-centrality parameter l is equal to the post-correlation signal-to-noise ratio (SNR) given by Equation 6:

l = 2L · SNRprecor Equation 6

[0054] where SNRprecor is the SNR before correlation.

[0055] FIG. 7 illustrates, by way of example, a graph 700 of an example of the metric sn as determined based on the received samples rn from FIG. 6. The spike in FIG. 7 shows that the SS is detected early in the SS signal window.

[0056] Example Application of the Present Invention to LTE and NR

[0057] Embodiments are applicable to LTE and NR RATs. This example illustrates more specifically how embodiments can be applied to concurrently detect synchronization signals that have different spectral bandwidths. The LTE primary synchronization signal (PSS) is an orthogonal frequency division multiplex (OFDM) based signal, has a length of TVe = 64 samples in frequency domain and a sub carrier spacing A/e e{7.5, 15} kHz. Similarly, the NR PSS is an OFDM-based signal, has a length of A7r = 128 samples in frequency domain and a sub carrier spacing D f = 2m 15 kHz where m E (0,1, 2, 3, 4}. Thus, in general the sub carrier spacing values for the two RATs are related by A/r = M · A/e where M E { 2m , 2m+1 }. Given the sub carrier spacing and the sequence length in time domain, LTE PSS and NR PSS respectively have nominal bandwidths given by WQ = NeAfe and W r = iVrA/r. With the standardized numerology, NR PSS always has a wider spectral bandwidth than LTE PSS. To capture both signals, the received signal is sampled at a rate of W = DWr where D > 1. For implementation efficiency, D can be a small integer representing the

oversampling factor relative to the NR PSS bandwidth. The sampling period is given by Equation 7:

Figure imgf000015_0001

[0058] Because the time duration of the LTE OFDM symbol is l/Afe

(ignoring the cyclic prefix), the number of time-domain (TD) sampl es for the LTE PSS is given by Equation 8:

Figure imgf000015_0002

[0059] Similarly, the number of TD samples for the NR PSS is given by Equation 9:

Figure imgf000015_0003

[0060] When using a common sample rate, time domain (TD) sampled SS sequence length for LTE is larger than that for NR by a factor of M, so the values of M\ and M2 in FIG 2 can be given by Equations 10 and 1 1 :

M± = ne Equation 10

M2 = nr Equation 11

[0061] In the case of m = 0 and Afe = 15 kHz, M = 1 and the two SS’s have the same length in time domain.

[0062] The oversampling factor D and the FFT size N are an implementation choice. Consider an example where m = 0 and Af = 15 kHz (so M = 1). In this case i = 2 = 128D, and if D = 2, then Ml = M2 = 256, for which the FFT size /V can be 512 or 1024 or larger. For A,r = 1024, each IFFT performed by the time domain transform unit 232A, 232B, 238 A, and 238B in FIG. 2 produces N

- M\ + 1 = 769 correlation (linear-convolution) samples.

[0063] Although an embodiment has been described regarding LTE and NR, which are OFDM-based signals, embodiments are applicable to non-OFDM- based signals such as code-division multiple access (CDMA) signals, or the like.

[0064] FIG. 8 illustrates a block diagram of an example machine 800 upon which any one or more of the techniques (e.g., methodologies) discussed herein may perform. In alternative embodiments, the machine 800 may operate as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine 800 may operate in the capacity of a server machine, a client machine, or both in server-client network environments. In an example, the machine 800 may act as a peer machine in peer-to-peer (P2P) (or other distributed) network environment. The machine 800 may be, or be a part of, an Autonomous Vehicle, an infrastructure device, a cloud service, a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a mobile telephone, a smart phone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify actions to be taken by that machine. For example, machine 800 may be or be part of the controller circuitry 120 or the RAT detector 114, 116. One or more of the cell records device 118, controller circuitry 120, buffer 106, RAT detector 1 14, 116, tuner and sampler circuitry 104, the antenna 102, multiplier 224 A, 224B, filter 222 A, 222B, or other item of the system 100, 200 can include one or more components of the machine 800. Machine 800 may be configured to implement a portion of the methods discussed herein. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein, such as cloud computing, software as a sendee (SaaS), other computer cluster configurations.

[0065] Examples, as described herein, may include, or may operate on, logic or a number of components, modules, or mechanisms. Modules are tangible entities (e.g., hardware) capable of performing specified operations and may be configured or arranged in a certain manner. In an example, circuits may be arranged (e.g., internally or with respect to external entities such as other circuits) in a specified manner as a module. In an example, the whole or part of one or more computer systems (e.g., a standalone, client or server computer system) or one or more hardware processors may be configured by firmware or software (e.g., instructions, an application portion, or an application) as a module that operates to perform specified operations. In an example, the software may reside on a machine readable medium. In an example, the software, when executed by the underlying hardware of the module, causes the hardware to perform the specified operations.

[0066] Accordingly, the term“module” is understood to encompass a tangible entity, be that an entity that is physically constructed, specifically configured (e.g., hardwired), or temporarily (e.g., transitorily) configured (e.g., programmed) to operate in a specified manner or to perform part, or all, of any operation described herein. Considering examples in which modules are temporarily confi gured, each of the modules need not be instantiated at any one moment in time. For example, where the modules comprise a general-purpose hardware processor configured using software, the general-purpose hardware processor may be configured as respective different modules at different times. Software may accordingly configure a hardware processor, for example, to constitute a module at one instance of time and to constitute a different module at a different instance of time.

[0067] Machine (e.g., computer system) 800 may include a hardware processing circuitry 802 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a hardware processor core, or any combination thereof), a main memory 804 and a static memory 806, some or all of which may communicate with each other via an interlink (e.g., bus) 808. The machine 800 may further include a display unit 810, an alphanumeric input device 812 (e.g., a keyboard), and a user interface (UI) navigation device 814 (e.g., a mouse). In an example, the display unit 810, input device 812 and UI navigation device 814 may be a touch screen display. The machine 800 may additionally include a storage device (e.g., drive unit) 816, a signal generation device 818 (e.g., a speaker), a network interface device 820, and one or more sensors 821, such as a global positioning system (GPS) sensor, compass, accelerometer, or other sensor. The machine 800 may include an output controller 828, such as a serial (e.g., universal serial bus (USB), parallel, or other wired or wireless (e.g., infrared(IR), near field communication (NFC), etc.) connection to communicate or control one or more peripheral devices (e.g., a printer, card reader, etc ).

[0068] The storage device 816 may include a machine readable medium 822 on which is stored one or more sets of data structures or instructions 824 (e.g., software) embodying or utilized by any one or more of the techniques or functions described herein. The instructions 824 may also reside, completely or at least partially, within the main memory 804, within static memory 806, or within the hardware processor 802 during execution thereof by the machine 800. in an example, one or any combination of the hardware processor 802, the main memory 804, the static memory 806, or the storage device 816 may constitute machine readable media.

[0069] While the machine readable medium 822 is illustrated as a single medium, the term "machine readable medium" may include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) configured to store the one or more instructions 824.

[0070] The term“machine readable medium” may include any medium that is capable of storing, encoding, or carrying instructions for execution by the machine 800 and that cause the machine 800 to perform any one or more of the techniques of the present disclosure, or that is capable of storing, encoding or carrying data structures used by or associated with such instructions. Non- limiting machine readable medium examples may include solid-state memories, and optical and magnetic media. Specific exampl es of machine readable media may include: non-volatile memory, such as semiconductor memory devices (e.g., Electrically Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM)) and flash memory devices; magnetic disks, such as internal hard disks and removable disks;

magneto-optical disks; Random Access Memory (RAM); Solid State Drives (SSD); and CD-ROM and DVD-ROM disks. In some examples, machine readable media may include non-transitory machine-readable media. In some examples, machine readable media may include machine readable media that is not a transitory propagating signal.

[0071] The instructions 824 may further be transmitted or received over a communications network 826 using a transmission medium via the network interface device 820. The machine 800 may communicate with one or more other machines utilizing any one of a number of transfer protocols (e.g., frame relay, internet protocol (IP), transmission control protocol (TCP), user datagram protocol (UDP), hypertext transfer protocol (HTTP), etc.). Example

communication networks may include a local area network (LAN), a wide area network (WAN), a packet data network (e.g., the Internet), mobile telephone networks (e.g., cellular networks), Plain Old Telephone (POTS) networks, and wireless data networks (e.g., Institute of Electrical and Electronics Engineers (IEEE) 802.11 family of standards known as Wi-Fi®, IEEE 802.16 family of standards known as WiMax®), IEEE 802.15.4 family of standards, a Long Term Evolution (LTE) family of standards, a Universal Mobile T el ecommuni cati ons System (UMTS) family of standards, peer-to-peer (P2P) networks, among others. In an example, the network interface device 820 may include one or more physical jacks (e.g., Ethernet, coaxial, or phone jacks) or one or more antennas to connect to the communications network 826 In an example, the network interface device 820 may include a plurality of antennas to wirelessly communicate using at least one of single-input multiple-output (SIMO), multiple-input multiple-output (MEMO), or multiple-input single-output (MISO) techniques. In some examples, the network interface device 820 may wirelessly communicate using Multiple User MEMO techniques.

[0072] OTHER NOTES AND EXAMPLES

[0073] Example 1 includes a wireless communication device comprising an antenna to transduce signals at first and second spectral bandwidths to electrical signals, sampler circuitry to receive the electrical signals and produce samples of the electrical signals at a specified sample rate, a first radio access technology

(RAT) detector to determine whether a first synchronization signal (SS) of a first

RAT is present in the samples, a second RAT detector in parallel with the first

RAT, the second RAT detector to determine whether a second SS of a second

RAT is present in the samples, and controller circuitry to adjust a spectral bandwidth of the of the antenna and the specified sample rate of the sampler circuitry based on signals from the first RAT detector and the second RAT detector indicating whether the first SS and the second SS are present in the samples, respectively.

[0074] In Example 2, Example 1 further includes circuitry to produce a frequency domain representation of the samples (FDRS).

[0075] In Example 3, Example 2 further includes, wherein the first RAT detector includes a first RAT filter that passes FDRS within the first spectral bandwidth and filters FDRS outside the first spectral bandwidth to produce first filtered samples.

[0076] In Example 4, Example 3 further includes, wherein the second RAT detector includes a second RAT filter that passes FDRS within the second spectral bandwidth and filters out FDRS outside the second spectral bandwidth to produce second filtered samples.

[0077] In Example 5, Example 4 further includes, wherein the first RAT detector determines a correlation between the first SS and the first filtered samples and compares the determined correlation to the first filtered samples to determine whether the first SS is present.

[0078] In Example 6, Example 5 further includes, wherein the first RAT detector determines the correlation using the first filtered samples and a frequency domain representation of the first SS.

[0079] In Example 7, at least one of Examples 1-6 further includes, wherein the first RAT detector determines a normalized magnitude of the first filtered samples to determine whether the first SS is present.

[0080] In Example 8, Example 7 further includes, wherein the first RAT detector determines a decision statistic only if the normalized magnitude of the first filtered samples is greater than a threshold, and the control circuitry determines the first SS is present only if the decision statistic is greater than (or equal to) a threshold.

[0081] In Example 9, at least one of Examples 1-8 further includes, wherein the first RAT is a long-term evolution RAT and the second RAT is a new radio RAT. [0082] Example 10 includes a method performed by a wireless

communication device, the method comprising transducing, by an antenna, signals at first and second spectral bandwidths to electrical signals, receiving, by sampler circuitry, the electrical signals and producing samples of the electrical signals at a specified sample rate, determining, by a first radio access technology (RAT) detector, whether a first synchronization signal (SS) of a first RAT is present in the samples, determining, by a second RAT detector in parallel with the first RAT, whether a second SS of a second RAT is present in the samples, and adjusting, by controller circuitry, a spectral bandwidth of the antenna and the specified sample rate of the sampler circuitry based on signals from the first RAT detector and the second RAT detector indicating whether the first SS and the second SS are present in the samples, respectively.

[0083] In Example 11, Example 10 further includes producing a frequency domain representation of the samples (FDRS).

[0084] In Example 12, Example 11 further includes passing, by a first RAT filter of the first RAT detector, FDRS within the first spectral bandwidth and filtering FDRS outside the first spectral bandwidth to produce first filtered samples.

[0085] In Example 13, Example 12 further includes passing, by a second RAT filter of the second RAT detector, FDRS within the second spectral bandwidth and filtering FDRS outside the second spectral bandwidth to produce second filtered samples.

[0086] In Example 14, Example 13 further includes determining, by the first RAT detector, a correlation between the first SS and the first filtered samples and comparing the determined correlation to the first filtered samples to determine whether the first SS is present.

[0087] In Example 15, Example 14 further includes determining, by the first RAT detector, the correlation using the first filtered samples and a frequency domain representation of the first SS.

[0088] Example 16 includes at least one non -transitory machine-readable medium including instructions that, when executed by a wireless communication device, cause the wireless communication device to perform operations comprising producing samples of transduced electrical signals at a specified sample rate, determining, by a first radio access technology (RAT) detector, whether a first synchronization signal (SS) of a first RAT is present in the samples, determining, by a second RAT detector in parallel with the first RAT, whether a second SS of a second RAT is present in the samples, and adjusting a spectral bandwidth of the antenna and the specified sample rate of the sampler circuitry based on signals from the first RAT detector and the second RAT detector indicating whether the first SS and the second SS are present in the samples, respectively.

[0089] In Example 17, Example 16 further includes, wherein the operations further include, determining, by the first RAT detector, a normalized magnitude of the first filtered samples to determine whether the first SS is present.

[0090] In Example 18, Example 17 further includes, wherein the operations further include, determining, by the first RAT detector, a decision statistic only if the normalized magnitude of the first filtered samples is greater than a threshold, and determining the first SS is present only if the decision statistic is greater than (or equal to) a threshold.

[0091] In Example 19, at least one of Examples 16-18 further includes, wherein the first RAT is a long-term evolution RAT and the second RAT is a new radio RAT.

[0092] In Example 20, at least one of Example 16-19 further includes, wherein the operations further include one or more of producing a frequency domain representation of the samples (FDRS), passing, by a first RAT filter of the first RAT detector, FDRS within the first spectral bandwidth and filtering FDRS outside the first spectral bandwidth to produce first filtered samples, passing, by a second RAT filter of the second RAT detector, FDRS within the second spectral bandwidth and filtering FDRS outside the second spectral bandwidth to produce second filtered samples, determining, by the first RAT detector, a correlation between the first SS and the first filtered samples and comparing the determined correlation to the first filtered samples to determine whether the first SS is present, and determining, by the first RAT detector, the correlation using the first filtered samples and a frequency domain representation of the first SS.

Claims

CLAIMS WHAT IS CLAIMED IS:
1. A wireless communication device comprising:
an antenna to transduce signals at first and second spectral bandwidths to electrical signals;
sampler circuitry to receive the electrical signals and produce samples of the electrical signals at a specified sample rate;
a first radio access technology (RAT) detector to determine whether a first synchronization signal (SS) of a first RAT is present in the samples;
a second RAT detector in parallel with the first RAT detector, the second RAT detector to determine whether a second SS of a second RAT is present in the samples; and
controller circuitry to adjust a spectral bandwidth of the antenna and the specified sampl e rate of the sampler circuitry based on si gnals from the first RAT detector and the second RAT detector indicating whether the first SS and the second SS are present in the samples, respectively.
2. The wireless communication device of claim 1, further comprising circuitry to produce a frequency domain representation of the samples (FDRS).
3. The wireless communication device of claim 2, wherein the first RAT detector includes a first RAT filter that passes FDRS within the first spectral bandwidth and filters FDRS outside the first spectral bandwidth to produce first filtered samples.
4. The wireless communication device of claim 3, wherein the second RAT detector includes a second RAT filter that passes FDRS within the second spectral bandwidth and filters FDRS outside the second spectral bandwidth to produce second filtered samples.
5. The wireless communication device of claim 4, wherein the first RAT detector determines a correlation between the first SS and the first filtered samples and compares the determined correlation to the first filtered samples to determine whether the first SS is present.
6. The wireless communication device of claim 5, wherein the first RAT detector determines the correlation using the first filtered samples and a frequency domain representation of the first SS.
7. The wireless communication device of claim 1, wherein the first RAT detector determines a normalized magnitude of the first filtered samples to determine whether the first SS is present.
8. The wireless communication device of claim 7, wherein the first RAT detector determines a decision statistic only if the normalized magnitude of the first filtered samples is greater than a first threshold, and the controller circuitry determines the first SS is present only if the decision statistic is greater than (or equal to) a second threshold.
9. The wireless communication device of claim 1, wherein the first RAT is a long-term evolution RAT and the second RAT is a new radio RAT.
2?
10. A method performed by a wireless communication device, the method comprising:
transducing, by an antenna, signals at first and second spectral bandwidths to electrical signals;
receiving, by sampler circuitry, the electrical signals and producing samples of the electrical signals at a specified sample rate; determining, by a first radio access technology (RAT) detector, whether a first synchronization signal (SS) of a first RAT is present in the samples;
determining, by a second RAT detector in parallel with the first RAT detector, whether a second SS of a second RAT is present in the samples; and
adjusting, by controller circuitry, a spectral bandwidth of the antenna and the specified sample rate of the sampler circuitry based on signals from the first RAT detector and the second RAT detector indicating whether the first SS and the second SS are present in the samples, respectively.
1 1. The method of claim 10, further comprising producing a frequency domain representation of the samples (FDRS).
12. The method of claim 11, further comprising passing, by a first RAT filter of the first RAT detector, FDRS within the first spectral bandwidth and filtering FDRS outside the first spectral bandwidth to produce first filtered samples.
13. The method of claim 12, further comprising passing, by a second RAT filter of the second RAT detector, FDRS within the second spectral bandwi dth and filtering FDRS outside the second spectral bandwidth to produce second filtered samples.
14. The method of claim 13, further comprising determining, by the first RAT detector, a correlation between the first SS and the first filtered samples and comparing the determined correlation to the first filtered samples to determine whether the first SS is present.
15. The method of claim 14, further comprising determining, by the first RAT detector, the correlation using the first filtered samples and a frequency domain representation of the first SS.
16. At least one non-transitory machine-readable medium including instructions that, when executed by a wireless communication device, cause the wireless communication device to perform operations comprising:
producing samples of transduced electrical signals at a specified sample rate;
determining, by a first radio access technology (RAT) detector, whether a first synchronization signal (SS) of a first RAT is present in the samples;
determining, by a second RAT detector in parallel with the first RAT detector, whether a second SS of a second RAT is present in the samples; and adjusting a spectral bandwidth of the antenna and the specified sample rate of the sampler circuitry based on signals from the first RAT detector and the second RAT detector indicating whether the first SS and the second SS are present in the samples, respectively
17. The at least one non-transitory machine-redable medium of claim 16, wherein the operations further include, determining, by the first RAT detector, a normalized magnitude of the first filtered samples to determine whether the first SS is present.
18. The at least one non-transitory machine-readable medium of claim 17, wherein the operations further include, determining, by the first RAT detector, a decision statistic only if the normalized magnitude of the first filtered samples is greater than a first threshold, and determining the first SS is present only if the decision statistic is greater than (or equal to) a second threshold.
19. The at least one non-transitory machine-readable medium of claim 16, wherein the first RAT is a long-term evolution RAT and the second RAT is a new radio RAT.
20. The at least one non-transitory machine-readabl e medium of claim 16, wherein the operations further include:
producing a frequency domain representation of the samples (FDRS); passing, by a first RAT filter of the first RAT detector, FDRS within the first spectral bandwidth and filtering FDRS outside the first spectral bandwidth to produce first filtered samples;
passing, by a second RAT filter of the second RAT detector, FDRS within the second spectral bandwidth and filtering FDRS outside the second spectral bandwidth to produce second filtered samples;
determining, by the first RAT detector, a correlation between the first SS and the first filtered samples and comparing the determined correlation to the first filtered samples to determine whether the first SS is present; and
determining, by the first RAT detector, the correlation using the first filtered samples and a frequency domain representation of the first SS.
PCT/US2018/052452 2018-09-24 2018-09-24 Multi-radio simultaneous frequency scanning WO2020068039A1 (en)

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