METHODS FOR REDUCING INTERFERENCE IN COMMUNICATION
SYSTEMS
BACKGROUND
Multiple-input-multiple-output (MIMO) systems represent an advance
in wireless communication. MIMO employs multiple antennas at the
transmitting and receiving ends of a wireless link to improve the data
transmission rate while holding radio bandwidth and power constant.
A MIMO transmitter transmits an outgoing signal using multiple
antennas by demultiplexing the outgoing signal into multiple subsignals
and transmitting the sub-signals from separate antennas.
MIMO exploits multiple signal propagation paths to increase
throughput and reduce bit error rates. Each sub-signal reflects off the
local environment along its associated signal propagation paths. The
spatial richness of the local environment is a function of the
uniqueness and distinctness among the different associated signal
propagation paths. While multiple signal propagation paths cause
interference and fading in conventional radios, MIMO uses these
multiple signal propagation paths to carry more information than
conventional radio transmissions.
FIG. 1 illustrates a basic MIMO wireless link 10, where the transmitter
20 has ma transmitting antennas 1 (2 1- 1...2 1-m), and the receiving
station 30 has N receiving antenna 3 1 (3 1- 1...3 1-n), the number of
transmitters active at a given moment is M, such that M <=M a . A
scattering environment 50 with some degree of spatial richness, or
statistical independence of fading coefficients, exists between the
transmitter and receiver. The channel matrix H represents the
channel connection characteristics (or impulse response) between the
transmitting and receiving antennas, 2 1 and 3 1, respectively.
Most improvements on multiuser MIMO systems have been directed to
single cell environments in which one base station serves several
users. However, in multiple cell environments, capacity gain is
degraded.
Moreover, most prior network MIMO algorithms that were designed to
support multiple users and improve capacity gain assumed that all
base stations in a multi-cell environment have to share all the data
messages to be transmitted to each user. This assumption is difficult
to implement.
SUMMARY
Example embodiments are directed to methods for reducing
interference between users in a system having base stations and
mobile stations that include multiple antennas while limiting feedback
from a mobile station to a base station or vice versa. According to
example embodiments, a base station determines a transmission
beamforming vector without receiving information from other base
stations in the communication system. Moreover, the base station
determines that transmission beamforming vector based only on
information received from a mobile station in the communication
system.
At least one example embodiment discloses a method of reducing
interference in a communication system. The method includes
receiving, by a transmitter, first and second quantized matrices from a
mobile station. The first and second quantized matrices are based on
an estimated channel matrix and an estimated interference matrix.
The method further includes determining, by the transmitter, a
transmission beamforming vector based on the first and second
quantized values.
Some other example embodiments provide a method of reducing
interference in a communication system. The method includes first
determining, by the receiver, a quantized estimated channel matrix
and a quantized estimated interference matrix. The quantized
estimated channel matrix and the quantized estimated interference
matrix are determined by at least one of scalar quantization and
vector quantization. The method also includes second determining, by
the receiver, a receive beamforming vector based on the first
determining.
At least another example embodiment provides a method of reducing
interference in a communication system. The method includes first
determining, by a transmitter, an interfering beam of an interfering
transmitter and second determining, by the transmitter, a
transmission beamforming vector such that a beam from the
transmitter conflicts with the interfering beam at a first time.
BRIEF DESCRIPTION OF THE DRAWINGS
Example embodiments will be more clearly understood from the
following detailed description taken in conjunction with the
accompanying drawings. FIGS. 1-8 represent non-limiting, example
embodiments as described herein.
FIG. 1 illustrates a conventional MIMO wireless link;
FIG. 2A illustrates a two-cell MIMO communication system according
to an example embodiment;
FIG. 2B illustrates a detailed view of a received channel matrix
and an interference channel matrix according to an example
embodiment;
FIGS. 3A and 3B illustrate a method for reducing interference between
users and increasing sum throughput from a serving base station in a
downlink channel of a two-cell MIMO communication system;
FIG. 4 illustrates a method of grouping a plurality of base stations to
minimize interference between mobile stations according to an
example embodiment;
FIG. 5A illustrates conventional beam switching at an even time/first
frequency;
FIG. 5B illustrates conventional beam switching at an odd
time / second frequency;
FIG. 6A illustrates beam switching at an even time/first frequency
according to an example embodiment;
FIG. 6B illustrates beam switching at an odd time/ second frequency
according to an example embodiment;
FIG. 6C illustrates a method of beam switching according to an
example embodiment;
FIG. 7 illustrates a base station including a transmitter according to
an example embodiment; and
FIG. 8 illustrates a receiver the mobile station MSI including a
receiver according to an example embodiment.
DETAILED DESCRIPTION
Various example embodiments will now be described more fully with
reference to the accompanying drawings in which some example
embodiments are illustrated.
Accordingly, while example embodiments are capable of various
modifications and alternative forms, embodiments thereof are shown
by way of example in the drawings and will herein be described in
detail. It should be understood, however, that there is no intent to
limit example embodiments to the particular forms disclosed, but on
the contrary, example embodiments are to cover all modifications,
equivalents, and alternatives falling within the scope of the claims.
Like numbers refer to like elements throughout the description of the
figures.
It will be understood that, although the terms first, second, etc. may
be used herein to describe various elements, these elements should
not be limited by these terms. These terms are only used to
distinguish one element from another. For example, a first element
could be termed a second element, and, similarly, a second element
could be termed a first element, without departing from the scope of
example embodiments. As used herein, the term "and/or" includes
any and all combinations of one or more of the associated listed items.
The terminology used herein is for the purpose of describing particular
embodiments only and is not intended to be limiting of example
embodiments. 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. It will be further understood that the
terms "comprises," "comprising," "includes" and/ or "including," when
used herein, specify the presence of stated features, integers, steps,
operations, elements and/ or components, but do not preclude the
presence or addition of one or more other features, integers, steps,
operations, elements, components and/ or groups thereof.
It should also be noted that in some alternative implementations, the
functions/ acts noted may occur out of the order noted in the figures.
For example, two figures shown in succession may in fact be executed
substantially concurrently or may sometimes be executed in the
reverse order, depending upon the functionality/ acts involved.
Unless otherwise defined, all terms (including technical and scientific
terms) used herein have the same meaning as commonly understood
by one of ordinary skill in the art to which example embodiments
belong. It will be further understood that terms, e.g., those defined in
commonly used dictionaries, should be interpreted as having a
meaning that is consistent with their meaning in the context of the
relevant art and will not be interpreted in an idealized or overly formal
sense unless expressly so defined herein.
Portions of example embodiments and corresponding detailed
description are presented in terms of algorithms and symbolic
representations of operation on data bits within a computer memory.
These descriptions and representations are the ones by which those of
ordinary skill in the art effectively convey the substance of their work
to others of ordinary skill in the art. An algorithm, as the term is used
here, and as it is used generally, is conceived to be a self-consistent
sequence of steps leading to a desired result. The steps are those
requiring physical manipulations of physical quantities. Usually,
though not necessarily, these quantities take the form of optical,
electrical, or magnetic signals capable of being stored, transferred,
combined, compared, and otherwise manipulated. It has proven
convenient at times, principally for reasons of common usage, to refer
to these signals as bits, values, elements, symbols, characters, terms,
numbers, or the like.
In the following description, illustrative embodiments will be described
with reference to acts and symbolic representations of operations (e.g.,
in the form of flowcharts) that may be implemented as program
modules or functional processes including routines, programs,
objects, components, data structures, etc., that perform particular
tasks or implement particular abstract data types and may be
implemented using existing hardware at existing network elements or
control nodes (e.g., a scheduler located at a cell site, base station or
Node B). Such existing hardware may include one or more Central
Processing Units (CPUs), digital signal processors (DSPs), applicationspecific-
integrated-circuits, field programmable gate arrays (FPGAs)
computers or the like.
Unless specifically stated otherwise, or as is apparent from the
discussion, terms such as "processing" or "computing" or "calculating"
or "determining" or "displaying" or the like, refer to the action and
processes of a computer system, or similar electronic computing
device, that manipulates and transforms data represented as physical,
electronic quantities within the computer system's registers and
memories into other data similarly represented as physical quantities
within the computer system memories or registers or other such
information storage, transmission or display devices.
As used herein, the term "mobile station" (MS) may be synonymous to
a mobile user, user equipment, mobile terminal, user, subscriber,
wireless terminal and/ or remote station and may describe a remote
user of wireless resources in a wireless communication network. The
term "base station" may be understood as a one or more cell sites,
base stations, access points, and/or any terminus of radio frequency
communication. Although current network architectures may
consider a distinction between mobile/user devices and access
points/ cell sites, the example embodiments described hereafter may
generally be applicable to architectures where that distinction is not
so clear, such a s ad hoc and/ or mesh network architectures, for
example. Serving base station may refer to the base station currently
handling communication needs of the UE.
Example embodiments are directed to methods for reducing
interference between users in a system having base stations and
mobile stations that include multiple antennas while limiting feedback
from a mobile station to a base station or vice versa. According to
example embodiments, a base station determines a transmission
beamforming vector without receiving information from other base
stations in the communication system. Moreover, the base station
determines that transmission beamforming vector based only on
information received from a mobile station in the communication
system.
FIG. 2A illustrates a two-cell MIMO communication system according
to an example embodiment. As shown, a MIMO communication
system 200 includes first and second base stations BS1 and BS2 and
first and second mobile stations MSI and MS2. The first base station
BS1 serves cell 2 10 and the second base station serves cell 220.
FIG. 2A illustrates that the first base station BS1 is a serving base
station for the first mobile station MSI and the second base station
BS2 is a serving base station for the second mobile station MS2. As
shown, both first and second mobile stations MSI and MS2 receive
interfering signals (interference matrix) because of an overlapping
coverage area.
FIG. 2B illustrates a more detailed view of a received channel and an
interference matrix.
As shown in FIG. 2B, each of the first and second base stations BS1
and BS2 and first and second mobile stations MSI and MS2 includes
first and second antennas. The first and second base stations BS1
and BS include first and second antennas ABs , ABs2i and ABsi2,
ABS22- The first and second mobile stations MSI and MS include first
and second antennas AMs , AMs2i and AMsi2, AMs22-
The first and second base stations BSl and BS2 transmit signals
according to transmission beamforming vectors f i and , respectively.
As will be described below, the transmission beamforming vectors f i
and are determined so as to reduce interference to non-served
mobile stations and increase sum throughput (effective channel gain) .
The first and second mobile stations MSI and MS2 receive signals
according to receive beamforming vectors w i and w2, respectively. As
will be described below, the receive beamforming vectors i and W2
are determined so as to reduce interference from non-serving
transmitters (from base stations and mobile stations) and increase
sum throughput.
Since the first base station BSl serves the first mobile station MSI,
the first mobile station MSI determines an estimated first received
channel matrix H i based on signals and noise received over a
communication link between the first base station BSl and the first
mobile station MSI. Moreover, the first mobile station MSI
determines an estimated second interference channel matrix G2 based
on signals and noise from the second base station BS2 that interfere
with the communication link between the first base station BSl and
the first mobile station MSI.
Estimated receive channel matrix may be referred to as a channel
matrix and the estimated interference channel matrix may be referred
to as an interference matrix.
Since the second base station BS2 serves the second mobile station
MS2, the second mobile station MS2 determines an estimated second
received channel matrix ¾ based on signals and noise received over a
communication link between the second base station BS2 and the
second mobile station MS2. Moreover, the second mobile station MS2
determines an estimated first interference channel matrix G i based on
signals and noise from the first base station BSl that interfere with
the communication link between the second base station BS2 and the
second mobile station MS2.
The first and second mobile stations MSI and MS2 may determine the
estimated first and second received channel matrices Hi and H2 and
the estimated first and second interference channel matrices Gi and
G2 using known algorithms such as MMSE (minimum mean-square
error estimation) .
It should be understood that FIGS. 2A-2B are not limiting and the
second base station BS2 may serve the first mobile station MSI and
the first base station BS1 may serve the second mobile station MS2.
Moreover, while only two base stations and two mobile stations are
illustrated, it should be understood that the MIMO communication
system 200 may include more or less than two base stations and two
mobile stations. The number of antennas in each of the base stations
and mobiles stations can differ and serving base station does not need
to have a same number of antennas as a receiving mobile station.
Accordingly, example embodiments will be described with respect to
the MIMO communication system 200 shown in FIGS. 2A and 2B, but
the example embodiments are not limited to the MIMO
communication system 200 shown in FIGS. 2A and 2B.
Two-Cell MIMO Method
FIGS. 3A and 3B illustrate a method for reducing interference between
mobile stations (users) and increasing sum throughput from a serving
base station in a downlink channel of a two-cell MIMO communication
system.
It should be understood that the methods of FIGS. 3A and 3B may be
implemented in a two-cell or more communication system such as the
MIMO communication system 200 shown in FIGS. 2A and 2B.
Moreover, while FIGS. 3A and 3B are described as being implemented
by the mobile station and the base station, respectively, for a
downlink channel, the methods of FIGS. 3A and 3B may be used for
an uplink channel. For example, the base station may implement the
method of FIG. 3A and the mobile station may implement the method
of FIG. 3B for the uplink.
In the description of FIGS. 3A and 3B below, k and 1are used as user
indexes where (1) k and 1are one or two and (2) k is not the same as 1.
For example, in the MIMO communication system 200, the base
station BS1 and the mobile station MSI have the same user index
because the base station BS 1 is the serving base station for the mobile
station MSI.
FIG. 3A illustrates a method implemented by a mobile station, such as
the mobile station MSI shown in FIGS. 2A and 2B. FIG. 3B
illustrates a method implemented by a base station, such as the base
station BS1 shown in FIGS. 2A and 2B.
As shown in FIG. 3A, a mobile station MSk determines an estimated
received channel matrix Hk and an estimated interference channel
matrix Gi, at S305. The estimated received channel matrix Hk is
determined based channel connection characteristics (or impulse
response) between a base station BSk (e.g., a serving base station for
the mobile station MSk, BS1) and the mobile station MSk (e.g., MSI).
The estimated interference channel matrix Gi is determined based on
channel interference characteristics between the mobile station MSk
and the base station BS1.
Therefore, if the mobile station MSk includes two receivers and the
base station BSk includes two transmitters, then
n 12 Hk = (1)
22
and
Gi = (2)
where for Hxy, x is a receiver for the mobile station MSk and y is a
transmitter for the base station BSk; and for Gxz, z is a transmitter for
the base station BS1.
Using FIGS. 2A and 2B as an example, the mobile station MSI
determines the estimated interference channel matrix G2 based on the
channel interference characteristics between the mobile station MSI
and the base station BS2.
The mobile stations MSk and MSI may determine the estimated
received channel matrices Hk, Hi and the estimated interference
channel matrices Gk, Gi using conventional methods such as MMSE.
At step S3 10, the received channel matrix Hk and the interference
channel matrix Gi are quantized by the mobile station MSk. To
quantize the received channel matrix Hk and the interference channel
matrix Gi, the mobile station MSk first determines estimated channel
information matrices I¾k and RGI by
and
where Hk* is a homogenization of Hk, is a normalization factor
of Hk, Gi* is a homogenization of Gi, and ||G;|| is a normalization factor
of Gi.
Both the estimated channel information matrices RHk and RGI are
Hermitian matrices with a unit Frobenius norm, therefore RHk and RGI
have the following properties:
R + R 22 = 1 (5)
22 = 1 (6)
R *= R 2 \ (7)
Therefore, three values may be used to quantize the estimated
channel information matrices ¾ k and RGI. For example, Rf , {R }
and lm{R 2} may be used to quantize the estimated channel
information matrix !¾¾.
Consequently, each quantized estimated channel information matrix
RHk and RGl are determined by the mobile station MSk by
quantization of three values. The mobile station MSk may use scalar
and/or vector quantization.
To determine the quantized estimated channel information matrix RHk
by scalar quantization, the mobile station may quantize three values
as follows:
Q(R ) , Q {R l2}) and Q(lm{R 2})
To determine the quantized estimated channel information matrix R l
by scalar quantization, the mobile station may quantize three values
as follows:
Q(RG ) , ( e{RG12 }) and (Im{RG12 })
To determine the quantized estimated channel information matrices
RHK and RG L by vector quantization, the mobile station may quantize
three values as follows:
and
where (vH), (VG
The quantization used by the mobile station MSk may be based on
uniform or non-uniform quantization. For uniform quantization, the
mobile station MSk may use a same codebook for all values that are
quantized. For example, T/6 bits may be used per value, where T is a
total feedback overhead to the base station BSk. For non-uniform
quantization, different codebooks may be used. For example, T/ 10
bits may be used for Q(R ) and Q{RG ) a n T/5 bits may be used for
the remaining elements. As uniform and non-uniform quantization
are known in the art, a more detailed description will be omitted for
the sake of clarity.
Moreover, the mobile station may implement at least one of scalar and
vector quantization based on SINR (signal-to-interference-and-noise
ratio). For example, scalar quantization may be used when SINR is
high. When SINR is low and the quantization level is not large (e.g.,
codebook size is less than 5 bits/ user), vector quantization may be
used.
Once the estimated channel information matrices I¾k and RGI are
quantized by the mobile station MSk, the mobile station MSk
feedbacks to the base station BSk, the quantized estimated channel
information matrices RHk and RGl at S3 15.
The base station BSk determines a transmission beamforming vector,
as will described later with reference to FIG. 3B based on the feedback
matrices. Since each base station may determine a transmission
beamforming vector based on information from a mobile station that
the base station serves, cooperation among base stations through a
backbone may be eliminated.
At S320, the mobile station MSk determines a receive beamforming
vector. First, the received signal at the at the mobile station MSk is
given by
¾ =V— + ,' . —WfcG + n k
where f is the transmission beamforming vector, ½ is the receive
beamforming vector, x is the data signal for the mobile station MSk,
ik is a noise vector at the mobile station MSk and P/2 is the transmit
power for the base station BSk. Based on equation (1 1), the receive
beamforming vector may be determined by
where I is the interference for the number of receiving antennas N
(e.g., 2), and fi is a transmission beamforming vector from the base
station BS1 to the mobile station MSI. As shown in equation (12), the
mobile station MSk may determine the receive beamforming vector
based on the estimated received channel matrix Hk and the estimated
interference channel matrix Gi that are directly determined at the
mobile station MSk. Alternatively, it should be understood that the
mobile station MSk may determine the receive beamforming vector
based on the quantized estimated channel information matrices R
and RGl to determine a channel matrix and an interference matrix.
The determined received beamforming vector k increases effective
channel gain and minimizes the interference from interfering
transmitters.
While FIG. 3A is described with reference to the mobile station MSk,
the mobile station MSI can implement the same method and calculate
quantized estimated channel information matrices RHl and RGk .
Therefore, for the sake of clarity and brevity a further description is
not provided.
In a TDD (time-division duplex) system, S3 10 and S3 15 may be
skipped. The base station BSk may estimate the downlink channel
using reciprocity. Reciprocity is known and, therefore, will not be
described in greater detail.
FIG. 3B illustrates a method implemented by a base station, such as
the base station BSk.
At S350, the base station BSk receives the quantized estimated
channel information matrices RHk and RGl . Based on the quantized
estimated channel information matrices RHk and RGl , the base station
BSk determines the transmission beamforming vector in step S355.
The transmission beamforming vector may be determined as follows (if
base station BSk knows perfect information) :
where I is the interference for a number of transmitting antennas Nt
(e.g., 2). However, since the base station BSk most likely does not
know perfect information, the base station may substitute the received
channel matrix ¾ and the interference channel matrix Gk with the
quantized estimated channel information matrices RHk and RGk ,
respectively.
After the transmission beamforming vector is determined, the base
station BSk uses the transmission beamforming vector to
communicate with the mobile station MSk, at S360. Therefore, the
base station BSk determines the transmission beamforming vector
without receiving information from other base stations in the
communication system. Moreover, the base station BSk determines
that transmission beamforming vector based only on information
received from the mobile station MSk in the communication system.
Greater than Two-Cell MIMO Method
FIG. 4 illustrates a method of grouping a plurality of base stations to
minimize interference between mobile stations.
As shown in FIG. 4, base stations BSl, BS3, BS5, BS7 and BS9 are
positioned in a first building and base stations BS2, BS4, BS6 and
BS8 are positioned in a second building. At an even scheduling time
(for TDD) or first frequency band (for FDD), base stations BS k and BS
k+1 support two mobile stations using the transmission beamforming
vector determined in equation (13), where k equals 1, 3, 5 and 7. At
an odd scheduling time or a second frequency band, base stations BS
k+1 and BS k+2 support two mobile stations using the transmission
beamforming vector determined in equation (13). Each mobile station
uses the receive beamforming vector determined in equation (12).
Each base station BS1-B9 knows the physical beam switching
pattern/ frequency partitioning because the physical beam switching
pattern/ frequency partitioning is broadcasted to all of the base
stations BS1-BS9. The beam switching pattern/ frequency
partitioning may be determined based on cell planning which includes
at least one of (1) locations of the base stations BS1-BS9, (2) cell
structures and (3) empirical data.
FIGS. 5A and 5B illustrate a conventional method of beam switching
(for TDD)/frequency partitioning (for FDD) to avoid background
interference from non-supporting base stations. The arrows shown in
FIGS. 5A and 5B indicate the direction of the beam. FIG. 5A
illustrates the beam switching/frequency partitioning at an even
time/first frequency and FIG. 5B illustrates the beam
switching/frequency partitioning at an odd time/ second frequency.
Each FIGS. 5A and 5B show a plane 500 which is used a reference to
describe the directions and angles of beams of the base stations BS 1,
BS3 and BS5.
As shown in FIG. 5A, non-supporting base stations BSl, BS3 and BS5
transmit beams in a positive azimuth direction. More specifically, the
base station BSl, the base station BS3 and the base station BS5
transmit beams in a right direction.
Additionally, each of the non-supporting base stations BSl, BS3 and
BS5 transmits a beam at an opposite angle of the adjacent nonsupporting
base stations. As shown in FIG. 5A, the base station BSl
transmits a beam at a 45 degree angle with respect to the plane 500.
The non-supporting base station adjacent to the base station BSl, the
base station BS3, transmits a beam at a -45 degree angle with respect
to the plane 500. Since the base station BS3 transmits the beam at a
-45 degree angle, the adjacent non-supporting base station BS5
transmits a beam at a 45 degree angle with respect to the plane 500.
While 45 and -45 degree angles are used to describe example
embodiments, any angle and any number of beams may be used.
In FIG. 5B, each of the base stations BSl, BS3 and BS5 switch the
directions of the beams, respectively, for odd timing or a second
frequency. More specifically, each of the base stations BS 1, BS3 and
BS5 transmits a beam in a negative azimuth direction. In other
words, the base station BSl, the base station BS3 and the base
station BS5 transmit beams in a left direction.
Additionally, each of the non-supporting base stations BSl, BS3 and
BS5 transmits a beam at an opposite angle of the adjacent nonsupporting
base stations. As shown in FIG. 5B, the base station BSl
transmits a beam at a 45 degree angle with respect to the plane 500.
The non-supporting base station adjacent to the base station BSl, the
base station BS3, transmits a beam at a -45 degree angle with respect
to the plane 500. Since the base station BS3 transmits the beam at a
-45 degree angle, the adjacent non-supporting base station BS5
transmits a beam at a 45 degree angle with respect to the plane 500.
FIGS. 6A and 6B illustrate a method of beam switching/frequency
partitioning to avoid background interference from non-supporting
base stations according to example embodiments. The arrows shown
in FIGS. 6A and 6B indicate the direction of the beam. FIG. 6A
illustrates the beam switching/frequency partitioning at an even
time/first frequency and FIG. 6B illustrates the beam
switching/frequency partitioning at an odd time/ second frequency.
Each FIGS. 6A and 6B show a plane 600 which is used a reference to
describe the directions and angles of beams of the base stations BS 1,
BS3 and BS5. FIG. 6C illustrates a flow chart of the method shown in
FIG. 6A and 6B.
As shown in FIG. 6A, non-supporting interfering base stations are
allocated into groups of two. As provided above the beam
switching/frequency partitioning, including the allocation, is
determined based on cell-planning. For each group of two base
stations, the base stations transmits beams at opposite directions and
opposite angles so that the beams directly conflict, creating a large
interference. More specifically, a first beam is transmitted in a
negative azimuth direction and a second beam is transmitted in a
positive azimuth direction. The first beam may be transmitted at a
first angle and the second beam is transmitted the negative of the first
angle.
For example, in FIG. 6A, the base station BSl and the base station
BS3 are in one group for the even time/first frequency. The base
station BSl transmits a beam in a positive azimuth direction and at
an angle of 45 degrees with respect to the plane 600. The base station
BS3 transmits a beam in a negative azimuth direction and at an angle
of -45 degrees with respect to the plane 600. Therefore, the beams of
the base station BSl and the base station BS2 directly conflict.
At the even time/ first frequency, a mobile station and serving base
station may implement the two-cell MIMO method to determine
receive and transmission beamforming vectors that reduce or
eliminate the direct conflict interference.
For example, a mobile station (e.g., MSI) that is served by the base
station BS 1 and the base station BS 1 may determine the transmission
and receive beamforming vectors according to the method of FIGS. 3A
and 3B to eliminate or reduce the interference from the base station
BS3. The mobile station served by the base station BSl and the base
station BS 1 may determine a transmission beamforming vector and a
receive beamforming vector based on FIGS. 3A-3B, where the base
station BS3 is the interfering base station.
Therefore, the interference from the base station BS3 is reduced, or
eliminated, and there is marginal interference from the base station
BS5, as shown in FIG. 6A. By reducing or eliminating the strongest
interference (direct conflict), the beam switching sequence (time
domain) or frequency partitioning pattern (frequency domain)
minimize interference from other neighboring base stations (e.g., base
station BS5). The base station BS3 and all other base stations may
perform the same functions and determinations as the base station
BSl. Therefore, for the sake of clarity and brevity, a detailed
description of the base station BS3 is omitted.
At an odd time/ second frequency, the groupings and beams are
switched, as shown in FIG. 6B. For each group of two base stations,
the base stations transmits beams at opposite directions and opposite
angles so that the beams directly conflict, creating a large
interference. More specifically, a first beam is transmitted in a
negative azimuth direction and a second beam is transmitted in a
positive azimuth direction. The first beam may be transmitted at a
first angle and the second beam is transmitted the negative of the first
angle.
For example, the base station BS3 and the base station BS5 are in
one group for the odd time/ second frequency. The base station BS3
transmits a beam in a positive azimuth direction and at an angle of -
45 degrees with respect to the plane 600. During the odd
time/ second frequency, the base station BS3 transmits a beam at a
same angle as the even time/ first frequency, but in a different
direction. The base station BS5 transmits a beam in a negative
azimuth direction and at an angle of 45 degrees with respect to the
plane 600. Therefore, the beams of the base station BS3 and the base
station BS5 directly conflict.
At the odd time/ first frequency, a mobile station and serving base
station may determine transmission and receive beamforming vectors
according to the two-cell MIMO method to reduce or eliminate the
direct conflict interference. The base station BS3 and/or BS5 may
implement the two-cell MIMO method based on FIGS. 3A and 3B to
determine transmission and receive beamforming vectors that reduce
or eliminate the conflicting interference term. For the sake of brevity,
an example was given above with reference to the base station BS1,
therefore, a more detailed description of implementing the two-cell
MIMO method is omitted.
FIG. 6C illustrates a flow chart of the beam switching/frequency
partitioning methods of FIGS. 6A and 6B. FIG. 6C may be
implemented by serving base stations at an even time/ first frequency
and at an odd time / second frequency.
As shown, at S605, a serving base station determines whether TDD is
used. If TDD is used, the serving base station then determines an
interference beam (e.g., interference channel information) at S6 10.
The mobile station being served by the serving base station
determines the downlink channel from the serving base station and
interference terms from interfering base stations. Therefore, the
mobile station feeds back the downlink channel (from the serving base
station) and the strongest interference (from the interfering base
station) to the serving base station.
Based on the interference beam, the serving base station determines
the transmission beamforming vector at S6 15. The transmission
beamforming vector is determined to directly conflict with the
interference beam, as illustrated in FIGS. 6A and 6B and described
with reference to FIGS. 6A and 6B. The transmission beamforming
vector is determined by the serving base station using the method of
FIGS. 3A and 3B. At S620, the serving base station transmits
information using the transmission beamforming vector.
At S625, the serving base station determines whether there is a
change from even to odd time or from odd to even time. If there is no
change, the serving base station continues to transmit using the
transmission beamforming vector. If there is a change, the serving
base station switches beam directions at S630.
Once the base station switches beam directions, the base station
repeats S6 10 to S625. More specifically, the serving base station
determines a second interference beam and a second transmission
beamforming vector based on the second interference beam. The
serving base station then transmits information using the second
transmission beamforming vector.
For example, the base station BS3 may determine a first transmission
beamforming vector based on the interference experienced by a mobile
station that is attributed to the base station BS1 (at an even time).
The base station BS3 may determine a second transmission
beamforming vector based on the interference experienced by the
mobile station that is attributed to the base station BS5 (at an odd
time).
If TDD is not used, then the base station implements frequency
partitioning for FDD at S635. At S635, the serving base station
determines first and second frequencies to at which to transmit
information. At S640, the serving base station determines first and
second interference beams (e.g., interference channel information)
from first and second interfering base stations.
Once the first and second interference beams are determined, the
serving base station determines first and second transmission
beamforming vectors based on the first and second interference
beams, respectively, at S645. The first and second transmission
beamforming vectors are determined to directly conflict with the first
and second interference beams, respectively, as illustrated in FIGS. 6A
and 6B and described with reference to FIGS. 6A and 6B. The first
and second transmission beamforming vectors are determined by the
serving base station using the method of FIGS. 3A and 3B.
For example, the base station BS3 may determine a first transmission
beamforming vector based on the interference experienced by a mobile
station that is attributed to the base station BS 1 (at a first frequency) .
The base station BS3 may determine a second transmission
beamforming vector based on the interference experienced by the
mobile station that is attributed to the base station BS5 (at a second
frequency) .
At S650, the serving base station transmits information at first and
second frequencies using the first and second transmission
beamforming vectors, respectively. The serving base station may
return to S640 periodically, continuously or if an event occurs.
While TDD and FDD are described and illustrated, it should be
understood that example embodiments are not limited to FDD and
TDD.
FIG. 7 illustrates the base station BSl including a transmitter
according to an example embodiment. While a transmitter 700 is
illustrated as being implemented in the base station BSl, it should be
understood that the transmitter 700 may be included in all base
stations and mobile stations.
As shown, the base station BSl includes the transmitter 700
configured to receive data from a data generator 790. It should be
understood that the base station BSl shown in FIG. 7 is merely for
illustrative purposes and that the base station BS1 may include
additional features not shown in FIG. 7.
The data generator 790 is connected to a channel code/ interleaver
705 of the transmitter 700. The transmitter 700 further includes an
MCS (modulation and coding scheme) controller 7 10, a modulator
7 15, a transmission beamformer 720, a beamforming vector controller
725, a channel information/ control information processor 730 and a
plurality of transmission antennas 750_0 - 750_K.
The MCS controller 7 10 is configured to output MCS data to the
channel codec/ interleaver 705 and the modulator 7 15 based on an
output received from the channel information/ control information
processor 730. The channel information/ control information
processor 730 receives feedback data from the plurality of
transmission antennas 750_0-750_K as well as channel
information/ control information from other base stations and mobile
stations.
The channel code/ interleaver 705, MCS controller 7 10, modulator
7 15, channel information/ control information processor 730 and
plurality of transmission antennas 750_0 - 750_K are known, and
therefore, a further description of these features is omitted.
The beamforming vector controller 725 is configured to receive
channel information/ control information from the channel
information/ control information processor 730. For example, the
beamforming vector controller 725 may receive quantized estimated
channel information matrices RHk and RGk from a mobile station being
served by the base station BS1 via the channel information/ control
information processor 730. Based on the quantized estimated
channel information matrices RHk and RGk , the beamforming vector
controller 725 is configured to implement the method of FIGS. 3A and
3B and determine a transmission beamforming vector.
The beamforming vector controller 725 inputs the transmission
beamforming vector to the transmission beamformer 720. The
transmission beamformer 720 is configured to transmit signals using
the transmission beamforming vector.
FIG. 8 illustrates a receiver the mobile station MSI including a
receiver according to an example embodiment. While a receiver 800 is
illustrated as being implemented in the mobile station MSI, it should
be understood that the receiver 800 may be included in all base
stations and mobile stations.
As shown, the mobile station MSI includes the receiver 800
configured to input data to a controller 890. It should be understood
that the mobile station MSI shown in FIG. 8 is merely for illustrative
purposes and that the mobile station MSI may include additional
features not shown in FIG. 8.
The receiver 800 includes a beamforming vector controller 805, a
receiver beamformer 8 10, a demodulator 8 15, a deinterleaver/ channel
decodec 820, a channel estimator/ quantizer 825 and a plurality of
receiving antennas 830_0-830_N.
The receive beamformer 8 10 receives outputs from the beamforming
vector controller 805 and the channel estimator/ quantizer 825. The
receive beamformer 8 10 outputs data to the demodulator 8 15. The
demodulator receives the data from the receive beamformer 8 10 and
outputs demodulated data to the deinterleaver/ channel decodec 820.
Based on the demodulated data, the deinterleaver/ channel decodec
820 outputs data to the controller 890.
The demodulator 8 15 and deinterleaver/ channel decodec 820 are
known in the art, and therefore, a further description of these features
is omitted.
The channel estimator/ quantizer 825 is configured to receive signals
from the plurality of receiving antennas 830_0-830_N. The channel
estimator 825 determines quantized estimated channel information
matrices RHk and RGk based on the signals received from the plurality
of receiving antennas 830_0-830_N. The channel estimator/ quantizer
825 feedbacks to a serving base station the quantized estimated
channel information matrices RHk and RGk .
The beamforming vector controller 805 determines the receive
beamforming vector based on the quantized estimated channel
information matrices RHk and RGk .
As described, example embodiments disclose apparatuses and
methods for reducing interference between mobile stations (users) in a
system having base stations and mobile stations that include multiple
antennas while limiting feedback from a mobile station to a base
station or vice versa.
Example embodiments being thus described, it will be obvious that
the same may be varied in many ways. For example, each base
station and mobile station may have any number of antennas. Such
variations are not to be regarded as a departure from the spirit and
scope of example embodiments, and all such modifications as would
be obvious to one skilled in the art are intended to be included within
the scope of the claims.
CLAIMS
What is claimed is:
1. A method of reducing interference in a communication system
(200), the method comprising:
receiving, by a transmitter (700) having multiple antennas
(750_0-750_K), first and second quantized matrices, the first
quantized matrix being based on an estimated channel matrix, and
the second quantized matrix being based on an estimated interference
matrix, the estimated channel matrix estimating a receive channel
matrix between the transmitter (700) and a receiver (800), and the
estimated interference matrix estimating interference caused by at
least one other transmitter (BS2) at the receiver (800); and
determining, by the transmitter (700), a transmission
beamforming vector based on the first and second quantized matrices.
2. The method of claim 1, wherein
the transmitter (700) is in a base station (BS1), and
the determining determines a transmission beamforming vector
without receiving information from other base stations (BS2).
3. The method of claim 1, wherein
the transmitter (700) is in a base station (BS1), and
the determining determines a transmission beamforming vector
based only on information received from a mobile station (MSI) served
by the base station (BS1), the information including the first and
second quantized matrices.
4. A method of reducing interference in a communication system
(200), the method comprising:
first determining, by a receiver (800) having multiple antennas
(830_0-830_N), a quantized estimated channel matrix and a quantized
estimated interference matrix, the quantized estimated channel matrix
being based on an estimated channel matrix, and the quantized
estimated interference matrix being based on an estimated
interference matrix, the estimated channel matrix estimating a receive
channel matrix between a transmitter (700) and the receiver (800),
and the estimated interference matrix estimating interference caused
by at least one other transmitter (BS2) at the receiver (800); and
second determining, by the receiver (800), a receive
beamforming vector based on the first determining.
5. The method of claim 4, wherein the first determining determines a
quantized estimated channel matrix and a quantized estimated
interference matrix based on at least one of scalar quantization and
vector quantization.
6. The method of claim 4, wherein the first determining determines a
quantized estimated channel matrix by
wherein RH is the quantized estimated channel matrix and H is the
estimated channel matrix.
7. The method of claim 6, wherein the first determining determines a
quantized estimated channel matrix based on a number of receiving
antennas (830_0-830_N) included in the receiver (800).
8. The method of claim 6, wherein the first determining determines a
quantized estimated channel matrix based on at least another
transmitter (BS2) in the communication system (200).
9. The method of claim 4, wherein the first determining determines a
quantized estimated interference matrix by
wherein RG is the quantized estimated interference matrix and G is
the estimated interference channel matrix.
10. A method of reducing interference in a communication system
(200), the method comprising:
first determining, by a transmitter (700), an interfering beam of
an interfering transmitter (BS3); and
second determining, by the transmitter (700), a transmission
beamforming vector such that a beam from the transmitter (700)
conflicts with the interfering beam at a first time.