This invention relates generally to beam forming in a wireless network, and more particularly to beam forming in a vehicular network
Vehicular Communications and the WAVE Standard
The IEEE 802.11p specifies wireless access to vehicular environments (WAVE). This standard supports intelligent transportation systems (ITS). The current standard specifies transceivers with a single antenna, and orthogonal frequency-division multiplexing (OFDM) for the modulation technique at the physical layer (PHY). WAVE transceivers include mobile transceiver in vehicles, and stationary road side units (RSUS). The WAVE network can also be used in other mobile environments, such as railways, and water ways.
Multi-Antennas
Generally, multiple antennas transceivers improve throughput and reliability. A number of wireless standards specify OFDM and multiple nput multiple output (MIMO) technologies. These include IEEE 802.16, IEEE 802.11n, and 3GPP LTE (long term evolution).
However, MIMO requires accurate channel state information (CSI), and complex digital processing at the receiver. Providing CSI to the transmitter can require large overhead due to time varying nature of the channel caused by the fast velocity of WAVE transceivers.
Beam forming improves the reliability of focusing an array pattern in a directed beam. That is, the antenna array has a spatially dependent gain that amplifies signals based on there angle of arrival, see Godara “Applications of Antenna Arrays to Mobile Communications, Part I: Performance Improvement, Feasibility, and System Considerations”, Proceedings of the IEEE, Vol. 85, No. 7, pp. 1031-1060, 1997.
The goal of the invention is to improve reliability in WAVE networks using multiple antennas.
Beams are used to communicate in a wireless network including mobile and stationary receivers. The network operates according to the IEEE 802.11p in wireless access to vehicular environments (WAVE).
A direction from the mobile transceiver to the stationary receiver is predicted using geographic information available to the mobile transceiver. A set of signals are received in the mobile transceiver from the stationary transceiver, wherein the signals are received by an array of antennas, and wherein the signals are received using a set of beams, and wherein each beam is approximately directed at the stationary receiver.
A signal-to-noise ratio (SNR) is measured for each beam, and the beam with an optimal SNR is selected as an optimal beam for communicating data between the mobile transceiver and the stationary transceiver.
As shown in
where N is the number of antenna, wn, is the weight applied to the signal sn, received by the nth antenna, w=[w1, w2, . . . , wN]T, s=[s1, s2, . . . , sN]T, T is the transpose operator, and H is the Hermitian operator.
A weight vector wH for the received (or transmitted) signals is a function of a geometry the array of antennas. If the array is linear and uniform as shown in the
wn=exp(jnkd cos φ), (2)
where j is the complex number √{square root over (−1)}, n is the number of antennas, k is the wavenumber, and d is the distance between the antennas. Generally, w={wφ
Eqn. (2) applies to a uniform collinear array antenna as shown in
For example, the vector {w0, w90, w180, w270} represents the weights for beams at angles of {0, 90, 180, 270} degrees. The width of the beam is inversely proportional to the number of antenna elements. Optimally, an eigen beamformer adaptively adjusts the weights in accordance to the observed channel, and selects weights that direct energy into the optimal eigen channel.
However, in a mobile environment, this requires accurate and frequent channel estimates at the receiver, which must be fed back to the transmitter. If the vehicles travel at high speed, the coherence time of the channel is short, and the overhead for the feedback becomes impractical.
GPS Assisted Beam Selection
As shown in
The pointing in the direction 400 of the RSU refers to only the initial search when the transceiver in the vehicle does not known the optimal beam direction. The performance can be improved dramatically when the vehicle refines the beam direction. Therefore, we describe how to determine the optimal beam, at any point in time.
Specifically, if v is the velocity vector of the vehicle as determined by the GPS, then the angular direction is
where (x, y) are the north-south and east-west components of the velocity vector, respectively. Two cases can be considered. If the GPS has data pertaining to the geographical location of RSUs, then the beam can be directed 400 approximately toward the nearest RSU, see
This direction ensures that RSUs are detected as the vehicle approaches, and also provides the capability to find the RSUs that are located along the road, on nearby buildings, overhead signage, and the like. With a substantially wide beam, directing the beam forward is likely to cover a RSU. However, but the performance degrades dramatically if the beam is not directly at the RSU. The problem performance is even worse with narrow beams.
The weight vector with an index nearest to φd is selected from wφ
Alternatively, because the placement of the RSUs along the road will vary geographically, the receiver can search the possible prestored beams, and use the beam with the optimal signal-to-noise ratio (SNR) communicate data. In this case, it is reasonable to limit this search to beams over a small range of angular directions.
If the communications 112 are with other vehicles, then the weight vector with index closest to φd or φd±180 is selected so that the main beam is along the direction of travel.
Determining when to Switch Beams
As the vehicle travels, it will come into range of other RSUs. The GPS can also indicate when the vehicle changes direction. However, in an urban environment, the GPS signal may not always be available, and beam steering becomes unreliable.
OFDM Resource Block
As shown in
Some sub-carriers include pilot symbols 510 for the purposes of channel estimation, and beam selection as described herein. The received signal on each pilot symbol is
rp(n,k)=hn,k*pn,kexp(j2πg(n,k)*ΔfTs)+nn,k
where pn,k is the kth pilot symbol located in the nth OFDM symbol, and hn,k is the channel coefficient for the nth OFDM symbol at sub-carrier k, Δf is the sub-carrier spacing, Ts is the OFDM symbol duration and g(n, k) is a mapping of the OFDM symbol index, n, and the pilot index, k, to the physical sub-carrier index which is in the range of (0, K−1).
If the main beam is aimed directly towards a receiver, then the channel coefficients can be represented by non-zero mean complex Gaussian distributed random variables. This is true for all sub-carriers in the OFDM symbol. However, the beam is not directed at the receiver, then the channel coefficients become zero-mean Gaussian distributed.
The accuracy of the direction of the beam can be verified by determining whether an average T of the sub-channel fading coefficients are near zero or not:
where ñ is the noise component, and an appropriate weight vector can be selected.
Improving Performance Using Previously Traveled Routes
Personal vehicles most frequently travel over a small set of routes between home, work, school, shops, and the like. Commercial vehicles similarly have repetitive routes between. If the arrangement of the RSUS remains relative constant, then the geography of the appropriate routes and angular directions to the RSU along the routes can be determined and stored in a memory for later use, and periodically updated. The angular directions can be sampled, interpolated and evolved while the vehicle is traveling. The directions can include a confidence score.
Determining Frequently Traveled Routes
Routes begin at a start location, and terminate at an end location, which often are the same. Routes are partitioned into segments of length L. A route can include non-overlapping and adjacent segments. A usage metric is associated with each segment in stored memory.
If false, then the method determines 625 whether the memory is full 525. If true, then the segment with a smallest is deletes 630.
If the segment is not in the memory and the memory is not full, the segment is stored 640 in the memory. The usage metrics can decremented over time, so that the usage metric of less frequently traveled routes become zero, and the segments are deleted, so that only the frequently traveled segments are retained.
Storage of Angular Directions
Each segment includes sampled locations ρ. For each sampled location with a usage metric ψ greater than a threshold, a method stores the angular direction φ* that has the optimal SNR as
φdiff=φ*−φRSU,
where φRSU is the angular direction from the vehicle to the RSU. If there is line of sight exists between the vehicle and the RSU, the communication channel has a small number of strong multipath components. Therefore, the two angular locations φ* and φRSU are similar, and φdiff is close to zero. The value φdiff can be quantized to reduce storage. For further memory reduction, especially when the sample locations ρ are near each others, the method can combine φdiff of the ρ sampled locations, and perform low pass filtering to obtain low pass coefficients for storage.
If the exact location of the RSU(xR, yR) is not known, then the location can be inferred from the stored angular directions φ1, φ2, . . . , φρ and corresponding coordinates of sampled locations (x1, y1), (x2, y2), . . . , (xρ, yρ) using a least square solution for the following system of equations,
of the form Ax=b. The least square solution can be determined from bproj, which is a projection of the vector b onto the column space of the array A, and solving Ax=bproj. For an improved estimates, the method can combine the angular directions to a same RSU on multiple road segments to infer the location of the RSU. The vehicle can use the above procedure to update the locations of the RSUs, which can change over time.
Updating Angular Directions
The memory vehicle stores the angular directions that lead to a good signal-to-noise ratio. However, the stored angular directions may not be optimal. In addition, the environment can change over time due to new building construction, vegetation growth and seasonal weather changes.
If true, the method vehicle obtains 610 φmem, SNRmem and ψmem from its memory, and perturbs 615 φmem to obtain a trial angular direction φtrial to be used at the specific location. The signal-to-noise ratio SNRtrial is measured 620 when the beam is formed to the RSU using weighting coefficients corresponding to φtrial.
If the SNRtrial is determined 625 to be below an acceptable threshold, then the stored angular direction may be out of date, and the φmem, SNRmem are deleted. The method can also decrement the usage metric for this segment of the road to refresh memory.
If SNRtrial>SNRmem 630, then the trial angular direction φtrial can potentially be better than φmem. The method selects a random number R in a range [0 1], and compares 640 it to result of a function F(ψmem, SNRmem, SNRtrial). The function has the following properties:
For example, consider
where C is a constant. If F(ψmem, SNRmem, SNRtrial) is less than or equal to the random number R, the new φtrial and SNRtrial are stored. If SNRtrial≦SNRmem, or if F(ψmem, SNRmem, SNRtrial) is greater than the random number r, φmem, SNRmem are retained. This process is very similar to simulated annealing where a current solution is replaced by a nearby random solution. However, in our method, the usage metric ψmem decreases over time when the segment is not traveled.
Although the invention has been described by way of examples of preferred embodiments, it is to be understood that various other adaptations and modifications can be made within the spirit and scope of the invention. Therefore, it is the object of the appended s to cover all such variations and modifications as come within the true spirit and scope of the invention.
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2010239607 | Oct 2010 | JP |
Number | Date | Country | |
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20100248672 A1 | Sep 2010 | US |