TECHNICAL FIELD
The present invention pertains to a heterogeneous wireless communication network, and
more particularly, to a system and method for scheduling and mitigating cross-cell
interference in such a network.
BACKGROUND
Next generation cellular networks are expected to be characterized by their extreme density.
The current paradigm of having isolated cells (less than 4% overlap) operated by a single,
centrally placed cell tower, equipped with dedicated spectrum and isolated from its
neighbours by guard bands, will be replaced by a dense network of Distributed Antenna
Systems and Remote Radio Heads (hereinafter referred as RRH/‘network nodes’),
coordinating with each other to share a large coverage region using a shared frequency band.
Thus, the new paradigm offers unprecedented benefits, in terms of instantaneous throughput,
energy conservation and edge-of-cell performance. However, it will also have enormous
associated challenges with respect to user scheduling and spectrum sharing; especially in
cross-node interference.
Heterogenous networks are one such type of network existing in new paradigm. They consist
of a mix of macro and pico/femto base stations or small-cells operating in close proximity.
Recent innovations in the area of inter-cell association allow these nodes to coordinate
closely with each other in real-time to increase system capacity and user service. As networks
become more and more squeezed and the reuse distance drops, network operators have
demanded additional tools to manage the interference load which limits system performance,
especially at the cell edge. In response, the 3GPP has standardized a number of mechanisms
for achieving this under the term Inter-cell Interference Coordination (ICIC), followed by
enhanced (elCIC) and further enhanced ICIC.
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Figure 1 illustrates Inter-cell Interference Coordination (ICIC) deployment for heterogeneous
networks. The network comprises of one macro-cell and several small-cells. Each small-cell
shares a common frequency with the macro-cell. There are users in the boundary zone
between the macro-cell and any given small-cell, which can receive wireless transmissions
either from the macro-cell or by the small-cell. Particular users will be scheduled to use the
small-cell and others will be scheduled to use the macro-cell. Since the macro is resource
limited, it would like to let the small-cell handle as many users as possible. The small-cells,
on the other hand are power limited. Thus, small cells are not able to interfere with each
other, but each small-cell can and does interfere with (and are subject to interference from)
the macro-cell.
At each point of time, the macro-cell and the small-cell have to schedule transmissions to the
UEs associated with each of them. If the macro-cell and the small-cell transmit on the same
resource in the same time-slot, there will be interference.
In the standard ICIC/eICIC scenario, the macro-cell will coordinate with the small-cells by
creating dedicated time-gaps, called ABS (Almost Blank Subframes) or RBS (Reduced
Power Subframes) where the macro-cell either transmits no data or backs-off its transmit
power significantly. This gives an opportunity for the small-cells to transmit. However, in
these frames the UEs scheduled to the macro do not get data, and in the other sub-frames, it is
the UEs scheduled with the small-cells which do not receive data. The ABS/RBS frames
count as loss of capacity to the macro-cells (though the capacity saved in one sector could
potentially be used in other sectors or destinations).
Coordinated Multipoint (COMP) is a technology based on the ability for multiple endpoints
to coordinate as part of a common MIMO (Multiple-Input and Multiple-Output) transmission.
The efficiency of MIMO is increased when the number of antennae used are larger and the
spatial separation is high. When multiple transmitters or receivers coordinate implicitly or
explicitly with each other (using, for example, opportunistic scheduling) in order to use
multi-user MIMO, this becomes a case of Coordinated Multipoint (CoMP). Theoretically
CoMP can achieve significant gains in throughput by utilizing the statistical diversity of the
wireless channels. In reality, there are significant challenges in terms of inter-node
coordination.
4
Figure 2 shows different forms of multi-user MIMO transmission using Coordinated
Multipoint such as Broadcast transmission and Joint Transmission. In Joint Transmission,
where one cell (either the macro-cell or the small-cell) could simultaneously transmit to
multiple UEs.
In Figure 3, shows an urban network deployment comprising one macro-cell and several
small-cells. In one possible scheme, a pair of the UEs (ues and uem) are treated as a single unit
and, based on their measured/reported channel characteristics, the macro-cell decides whether
they should be broadcast from the small-cell or itself. This determination could be done for
all the UEs which are eligible, on a pair by pair basis. This scheme has the downside of
leaving some small cells idle, but has the upside that it mitigates the inter-cell interference, as
described below. The problem is that from any given network node, the individual members
of the targeted UEs will have different channel conditions, so it will be hard to implement
scheduling in a fair yet efficient manner.
In another scheme, which address similar problems include Block diagonalization (BD or
zero-forming). Block diagonalization is a technique allows a single transmitter to transmit to
multiple receivers simultaneously, without cross-receiver interference. The fundamental principle
of BD is to choose orthogonal pre-coding matrices, effectively making each receivers
data stream invisible to the others. However, in the case of block-diagonalization,
orthogonalization is achieved by choosing a pre-coding matrix which is orthonormal to the
co-resident UEs; it does not take the target UEs channel matrix into account. Further, BD is
unable to utilize additional antenna (Nt > Nr). This means that is unable to utilize modern
networks with RRH and massive-MIMO capabilities.
Hence, there is a need to have a system and method that can overcome the above stated
problems and provides a system and method with enhanced scheduling and simultaneously
maximizing network capacity and mitigating cross-cell interference.
SUMMARY
The following presents a simplified summary of the subject matter in order to provide a basic
understanding of some aspects of subject matter embodiments. This summary is not an
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extensive overview of the subject matter. It is not intended to identify key/critical elements of
the embodiments or to delineate the scope of the subject matter.
Its sole purpose is to present some concepts of the subject matter in a simplified form as a
prelude to the more detailed description that is presented later.
It is therefore a primary objective of this invention to provide a system and method for
mitigating cross-cell interference in heterogeneous networks using shared resources.
It is another objective of the present invention is to provide enhanced scheduling and
simultaneously maximizing network capacity.
According to the preferred embodiment, two or more network nodes of a heterogeneous
network with overlapping coverage regions, simultaneously transmit to a set of UEs attached
to them in a manner so as to mitigate cross-cell interference by using a joint encoding
technique. The scheme is designed so that the UEs can operate independently of each other,
as can the network nodes.
In another embodiment, the present invention provides a system for scheduling and
mitigating cross-cell interference, said system comprising a plurality of N network nodes,
each having a baseband processor and a transmit antenna Nt , capable of handling multiple
input multiple output (MIMO) channels, communicatively coupled with a plurality of K coresidents
user equipment (UEs); a central scheduler configured to control scheduling of said
plurality of network nodes; wherein each network node is configured to select a plurality of
UEs and provide the shortlisted UEs to the central scheduler; the central scheduler in turn
identifies a target set of UEs and the co-residents for each network node; and the network
node is configured to pre-select signal-to-noise power to the target UEs without impacting
transmission of co-residents UEs.
In another embodiment, the central scheduler identifies the target set of UEs based on
orthogonality of the UE’s channel matrix against those previously present in each nodes
target-set.
6
In another embodiment, the central scheduler is configured to receive transmission
parameters from specific UEs. The transmission parameters comprises channel capacity
information for each of the plurality of co-located UEs and power constraint information at
each of the network nodes.
In another embodiment, the network node pre-selects transmission power to the target UEs by
implementing pre-coding matrix. The pre-coding matrix is a linear matrix operation which
simultaneously separates the channels of the member UEs of the target set.
In another embodiment, the present invention provides a method for scheduling and
mitigating cross-cell interference, said method comprising controlling scheduling, by a
central scheduler, of a plurality of N network nodes, each having a baseband processor and a
transmit antenna Nt, and each network node is capable of handling multiple input multiple
output (MIMO) channels, communicatively coupled with a plurality of K co-residents user
equipment (UEs); selecting, by each network node, a plurality of UEs and provide the
shortlist UEs to the central scheduler; identifying, by the central scheduler, a target set of
UEs and the co-residents for each network node based on the shortlisted UEs provided by the
network node; and pre-selecting, by the network node, signal-to-noise power for the target
UEs without impacting transmission of co-residents UEs.
In another embodiment, the method of scheduling comprising sorting the list of all visible
UEs in ascending order of the number of nodes; adding UEs to the target set of that node only
visible to one node; determining UEs visible to multiple nodes which have to be selected to
the node which they will be targeted to; and checking the orthogonality of the UE’s channel
matrix against those already present in each nodes target-set.
These and other objects, embodiments and advantages of the present invention will become
readily apparent to those skilled in the art from the following detailed description of the
embodiments having reference to the attached figures, the invention not being limited to any
particular embodiments disclosed.
7
Brief Description of the Drawings
For a better understanding of the embodiments of the systems and methods described herein,
and to show more clearly how they may be carried into effect, reference will now be made,
by way of example, to the accompanying drawings, wherein:
FIGURE 1 illustrates Inter-cell Interference Coordination (ICIC) deployment for
heterogeneous networks.
FIGURE 2 shows different forms of multi-user MIMO transmission using Coordinated
Multipoint in accordance with a state-of-the-art.
FIGURE 3 shows an urban network deployment comprising one macro-cell and several
small-cells in accordance with the known art.
FIGURE 4 depicts a distributed radio architecture with a plurality of network nodes and a
central scheduler according to the present invention.
FIGURE 5 illustrates a scheduling operation by the central scheduler in accordance with
the present invention.
FIGURE 6 shows simulation results for relative channel capacity for ANF and BD
techniques according to the present invention.
FIGURE 7 shows simulation results for relative symbol error rates for ANF and BD
techniques according to the present invention.
DESCRIPTION
Exemplary embodiments will now be described with reference to the accompanying
drawings. The invention may, however, be embodied in many different forms and should not
be construed as limited to the embodiments set forth herein; rather, these embodiments are
provided so that this invention will be thorough and complete, and will fully convey its scope
to those skilled in the art. The terminology used in the detailed description of the particular
8
exemplary embodiments illustrated in the accompanying drawings is not intended to be
limiting. In the drawings, like numbers refer to like elements.
The specification may refer to “an”, “one” or “some” embodiment(s) in several locations.
This does not necessarily imply that each such reference is to the same embodiment(s), or
that the feature only applies to a single embodiment. Single features of different
embodiments may also be combined to provide other embodiments.
As used herein, the singular forms “a”, “an” and “the” are intended to include the plural
forms as well, unless expressly stated otherwise. It will be further understood that the terms
“includes”, “comprises”, “including” and/or “comprising” when used in this specification,
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 will be
understood that when an element is referred to as being “connected” or “coupled” to another
element, it can be directly connected or coupled to the other element or intervening elements
may be present. Furthermore, “connected” or “coupled” as used herein may include
operatively connected or coupled. As used herein, the term “and/or” includes any and all
combinations and arrangements of one or more of the associated listed items.
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
this invention pertains. It will be further understood that terms, such as 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.
The figures depict a simplified structure only showing some elements and functional entities,
all being logical units whose implementation may differ from what is shown. The
connections shown are logical connections; the actual physical connections may be different.
It is apparent to a person skilled in the art that the structure may also comprise other
functions and structures.
9
Also, all logical units described and depicted in the figures include the software and/or
hardware components required for the unit to function. Further, each unit may comprise
within itself one or more components which are implicitly understood. These components
may be operatively coupled to each other and be configured to communicate with each other
to perform the function of the said unit.
The features provided by the disclosed system in the present invention, may be accessed
remotely, in one or more embodiments, and/or through an online service provider. Such types
of online service providers operates and maintains the computing systems and environment,
such as server system and architectures, that promote the delivery of portable electronic
documents in a communication network. Typically, server architecture includes the
infrastructure (e.g. hardware, software, and communication lines) that offers online services.
The detailed description follows in parts to terms of processes and symbolic representations of
operations performed by conventional computers, including computer components. For the
purpose of this invention, a computer may be any microprocessor or processor (hereinafter
referred to as processor) controlled device such as, by way of example, personal computers,
workstations, servers, clients, minicomputers, main-frame computers, laptop computers, a
network of one or more computers, mobile computers, portable computers, handheld
computers, palm top computers, set-top boxes for a TV, interactive televisions, interactive
kiosks, personal digital assistants, interactive wireless devices, mobile browsers, or any
combination thereof.
For the most part, the operations described herein are operations performed by a computer or
a machine in conjunction with a human operator or user that interacts with the computer or the
machine. The programs, modules, processes, methods, and the like, described herein are but
an exemplary implementation and are not related, or limited, to any particular computer,
apparatus, or computer language. Rather, various types of general purpose computing
machines or devices may be used with programs constructed in accordance with the teachings
described herein.
It would be well appreciated by persons skilled in the art that the term “module” and “unit”
can be interchangeably used in the present invention.
10
Figure 4 depicts a distributed radio architecture with a plurality of network nodes and a
central scheduler according to the present invention. The network nodes (401a, 401b…
401n) are scattered over a geographical area, which is deemed a cell. Like the traditional
concept of a cell, it is allocated a certain amount of spectrum and a certain overall power,
which it uses for providing service to the users (users equipped with terminal equipment,
hence UE) in the area. The network nodes are connected to a central scheduler or base-band
unit (402), which provides common services (such as control signaling and packet routing to
the network core). It will be well appreciated by a person skilled in the art that it also
provides a vital scheduling and coordination function.
Further, each network node has a number of transmit antennae Nt, each UE has a number of
transmit antennae Nr and thereby, Nt = Nr * (K+1). K is a number (typically between 2 and
6) which corresponds to the expected number of UEs to be provided service by one network
node, at one time.
When a network node transmits to a given UE, it selects a transmission method and precoding
technique so as to maximize the signal strength and minimize the inter-stream
interference for that UE, as per the well-known methodology of MIMO pre-coding. However,
any other UE in the vicinity will also receive this transmission. If the other UE is
simultaneously receiving a transmission from another network node, then the former is
treated as noise. It is well known that this inter-node interference forms a limiting factor for
this kind of network.
In accordance with the present invention, the central scheduler (402) identifies a target set of
UEs for scheduling and co-resident UEs for each network node.
The UEs are selected based on a bidding mechanism, where individual network nodes
shortlist UEs for scheduling and present this to the central scheduler. The central scheduler
(402) in turn identifies the target UEs and the co-residents for each network node. In the next
step, the network node uses a specific algorithm to pre-code the transmission to the target set
of UEs so as to maximize their signal to noise power and simultaneously minimize the impact
on the co-resident UEs.
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In addition to the above, distributed pre-coding mechanism, the central scheduler executes the
scheduling by identifying the UEs which each network node has to transmit. Each UE which
is visible to a network node and not part of the transmit set must either be not scheduled in
this iteration, or has to be added to this UEs co-resident set. The algorithm used for precoding
works best if the channel matrices for the co-resident and target sets are as
independent (in a vector space sense) from each other as possible; this also holds true for the
members of the target sets themselves.
Each network node, at each instant, has to simultaneously transmit to a number of UEs,
known as the target set. The target set is provided by the central scheduler as the output of the
scheduling exercise. Along with the target set, each network node has a set of UEs known as
the co-resident set; these are the UEs which shall be receiving data from other network nodes
at the same time-instant. Hence, the network node must endeavor to provide service to its
target set in a manner so as to minimize the interference that it generates to each member of
the co-resident step. The network node implements this by appropriately pre-coding the
transmission. The pre-coding is a linear matrix operation which simultaneously separates the
channels of the members of the target set and also minimizes the interference for the coresident
steps. The pre-coding is implemented using standard matrix operations (singular
value decomposition, block Cholesky decomposition and finally inversion of an upper
triangular matrix) followed by Tomlinson Harashima pre-coding of the transmit vector so as
to pre-subtract anticipated interference.
Figure 5 illustrates a scheduling operation by the central scheduler in accordance with the
present invention. In step 501, sorting the list of all visible UEs (as reported by all network
nodes) in ascending order of the number of nodes reporting to them. In step 502, adding UEs
to the target set of that node only visible to one node. In step 503, determining UEs visible to
multiple nodes which have to be selected to the node which they will be targeted to. In step
504, checking. By the scheduler, the orthogonality of the UE’s channel matrix against those
already present in each nodes target-set. The least orthogonal node (subject to a minimum)
must accept this UE in the target set.
In an exemplary embodiment of the present invention, two individual transmitters are
considered which has to transmit data to K receivers each. The transmitters have to make sure
that the cross-user interference is minimized. The transmitter is deemed to have Nt =KNr
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transmit antennae and each of the K receivers will have Nr receive antennae. The description
below is for K=2, but can be modified for higher values of K as shall be shown subsequently.
Each transmitter orders the UEs as UE1 and UE2, with channel matrices H1 and H2
respectively. Each transmitter has Nt = 2 * Nr antennae for transmitting whereas each receiver
has Nr antennae. Thus, each channel matrix is an NrxNt matrix. Each transmitter transmits to
its intended UE a stream xi pre-coded using an Nt xNt pre-coding matrix Fi. The composite
channel matrix as seen by the ith transmitter to be Hi = [Hi ,1 Hi,2]T.
Further, each channel matrix Hi is a 2x4 matrix [Hi,k Hi,k], where Hi, k+p is the 1xNt matrix
corresponding to the path between to the ith antenna of the kth receiver.,
H = = (1)
The method works by expressing the complex hermitian matrix HHH into three matrices, with
the first one being lower triangular, the next one being block diagonal and the third one being
a conjugate transpose of the first matrix. Taking the original form of H as in (1), the
decomposed form the matrix is obtained as in (2).
HHH =
= (I+ DHUH) (I+DU)
Where,
U = , =
1 = H1H1
H
D = (H1H2
H)
2 = (H2H2
H - DH 1D) (2)
The transmitter uses a pre-coding matrix F as given in (3),
F = HH (I-DU)
= (3)
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Where, 1 2 are NrxNr power loading matrices selected by the transmitter. The received
signal is given by (4), where
Y = HFx + n
= HHH (I- DU) + n
= (I+ DHUH)
=
K = 2
-1DH 1
1 (4)
Thus, the common channel is effectively divided into two separate channels, with effective
channel matrix Heff,m = m m . From equation 4, we can see that the transmit stream to UE1
is interference-free and has the same effective channel matrix as if the second UE did not
exist. On the other hand, the stream to UE2 has an interference term Kx1, plus a reduced
effective channel matrix H2 - , where comes from the SVD (Singular Value
Decomposition) of the Hermitian matrix DH 1 D. The interference can now be presubtracted
using Tomlinson Harashima pre-coding or more expensive lattice coding methods.
Thereby, nearly interference free transmission to both UEs is achieved.
The loss of channel power to UE2 can be made up to an extent by adjusting the power loading
matrix 2 at the expense of UE1. The choice of the power loading matrix , must be so as to
maximize the channel capacity for both UE1 and UE2, while meeting the transmission power
constraint. In this case, the transmission power constraint can be written as: HH
Tr(FFH) = Tr ((HH(I- DU) )(HH ( I - DU) )H)
= Tr ((I- DU) HH ( I - DU) H)
= Tr ( H) (5)
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In the same way, the abovementioned broadcast technique can be modified for an
embodiment of Active null-forming (ANF), where the network node does not have direct
knowledge of the channel matrix Hi, but operates on the basis of the feedback of the
individual UEs. The individual matrices for the two UEs can be written in the form
Hi = Ui [ ] [Vi Ṽi ]H (6)
where Vi , Ṽi are each a matrix of the form [v1 v2] mutually orthonormal column vectors
corresponding to the positive and zero eigenvalues of Hi . For any feedback based pre-coding
scheme, the UEs will report the matrix V to the network node (or the closest member of V
from a pre-selected code-book) and the network node will use a pre-coding matrix VH. Since,
Hi is a 2x4 matrix, it will a maximum of two positive eigenvalues.
=
= VH (7)
Further, it is to be noted that V11, V12 are the mutually orthonormal rows from the SVD of the
channel matrix H1 corresponding to the first receiver and V21, are mutually orthonormal
column vectors from the second channel matrix. However, the vectors from the first set are
not orthonormal with the second, i.e. V1j
H V2, k , j, k (1,2) 0. Indeed, this is the source of
interference between the two streams. Hence,
VHV =
Vc =
If the two channels are uncorrelated, the terms in Vc to be independent variables with mean 0
and fixed variance. Vc is small, because its absolute eigenvalues are much less than 1. It is
clear that the worst case is when Vc = I . In this case, the interference between the two
channels is maximum.
Therefore, VHV can be rewritten as,
VHV = (I+DHUH) (I + DU) (8)

Combining with equation (7),
= I, D = Vc, = (I - DHD) (9)
Now, choosing a precoding matrix as F =V (I-DU) and the transmit signal is expressed as,
y = HFx + n = U VHV(I-DU) x + n
= U(1 + DHUH) x + n
= U [x1 x2]T
= U ]T (10)
K = ( -1
Minimum interference for UE2 is achieved by choosing so that || ||
is minimized in (10). The constraint is that || || || ||. In general, when the two paths are
independent of each other, D 0, and K DH . The equality is achieved by adjusting the
power loading factors Tr and Tr , such that ||D || || || and x2 = - x1. The individual
elements of can be chosen by the water-filling model so as to further optimize the SNR
for UE1, whereas the individual elements of are chosen to balance the amplitudes of the
components of x2. Effectively, the transmitter diverts a fraction of the available energy to
create a deliberate null at the co-resident UE, without sacrificing the optimal pre-coding
matrix for the targeted UE.
As our simulations show in Figure 5 and Figure 6, the method as per the present invention
significantly out-perform the BD technique, especially when the different channels are
independent and hence det(D) is relatively small. The difference between the capacities of
the two techniques are explained by considering the relative SER achieved by the two
methods i.e. Active null forming (ANF) and Block Diagonalization (BD) techniques. Even
for good values of SNR, the SER for the BD case is purely dictated by the relative
independence of the eigenspace of the two channel matrices. On the other hand, the precoding
approach has a performance which improves steadily as the SINR (signal-to-noiseplus-
interference ratio) improves.

The situations where the BD based zero-forming technique can match the ANF technique are
where the two channel matrices are relative correlated, so that D I. In this situation, the cell
can switch between the ANF technique and the BD techniques flexibly, based on the value of
D. Due to UE specific reference signals, no explicit signaling is required to switch between
the two approaches.
The solution described above can be directly extended to multiple co-resident UEs alongside
a single target UE. The network node has Nt transmit antennae with several UEs in its
immediate range. At each transmit opportunity, it receives channel state information
implicitly (through uplink reference signals in TDD mode) or explicitly {feedback on a
shared data channel (PUSCH) in FDD mode}. It uses this feedback to choose one UE as the
target for transmitting data. It then uses the CSI (channel state information) of the other UEs
to code the transmission in such a way so as to minimize interference for all the others. The
ith UE has an antenna count of Ni < Nt. Considering, the number of antenna available to the
target UE as Nr and the total number of antennae for all the other UEs as Nu = i Ni - Nr.
The channel matrix between the network node and the ith UE is given as Hi.
Each channel matrix Hi has a singular value decomposition Ui iV*, where Ui,Vi are
orthonormal matrices (their columns are mutually orthonormal) and Zi is a diagonal matrix.
Since Hi is a matrix with more rows than columns, the SVD actually looks like
Hi = Ui [ I 0] [Vi i]*
The transmitting network node uses a pre-coding matrix of the form
F = [Vr W ]
where, Vr is the sub-matrix of Vi corresponding to the non-null eigenvalues and Λ is a NrxNr
matrix of full rank. The matrix D is given by D = Vr
H W(ΛH)-1. The pre-coding matrix F is
then applied on a transmit vector [x ]T, where x is the vector of Nr symbols (postmodulation)
to be transmitted to the target UE. The matrices W, Λ and the vector of size Nt
- Nr is chosen so as to minimize interference, while honouring the transmit power constraint
≤ . This can be done using many methods; including but not limited to barrier
optimization, Tikhonov regularization, ridge regression and other similar techniques.

In an advantageous embodiment, the disclosed methodology according to the present
invention provides an improved Inter-cell Interference Coordination, where two network
nodes with overlapping coverage regions simultaneously transmit to UEs attached to them,
and coordinate so as to not cause cross-cell interference.
The present invention is applicable to all types of on-chip and off chip memories used in
various in digital electronic circuitry, or in hardware, firmware, or in computer hardware,
firmware, software, or in combination thereof. Apparatus of the invention can be
implemented in a computer program product tangibly embodied in a machine-readable
storage device for execution by a programmable processor; and methods actions can be
performed by a programmable processor executing a program of instructions to perform
functions of the invention by operating on input data and generating output. The invention
can be implemented advantageously on a programmable system including at least one input
device, and at least one output device. Each computer program can be implemented in a highlevel
procedural or object-oriented programming language or in assembly or machine
language, if desired; and in any case, the language can be a compiled or interpreted language.
Suitable processors include, by way of example, both general and specific microprocessors.
Generally, a processor will receive instructions and data from a read-only memory and/or a
random access memory. Generally, a computer will include one or more mass storage devices
for storing data file; such devices include magnetic disks and cards, such as internal hard
disks, and removable disks and cards; magneto-optical disks; and optical disks. Storage
devices suitable for tangibly embodying computer program instructions and data include all
forms of volatile and non-volatile memory, including by way of example semiconductor
memory devices, such as EPROM, EEPROM, and flash memory devices; magnetic disks
such as internal hard disks and removable disks; magneto-optical disks; CD-ROM and DVDROM
disks; and buffer circuits such as latches and/or flip flops. Any of the foregoing can be
supplemented by, or incorporated in ASICs (application-specific integrated circuits), FPGAs
(field-programmable gate arrays) and/or DSPs) digital signal processors).
It will be apparent to those having ordinary skill in this art that various modifications and
variations may be made to the embodiments disclosed herein, consistent with the present
invention, without departing from the spirit and scope of the present invention. Other embodiments consistent with the present invention will become apparent from consideration of the specification and the practice of the description disclosed herein.

We claim:
1. A system for scheduling and mitigating cross-cell interference, said system
comprising:
- a plurality of N network nodes, each having a baseband processor and a transmit
antenna Nt , capable of handling multiple input multiple output (MIMO) channels,
communicatively coupled with a plurality of K co-residents user equipment
(UEs);
- a central scheduler configured to control scheduling of said plurality of network
nodes;
wherein each network node is configured to select a plurality of UEs and provide
the shortlisted UEs to the central scheduler;
the central scheduler in turn identifies a target set of UEs and the co-residents for
each network node; and
the network node is configured to pre-select signal-to-noise power to the target
UEs without impacting transmission of co-residents UEs.
2. The system as claimed in claim 1, wherein the central scheduler identifies the target
set of UEs based on orthogonality of the UE’s channel matrix against those previously
present in each nodes target-set.
3. The system as claimed in claim 1, wherein the central scheduler is configured to
receive transmission parameters from specific UEs.
4. The system as claimed in claim 3, wherein said transmission parameters comprises
channel capacity information for each of the plurality of co-located UEs and power
constraint information at each of the network nodes.

5. The system as claimed in claim 1, wherein the network node pre-selects transmission
power to the target UEs by implementing pre-coding matrix.
6. The system as claimed in claim 5, wherein the pre-coding matrix is a linear matrix
operation which simultaneously separates the channels of the member UEs of the
target set.
7. A method for scheduling and mitigating cross-cell interference, said method
comprising:
- controlling scheduling, by a central scheduler, of a plurality of N network nodes,
each having a baseband processor and a transmit antenna Nt, and each network
node is capable of handling multiple input multiple output (MIMO) channels,
communicatively coupled with a plurality of K co-residents user equipment
(UEs);
- selecting, by each network node, a plurality of UEs and provide the shortlist UEs
to the central scheduler;
- identifying, by the central scheduler, a target set of UEs and the co-residents for
each network node based on the shortlisted UEs provided by the network node;
and
- pre-selecting, by the network node, signal-to-noise power for the target UEs
without impacting transmission of co-residents UEs.
8. The method as claimed in claim 7, wherein the method comprises identifying, by the
central scheduler, the target set of UEs based on orthogonality of the UE’s channel
matrix against those previously present in each nodes target-set.
9. The method as claimed in claim 7, wherein the central scheduler is configured to
receive transmission parameters from specific UEs.

10. The method as claimed in claim 9, wherein said transmission parameters comprises
channel capacity information for each of the plurality of co-located UEs and power
constraint information at each of the network nodes.
11. The system as claimed in claim 7, wherein pre-selecting signal-to-noise power to the
target UEs is by implementing pre-coding matrix.
12. The method as claimed in claim 11, wherein the pre-coding matrix is a linear matrix
operation which simultaneously separates the channels of the member UEs of the
target set.
13. The method as claimed in claim 7, wherein the scheduling comprises:
- sorting the list of all visible UEs in ascending order of the number of nodes;
- adding UEs to the target set of that node only visible to one node;
- determining UEs visible to multiple nodes which have to be selected to the node
which they will be targeted to; and
- checking, the orthogonality of the UE’s channel matrix against those already
present in each nodes target-set.