Patent Grant
12177043
This application is a 35 U.S.C. § 371 National Stage of International Patent Application No. PCT/EP2020/084486, filed Dec. 3, 2020, designating the United States.
The present disclosure relates to methods for channel estimation, characterization, and system evaluation in line-of-sight (LOS) multiple-input multiple-output (MIMO) microwave radio links. There are disclosed methods as well as radio transceivers and control units for determining channel parameters associated with a wireless propagation channel between two multi-antenna radio transceivers.
Point-to-point microwave radio links provide stable high rate data communication links between two fixed locations. They are often used to provide backhaul for radio base stations of a cellular access network, such as the fourth generation (4G) and fifth generation (5G) access networks defined by the third generation partnership program (3GPP).
These types of point-to-point radio links normally operate over line-of-sight (LOS) propagation channels and may use dual polarization to improve spectral efficiency measured in terms of bits per second and Hertz, bps/Hz, by cross-polar interference cancellation (XPIC) techniques. To further improve spectral efficiency, multiple-input multiple-output (MIMO) techniques may be employed. However, due to the prevailing LOS propagation conditions, the antennas must be carefully positioned in dependence of link distance and carrier frequency to provide the necessary channel rank for MIMO operation. LOS-MIMO techniques for microwave radio links, including aspects of antenna geometry and channel rank, is for instance described in U.S. Pat. No. 7,948,444 B2. When the antenna placement is sub-optimal MIMO precoding methods can be used to mitigate the link throughput performance degradation.
It is often desired to characterize the MIMO propagation channel between transmitter antennas and receiver antennas in a LOS-MIMO system, e.g., to determine a suitable precoding scheme or to evaluate the geometry of a given antenna deployment. However, such characterization is complicated by the fact that significant amounts of phase noise is introduced by oscillators at the transmitter antennas and at the receiver antennas. Phase noise is discussed in, e.g., U.S. Pat. No. 9,479,269 B2, and also by Hani Mehrpouyan, Ali A. Nasir, Steven D. Blostein, Thomas Eriksson, George K. Karagiannidis, and Tommy Svensson, in “Joint Estimation of Channel and Oscillator Phase Noise in MIMO Systems”, IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 60, NO. 9, SEPTEMBER 2012. However, despite the available literature on the topic, there is a continuing need for improved methods of LOS-MIMO channel characterization which are associated with low complexity and low signaling overhead.
It is an object of the present disclosure to provide improved methods for LOS-MIMO channel estimation and characterization. This object is obtained by a computer-implemented method, performed in a network node, for estimating one or more relative channel gains |{tilde over (h)}mn|2 and one or more channel phases {tilde over (ϕ)}mn{tilde over (H)} associated with a wireless propagation channel between N transmit antennas and M receive antennas in a LOS-MIMO communication system. The method comprises configuring a channel equalizer to compensate for differences in complex gain over the wireless propagation channel between the N transmit antennas and the M receive antennas and configuring a phase tracker to compensate for differences in phase between a set of transmit side oscillators at the N transmit antennas and a set of receive side oscillators at the M receive antennas. The method also comprises obtaining a set of equalizer coefficients from the channel equalizer indicative of relative complex gain differences of propagation paths between the N transmit antennas and the M receive antennas and obtaining a set of phase compensation values from the phase tracker representing estimated phases of the set of transmit side oscillators and the set of receive side oscillators. Upon the channel equalizer meeting a convergence criterion, the method estimates the one or more relative channel gains |{tilde over (h)}mn|2 and the one or more channel phases {tilde over (ϕ)}mn{tilde over (H)} based on an inverse function ƒ(⋅)−1 of the set of equalizer coefficients and the set of phase compensation values.
This way channel estimation can be performed in a robust and accurate manner. It is an advantage that the channel estimation is able to operate without transmission of known pilot symbols. It is a further advantage that the methods are able to cope with relatively large amounts of phase noise which is normally present in high carrier frequency microwave radio links. Thus, a method for channel characterization particularly suitable for LOS-MIMO systems is provided.
According to some aspects, the method comprises initially configuring the channel equalizer in a training phase mode of operation. This training phase provides a robust initial acquisition and paves the way for the pilot-less steady-state operation.
According to some other aspects, the method comprises configuring the channel equalizer as a single tap channel equalizer. This reduces computational complexity. For instance, the method may comprises obtaining the set of equalizer coefficients from the channel equalizer as one dominant tap value for each of a set of FIR filters.
According to further aspects, the method comprises tracking the one or more relative channel gains |{tilde over (h)}mn|2 and the one or more channel phases {tilde over (ϕ)}mn{tilde over (H)} over time, wherein the tracking comprises weighting newly estimated channel gains and channel phases in dependence of a phase error metric and/or an MSE metric value. By tracking the channel and accounting for phase error and/or other forms of detection error, such as MSE, the accuracy in the channel estimate can be improved, which is an advantage.
According to additional aspects, the method comprises configuring the phase tracker to estimate a separate phase value [{tilde over (ϕ)}1t, {tilde over (ϕ)}2t, . . . , {tilde over (ϕ)}Nt, {tilde over (ϕ)}1r, {tilde over (ϕ)}2r, . . . , {tilde over (ϕ)}Mr] for each oscillator in the set of transmit side oscillators and for each oscillator in the set of receive side oscillators. By keeping track of separate phase values, it becomes easier to determine channel phase. Also, channel coding can be improved by taking different oscillator phase noise statistics into account.
According to yet further aspects, the method comprises configuring a set of LOS-MIMO pre-coding coefficients based on the one or more relative channel gains |{tilde over (h)}mn|2 and the one or more channel phases {tilde over (ϕ)}mn{tilde over (H)}. Thus, MIMO operation can be improved.
According to aspects, the method comprises evaluating a LOS-MIMO deployment optimality criterion based on the one or more relative channel gains |{tilde over (h)}mn|2 and/or on the one or more channel phases {tilde over (ϕ)}mn{tilde over (H)}. Thus, sub-optimal deployments can be identified and corrected, which is an advantage. For instance, a notification to a network management entity can be triggered if the optimality criterion fails to meet a pre-determined optimality specification. The channel estimate is also applicable in verification of link long-term availability as well as for gathering cross-polar interference statistics.
There are also disclosed herein transceivers, signal processing circuits and computer program products associated with the above-mentioned advantages.
The present disclosure will now be described in more detail with reference to the appended drawings, where:
Aspects of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings. The different devices, systems, computer programs and methods disclosed herein can, however, be realized in many different forms and should not be construed as being limited to the aspects set forth herein. Like numbers in the drawings refer to like elements throughout.
The terminology used herein is for describing aspects of the disclosure only and is not intended to limit the invention. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise.
One or more satellite transceivers 160 may also communicate with wireless devices 140 over extra-terrestrial access links 165. The satellite transceiver 160 may be connected to the core network 130 via a ground station 170. The radio link 166 between the satellite transceiver 160 and the ground station 170 may also comprise LOS-MIMO transceivers as discussed above.
A network monitoring system 180 is connected to the core network 130. This network monitoring function keeps track of the network functions and overall network performance and may implement functions for detecting and mitigating error events, as well as for communication performance monitoring. For instance, the network monitoring function may keep track of the various radio link deployments in the network 100 and remotely configure parameters such as precoding vectors, modulations schemes, as well as filter bandwidths and the like for various tracking algorithms for use in LOS-MIMO systems. The network monitoring function may also control routing of data streams in the network to perform load balancing in dependence of current obtainable data rates on the different backhaul links in the network, and/or warn a network control unit about a potential radio link failure. This way the network control unit can prepare for a backhaul link failure, e.g., by allocating alternative backhaul communication resources, before the LOS-MIMO link actually goes down. The network monitoring function may also evaluate new radio link deployments to see if antenna geometries, i.e., inter-antenna spacing, can be improved, and if so dispatch technicians to adjust antenna geometry.
It is appreciated that LOS-MIMO microwave radio links may be used between almost any two types of wireless devices, even between two mobile wireless devices 140, although they are the most common between fixed location transceivers, such as point-to-point radio links for wireless backhaul applications. This is mainly because of the strict requirements on antenna geometry placed on LOS-MIMO systems in order to obtain the above-mentioned increase in spectral efficiency.
The following mathematical notation will the used throughout this disclosure:
An ideal oscillator generates a pure sine wave. In the frequency domain, this would be represented as a single pair of Dirac delta functions (positive and negative conjugates) at the oscillator's frequency; i.e., all the signal's power is at a single frequency. However, all real-world oscillators have phase modulated noise components. The phase noise components spread the power of a signal to adjacent frequencies, resulting in noise sidebands. Oscillator phase noise often includes low frequency flicker noise and may include white noise.
Consider the following noise-free signal:
s(t)=A cos(2πft)
Phase noise is typically expressed in units of dBc/Hz, which represents the noise power relative to the carrier contained in a 1 Hz bandwidth centered at a certain offset from the carrier. For example, a certain signal may have a phase noise of −80 dBc/Hz at an offset of 10 kHz and −95 dBc/Hz at an offset of 100 kHz. Phase noise can be measured and expressed as single-sideband or double-sideband values, although such considerations have no effect on the present disclosure.
With reference again to
The transmitted signal passes between the N transmit antennas 220 to the M receive antennas 230 over a LOS channel modelled by a complex channel matrix H 210. The channel, generally, applies a relatively slowly time-varying complex gain in-between any two antennas. This complex gain represents a change in amplitude as well as a change in phase. H is the complex-valued channel propagation matrix, which e.g. can be written as
The received signal is down-converted in frequency to baseband using M receive side oscillators 250. The phasor representing the m-th receive side oscillator phase is denoted ejϕ
Note that some antennas on the transmit side and/or at the receive side may share a single oscillator, and some oscillators may share a reference frequency signal. Generally, the higher the frequency of the reference signal, the more correlated the phase noise processes at the two oscillators will be.
Additive noise {n1, n2, . . . , nM} 260 is also added at the receiver. Consequently, the received signal at one of the receive side antenna branches is given by
wk=wk-1−μ(1MT⊗rk-1)⊙[w*k-1⊙(1MT⊗rk-1)−1MT⊗ŝk-1]
The output x from the equalizer 310 in
Denoting ϕk=[ϕ1t, ϕ2t, . . . , ϕNt, ϕ1r, ϕ2r, . . . , ϕMr]T, and assuming that each individual phase noise process follows a Weiner process, the state-observation equations used for phase noise tracking by the phase tracker 320 can be written as
ϕk=ϕk-1+δk
Since the channel propagation phases are not known, the phase estimates from the phase tracker, e.g., the state variables of the Kalman filters, herein denoted by
{tilde over (ϕ)}k=[{tilde over (ϕ)}1t,{tilde over (ϕ)}2t, . . . ,{tilde over (ϕ)}Nt,{tilde over (ϕ)}1r,{tilde over (ϕ)}2r, . . . ,{tilde over (ϕ)}Mr]T
In other words, the representation of oscillator phases {tilde over (ϕ)}k is given by the estimate {circumflex over (ϕ)}k and the potential bias vector Δ. It is noted that the output of the phase tracker 320 is also used to update the equalizer coefficients. This is because the error signal zk-1−ŝk-1, i.e., the difference between the input zk-1 to the demodulator 340 and the estimated modulated information symbol ŝk-1 output from the demodulator 340, must be back-rotated to compensate for the phase rotation applied by the phase rotator 325. Thus, it is realized that a large detection error in phase may have a significant effect on the accuracy of the phase tracker, and also on the equalizer phase and gain compensation.
The output y from the phase rotator 325 is then fed to a signal combiner 330 and then on to a demodulator 340 which generates estimates of the transmitted information symbols. According to an example, the demodulator performs an optimization over the transmission symbol alphabet
After equalization, phase noise correction, and signal combination, the input to the demodulator 340 can be written as:
zn=Σm=1M(wmnrm)e−j{tilde over (ϕ)}
With reference to
When the equalizers converge, we have
(W⊙E*)THϕ=IN
The instantaneous channel matrix estimate can be reconstructed as
{tilde over (H)}=Ĥϕ=(WT⊙EH)−1
Let {tilde over (W)}=(WT)−1, instantaneous relative channel powers |hmn|2 can be calculated as
|hmn|2=|{tilde over (h)}mn|2=|{tilde over (H)}(m,n)|2=|{tilde over (W)}(m,n)|2
Also, let {tilde over (W)}=(WT)−1, the instantaneous channel phase {tilde over (ϕ)}mn{tilde over (H)} can be calculated by a MIMO channel phase estimator 420 as
{tilde over (ϕ)}mn{tilde over (H)}={tilde over (ϕ)}mn{tilde over (W)}+{tilde over (ϕ)}mnΣ
where ϕmn{tilde over (W)} is the phase of {tilde over (W)}(m,n).
The method also comprises configuring S2 a phase tracker 320 to compensate for differences in phase between the set of transmit side oscillators 240 at the N transmit antennas 220 and the set of receive side oscillators 250 at the M receive antennas 230. It is appreciated that a near-constant phase offset vector
Δ=([Δ1t,Δ2t, . . . ,ΔNt,Δ1r,Δ2r, . . . ,ΔMr])T
The method further comprises obtaining S3 a set of equalizer coefficients W from the channel equalizer 310 indicative of relative complex gain differences of propagation paths between the N transmit antennas 220 and the M receive antennas 230, and also obtaining S4 a set of phase compensation values E from the phase tracker 320 representing estimated phases of the set of transmit side oscillators and the set of receive side oscillators. To reduce method complexity, the method may comprise obtaining S31 the set of equalizer coefficients W from the channel equalizer 310 as one dominant tap value for each of a set of FIR filters.
Then, upon the channel equalizer 310 meeting a convergence criterion S5, the method estimates S6 the one or more relative channel gains |{tilde over (h)}mn|2 and the one or more channel phases {tilde over (ϕ)}mn{tilde over (H)} based on an inverse function ƒ(⋅)−1 of the set of equalizer coefficients W and the set of phase compensation values E as was discussed above. This can, for instance, be performed by estimating S61 the one or more relative channel gains |{tilde over (h)}mn|2 and the one or more channel phases {tilde over (ϕ)}mn{tilde over (H)} as
Ĥϕ=(WT⊙EH)−1
where Ĥϕ is a matrix representing the channel gains and the channel phases, as discussed above.
Various convergence criteria can be adopted to determine when channel estimation based on the equalizer and phase tracker states can be performed with sufficient accuracy. For instance, the convergence criterion S51 may comprises any of an equalizer tap variation metric threshold, a receiver mean-squared-error (MSE) metric threshold, a gain error metric, a phase error metric, a bit-error rate, BER, metric threshold, and a packet-error-rate (PER), metric threshold.
The channel estimates can be refined by tracking the channel state over time. For instance, the method may comprise tracking S7 the one or more relative channel gains |{tilde over (h)}mn|2 and the one or more channel phases {tilde over (ϕ)}mn{tilde over (H)} over time, wherein the tracking comprises weighting newly estimated channel gains and channel phases in dependence of a phase error metric and/or an MSE metric value. These error metrics can be obtained from the demodulator function 340 in a known manner. Since the methods rely on equalizer and phase tracker states, i.e., estimates of optimal compensation functions W and E to account for gain and phase perturbations introduced by propagation over the channel H, including phase perturbation introduced by transmit-side and receive-side oscillators, it can be expected that the channel estimates will vary with the detection error. When transmissions conditions are good, the mean-squared error of detection is low, and both the equalizer and the phase tracker errors are small. In this case the channel estimate quality can also be expected to be high. However, when transmission conditions are worse, e.g., due to rain fading and the like, or due to bursts of higher-than-normal phase noise levels, then the channel estimate quality may deteriorate some. Thus, over time, the channel estimate can be improved by tracking and weighting in dependence of a phase error metric and/or an MSE metric value.
Several applications of the proposed MIMO channel estimation methods exist. For instance, the method may comprise configuring S8 a set of LOS-MIMO pre-coding coefficients based on the one or more relative channel gains |{tilde over (h)}mn|2 and the one or more channel phases {tilde over (ϕ)}mn{tilde over (H)}. These pre-coding coefficients may, e.g., form part of a singular value decomposition (SVD) or the like. Such channel pre-coding approaches are known and will therefore not be discussed in more detail herein.
The method may furthermore comprise evaluating S9 a LOS-MIMO deployment optimality criterion based on the one or more relative channel gains |{tilde over (h)}mn|2 and/or on the one or more channel phases {tilde over (ϕ)}mn{tilde over (H)}. It is appreciated that linear combinations of the estimated quantities can also be used with advantage, e.g., to evaluate deployment quality. In case a sub-optimality or a problem is detected based on the channel estimate, the method may comprise triggering S91 a notification to a network management entity if the optimality criterion fails to meet a pre-determined optimality specification. An example of a network management entity 180 was discussed above in connection to
The optimality criterion may, e.g., comprise a channel matrix condition number, a phase variation, or the like.
Particularly, the processing circuitry 710 is configured to cause the node to perform a set of operations, or steps, such as the methods discussed in connection to
The storage medium 730 may also comprise persistent storage, which, for example, can be any single one or combination of magnetic memory, optical memory, solid state memory or even remotely mounted memory.
The node 110, 120, 130, 140, 160, 170, 180 may further comprise an interface 720 for communications with at least one external device. As such the interface 720 may comprise one or more transmitters and receivers, comprising analogue and digital components and a suitable number of ports for wireline or wireless communication.
The processing circuitry 710 controls the general operation of the node 110, 120, 130, 140, 160, 170, 180, e.g., by sending data and control signals to the interface 720 and the storage medium 730, by receiving data and reports from the interface 720, and by retrieving data and instructions from the storage medium 730. Other components, as well as the related functionality, of the control node are omitted in order not to obscure the concepts presented herein.
Thus,
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2020/084486 | 12/3/2020 | WO |
| Publishing Document | Publishing Date | Country | Kind |
|---|---|---|---|
| WO2022/117194 | 6/9/2022 | WO | A |
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| 20220190848 | Jiang | Jun 2022 | A1 |
| Number | Date | Country |
|---|---|---|
| 2012167823 | Dec 2012 | WO |
| Entry |
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| International Search Report and Written Opinion with Transmittal dated Aug. 13, 2021 issued in International Patent Application No. PCT/EP2020/084486 (14 pages). |
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| Number | Date | Country | |
|---|---|---|---|
| 20240048410 A1 | Feb 2024 | US |
