Embodiments of the invention relate to the field of wireless cellular networks, like multi-cell MIMO communications networks (MIMO=Multiple Input Multiple Output). More specifically, embodiments of the invention relate to a method for determining for a plurality of users of a wireless cellular network those transmitters used for determining candidate rate configurations for serving the users. Further embodiments concern a wireless cellular network as well as a transmitter and a network controller for such a wireless cellular network.
When considering efficient operation of a wireless cellular network comprising transmitters that may serve multiple users on the same resource block, for example on the same frequency, interference among users served by the same transmitter can be coordinated optimally. For example, the spatial degrees of freedom offered by multiple antenna techniques may be used to establish orthogonality so that inter-cell interference may be the main diminishing effect on the performance of the network. This is depicted schematically in
To efficiently manage inter-cell interference, a common approach is “fractional reuse” (FR). In accordance with this approach users at a cell-edge are served in protected resource blocks that are not available for the most dominant interferers. However, due to fading, the transmitters that cause the main interference are also potential candidates for being the serving transmitter.
A further known approach is “dynamical cell selection” (DCS) which is a technique to gain from cell selection diversity by reassigning users in a fast time scale. Additionally, DCS allows to reassign users to perform load balancing leading to more efficient resource utilization.
In the following, the downlink of a cellular network will be considered, wherein the cellular network comprises a set of transmitter arrays T,T=|T| and a set of users K,K=|K| distributed throughout the covered area. Multiple transmit arrays, typically three or six, may be mounted on the same site to form sectors, by using fixed and predefined antenna patterns. For each user k a set of transmitters Tk is assumed from which a user may receive and decode a reference signal. For every transmitter in the set Tk the user calculates a scalar indicator ukt of the long-term average quality, for example, the “Reference Signal Received Quality” (RSRQ) in LTE. The transmitters in the set Tk represent suitable candidates to send data to the user k, but also represent the most dominant interferers. Every user is served with a certain transmission weight that is described by the rate vector r=[r1, . . . , rK]1εR+K. The user's rates rεR⊂R+K are coupled by shared resources and interference and are universally modeled by an achievable rate region R. A utility U(r) measures the system performance by mapping the rate vector to a real number, i.e U:R+K→R. One known example for this is the network-wide proportional fairness as described in F. P. Kelly, A. K. Maulloo, and D. K. H. Tan, “Rate control for communication networks: shadow prices, proportional fairness and stability,” Journal of the Operational Research Society, vol. 49, no. 3, pp. 237-252, 1998.
An efficient operating point of the network is given by the solution of the following optimization problem:
A frequency reuse of one is desired to achieve data rates that are necessitated in accordance with specifications of present and future networks (e.g. future networks will provide a large variety of services). However, in a network with universal reuse the cell-edge users might be excluded from a service due to the high inter-cell interference. Hybrid schemes that are a combination of universal reuse and higher reuse factors, the so-called fractional reuse, are described in S. W. Halpern, “Reuse partitioning in cellular systems,” 33rd IEEE Vehicular Technology Conference, 1983, vol. 33, pp. 322-327, May 1983.
The principal underlying the fractional reuse approach will be described in the following with regard to
Conventional approaches usually build on primary indicators for each resource block to announce if a transmitter will keep transmission power below a certain threshold. The indicators of the neighboring cells can be used in a scheduling algorithm. Fractional reuse may, for example, be implicitly implemented by avoiding to schedule cell-edge users or resource blocks with a high interference. Examples of dynamic coordination schemes for the fractional reuse, which are implemented by active resource control and centralized coordination, are described in M. Rahman and H. Yanikomeroglu, “Enhancing cell-edge performance: a downlink dynamic interference avoidance scheme with inter-cell coordination,” IEEE Transactions on Wireless Communications, vol. 9, no. 4, pp. 1414-1425, 2010 for a single user system and in A. Dotzler, W. Utschick, and G. Dietl, “Fractional reuse partitioning for MIMO networks, in Proc. IEEE Global Telecommunications Conference (GLOBECOM 2010), December 2010 for a multi-user system. This approach attempts to solve the optimization given by the equation above based on a suitable description of R.
As mentioned above, in addition to the fractional reuse approach, also the dynamic cell selection approach is known in the art. Existing networks typically use a cell (transmitter) selection scheme based on the average channel quality. An active transmitter ak of the user k may be selected as
A cell selection that operates on a fast scale is the “fast cell site selection” (FCSS), which has been proposed for HSDPA. In FCSS users chose the best transmitter based on the instantaneous channel conditions. However, as the user, in general, is not aware of the load in the cells, load balancing necessitates coordination at the network side. A possible implementation is to manipulate the reference signal of overloaded cells such that users select cells with a lower load. This approach may not be suitable for future wireless networks necessitating accurate cell state information. An approach using a load-aware coordinated scheduler with cell selection is described in S. Das, H. Viswanathan, and G. Rittenhouse, “Dynamic load balancing through coordinated scheduling in packet data systems,” in Proc. 22nd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2003), vol. 1, April 2003, pp. 786-796. In accordance with the approach interference management is implemented by a power control for CDMA. A. Sang, X. Wang, M. Madihian, and R. Gitlin, “Coordinated load balancing, handoff/cell site selection, and scheduling in multi-cell packet data systems,” Wireless Networks, vol. 14, pp. 103-120, 2008 describe a decentralized approach that, instead of directly controlling the cell selection, manipulates the schedulers in each cell such that users move to low load cells. The schedulers (and therefore the implicit cell selection scheme) are aware of the inter-cell interference, but it is not actively managed.
For future wireless systems FCSS is considered within the coordinated multi-point (CoMP) framework and is named “dynamic cell selection” (DCS). A DCS method for a single user LTE-A system is described in M. Feng, X. She, L. Chen, and Y. Kishiyama, “Enhanced dynamic cell selection with muting scheme for DL CoMP in LTE-A,” in Proc. IEEE 71st Vehicular Technology Conference (VTC 2010—Spring), 2010, pp. 1-5. Interference coordination is implemented by cell muting, which may be interpreted as a specific form of FR.
The main advantages of DCS are the gains from the cell selection diversity due to the independent fading, and the ability to off-load users to neighboring cells in case a cell is congested. However, there are additional costs for coordination and user data distribution when user data needs to be communicated among the transmitters in case of a handover or needs to be made available at multiple transmitters.
In the following, the interference and load management offered by the LTE release 8 is considered. Typically, the downlink transmitter coordination is not part of a standard, only the signaling to be used for coordination schemes is specified. The LTE release 8 is described in S. Sesia, I. Toufik, and M. Baker, LTE, The UMTS Long Term Evolution: From Theory to Practice. Wiley, April 2009. Inter-cell interference coordination in LTE may be static, for example, by providing a cell-planning with rare reconfigurations, or may be semi-static, typically performed on a time scale of seconds or longer. Such semi-static interference coordination is mostly performed by simple “on-off” masks with regard to the resource blocks. The standardized signaling for the downlink are “Relative Narrowband Transmit Power” (RNTP) indicators for each resource block to announce if the transmitter will keep transmission power below a certain threshold. The RNTP indicators of the neighboring cells can be used in the scheduling algorithm, for example, to avoid scheduling cell-edge users of resource blocks with high interference, which is a possible way to implement FR.
In LTE handovers can be initiated for several reasons, including:
Long term mechanisms to detect load imbalances that operate with a frequency in the order of seconds can be used to configure handover offset values between the cells. Fast cell selection is actively prevented in LTE, as user data is not available at multiple transmitters, but is moved to the new active transmitter during a handover. To enable enhanced interference management that is load-aware, additionally, a separate load indication procedure is employed to exchange load information in the order of tens of milliseconds.
According to an embodiment, a method for selecting base stations in a wireless cellular network that are used for determining candidate rate configurations for serving users of the wireless cellular network, wherein the base stations operate in accordance with a fractional reuse scheme, the fractional reuse scheme allocating frequencies such that, at the cell centers, base stations operate at the same frequency, and, at the cell edge regions, the base stations operate at frequencies different from the frequencies of adjacent cells, wherein the bases stations are partitioned into subsets, the fractional reuse scheme allocating distinct frequencies to respective base station subsets, each subset including base stations having assigned the same frequency at the cell edge regions, may have the steps of: for each user, determining an active base station set by selecting from each base station subset a base station as an active base station in accordance with a predefined criterion, an active base station being a base station from which a user, in accordance with the predefined criterion, can receive data, the predefined criterion having a parameter describing a communication between a user and a base station, and serving a user by the active base stations in the active base station set in consecutive time slots, but not by more than one active base station in a single timeslot.
Another embodiment may have a computer program product having instructions to perform the above method when executing the instructions on a computer.
Another embodiment may have a wireless cellular network having a plurality of base stations operating in accordance with the fractional reuse scheme, wherein the network is configured to be operated in accordance with the above method.
Another embodiment may have a base station for a wireless cellular network, the wireless cellular network having a plurality of base station operating in accordance with the fractional reuse scheme, wherein the base station is configured to perform, at least in part, the above method.
Another embodiment may have a network controller for a wireless cellular network, the wireless cellular network having a plurality of base stations operating in accordance with the fractional reuse scheme, wherein the network controller is configured to perform, at least in part, the above method.
Embodiments of the invention provide a method for determining for a plurality of users of a wireless cellular network transmitters of the wireless cellular network used for determining candidate rate configurations for serving the users, wherein the transmitters of the wireless cellular network operate in accordance with the fractional reuse scheme allocating distinct resource blocks to respective transmitter partitions, each partition including transmitters having assigned the same resource block, the method comprising, for each user, determining an active transmitter set by selecting from each transmitter partition a transmitter as an active transmitter in accordance with a predefined criterion.
In accordance with embodiments a transmitter is determined to be an active transmitter in accordance with the dynamic cell selection scheme, wherein one transmitter may be selected from each transmitter partition as an active transmitter.
In accordance with embodiments the predefined criterion comprises a parameter describing a communication between a user and a transmitter, wherein the parameter may comprise an average channel quality. A transmitter may be selected as an active transmitter in case the parameter associated with the transmitter has a maximum/minimum value when compared to all remaining transmitters in the transmitter partition.
In accordance with embodiments at least one of the active transmitter sets comprises at least two active transmitters.
In accordance with embodiments the method further comprises, for every transmitter, determining a collection of all active user sets for the transmitter, wherein an active user set comprises the users of a transmitter having assigned thereto a resource block.
In accordance with embodiments the active transmitter set is determined by the user and fed back to the transmitter, or is determined by a network controller on the basis of parameters received from the user and describing a communication between the user and the transmitters.
In accordance with embodiments the method further comprises determining candidate rate configurations by performing at each transmitter an optimization per transmitter partition the transmitter is part of and allocating the resource blocks to the transmitters in accordance with the determined candidate rate configuration. The optimization may comprise a weighted sum rate optimization, the optimization comprising, for each transmitter, performing the weight sum rate optimization for every partition; and finding the best network wide partition which is applied at each transmitter. The method my further comprise performing a convergence check; and in case the convergence check is negative, updating the weights for the weighted sum rate optimization and repeating the previous steps.
In accordance with embodiments finding the best network wide partition is determined by a network controller, wherein the network controller receives the weighted sum rate optimization results from each transmitter, performs the convergence check, updates the weights if necessitated, and communicates the final resource allocation and rate assignment to the transmitters, or by every transmitter, wherein each transmitter receives the weighted sum rate optimization results from all other transmitters, wherein messages for the convergence check, for the update of the weights if necessitated, and for the final resource allocation and rate assignment are exchanged between the transmitters.
In accordance with embodiments, in case a plurality of users assigned to a specific cell are cell-edge users that comprise an active transmitter set including the transmitter of the specific cell and transmitters of different neighboring cells, the cell-edge users are moved to the neighboring cells and the transmitter of the specific cell is shut down.
Embodiments of the invention provide a computer program product comprising instructions to perform a method in accordance with embodiments of the invention when executing the instructions on a computer.
Embodiments of the invention provide a wireless cellular network comprising a plurality of transmitters operating in accordance with the fractional reuse scheme, wherein the network is configured to be operated in accordance with the method in accordance with embodiments of the invention.
Embodiments of the invention provide a transmitter for a wireless cellular network, the wireless cellular network comprising a plurality of transmitters operating in accordance with the fractional reuse scheme, wherein the transmitter is configured to perform, at least in part, the method in accordance with embodiments of the invention.
Embodiments of the invention provide a network controller for a wireless cellular network, the wireless cellular network comprising a plurality of transmitters operating in accordance with the fractional reuse scheme, wherein the network controller is configured to perform, at least in part, the method in accordance with embodiments of the invention.
Embodiments of the invention provide a load-aware dynamic cell selection scheme with interference coordination by fractional reuse for a downlink transmission in a multiple-input multiple-output (MIMO) cellular network, wherein for increasing the performance of the network interference is carefully managed by fractional reuse and dynamic cell selection which helps to balance the load among the cells, so that embodiments of the invention provide a novel approach for the cooperation of transmitters, where fractional reuse and dynamic cell selection are integrated and act in concert.
The present invention is based on the finding that efficient operation of a multi-user system necessitates a resource assignment such that users in unfavorable positions are served on the basis of resource blocks that are not used by neighboring transmitters and, additionally, load balancing on a fast scale is to be performed jointly with interference management which allows to circumvent any asymmetric loading of the cells and avoids load congestion of the network which leads to a higher overall performance. This efficient operation of a wireless cellular network is established by sophisticated methods for FR and DCS that, in accordance with embodiments, act in concert, thereby improving the network performance. In conventional approaches, FR is often implemented by user assignment, either by a central control unit or by a decentralized approach, wherein binary indicators and restriction lists are exchanged and negotiated, which are then considered in the scheduling decisions. For multi-user systems users within one cell are not affected by the same interference transmitters, therefore the indicator maps have to be merged which might block a lot of resource blocks and may lead to an inefficient usage of the resources. In general, the known attempts are not suited for multi-user systems, where transmission rates of users of the same transmitter do interdepend. Thus, in accordance with the inventive approach, a method for FR in a multi-user system as described in A. Dotzler, W. Utschick, and G. Dietl, “Fractional reuse partitioning for MIMO networks, in Proc. IEEE Global Telecommunications Conference (GLOBECOM 2010), December 2010 is enriched by DCS. For single-user systems DCS may be included in the user assignment problem that is solved centrally. Alternatively, transmitters can maintain and negotiate handover thresholds for the user. In A. Sang, X. Wang, M. Madihian, and R. Gitlin, “Coordinated load balancing, handoff/cell site selection, and scheduling in multi-cell packet data systems,” Wireless Networks, vol. 14, pp. 103-120, 2008 centrally coordinated cell breathing leads to handovers of the users and to less congested cells, without explicit manipulation of the handover parameters. Thus, the above-mentioned most interesting approaches known in the art are not applicable for multi-user systems, so that for multi-user systems a load-aware DCS scheme that integrates with FR is missing.
Thus, in accordance with a first aspect embodiments of the invention provide a novel way for selecting transmitters in a wireless cellular network that are used for determining candidate rate configuration for serving users. The inventive approach combines the advantageous effects of fractional reuse and dynamic cell selection in such a way that for each user not only a single active transmitter is determined, rather when starting from the fractional reuse scheme, all possible active transmitters are determined as an “active transmitter set”.
In accordance with a further aspect, which results from the first aspect, there is no explicit cell selection mechanism needed. Rather, in accordance with the second aspect—on the basis of the determined active transmitter set for a user—the candidate configurations are determined, e.g. by applying a WSR optimization (WSR=weighted sum rate), and the resources and rates are allocated so that the cell selection is performed inherently by the resource and rate assignment.
A further aspect of the inventive approach concerns the specifics of the signaling during the optimization and allocation process in accordance with the second aspect.
Yet a further aspect concerns the possibility of muting a transmitter for avoiding excessive interference which, at the same time, allows for energy savings. This is possible because of the approach in accordance with the first aspect determining a plurality of active transmitters for the users and providing for the possibility of muting one of the transmitters in case users within an assigned cell may be served by transmitters of neighboring cells so that the transmitter of the cell to which the users are assigned is no longer needed and may be shut off.
Embodiments of the invention will now be described with reference to the accompanying drawings, in which:
Embodiments of the invention provide a novel transmitter coordination method for the downlink of a cellular network which is an integrated approach for FR (fractional reuse) and load-aware DCS (dynamic cell selection). A mechanism to implement FR is, for example, described in A. Dotzler, W. Utschick, and G. Dietl, “Fractional reuse partitioning for MIMO networks, in Proc. IEEE Global Telecommunications Conference (GLOBECOM 2010), December 2010, which introduces a method with predefined partitions of the transmitters such that fractional FR can be established. All feasible resource allocations to the transmitter partitions and rate assignments among the multiple users served by the transmitters constitute an achievable rate region R and, in accordance with the inventive approach, an iterative algorithm is used to solve the optimization given above in Equation (1.2). The algorithm calculates a set of candidate configurations until a solution can be found as a convex combination of these points. The solution is established by a resource allocation such that each candidate configuration is applied to a fraction of the resources related to the coefficients of a convex combination. The candidate configurations are found by a sequence of weighted-sum rate (WSR) optimizations, where the weights are updated dependent on the utility.
To enable DCS, contrary to known approaches, a set of active transmitters per user is used (instead of a single active transmitter), and a mechanism is applied to select this set based on the transmitter partitions defined for FR. According to a suitable criterion, for example, the average channel quality, maximum one transmitter out of each transmitter partition is selected as a potential active transmitter. As is described in A. Sang, X. Wang, M. Madihian, and R. Gitlin, “Coordinated load balancing, handoff/cell site selection, and scheduling in multi-cell packet data systems,” Wireless Networks, vol. 14, pp. 103-120, 2008 no explicit selection rule is given, instead the cell (transmitter) selection is a direct consequence of the structure of the candidate configurations and the following resource allocation.
In a similar way as described in A. Dotzler, W. Utschick, and G. Dietl, “Fractional reuse partitioning for MIMO networks, in Proc. IEEE Global Telecommunications Conference (GLOBECOM 2010), December 2010, candidate configurations are found by WSR optimization and a competition among all transmitter partitions. However, in addition to known approaches in accordance with embodiments of the invention, an approach is provided where every transmitter performs a WSR per transmitter partition it is part of and in accordance with a further aspect, the signaling to compute the candidate point is also described. A WSR maximization automatically performs a user selection and allows to drop users in case they have too bad channel conditions and in case the transmitter is overloaded. This assures that a reselection only happens in case the channel conditions to the other transmitter are good enough (in relation to the channel conditions of the other users) and the transmitter has available resources to serve the user.
As users are allowed to have different active transmitters for each transmitter partition and as the solution is found by a combination of the configurations, reselection is possible. However, the mechanism to construct the active transmitter set and the resource allocation assures that within a resource block, for example, a time slot, a user is only served by a single transmitter. The active transmitter set for DCS is chosen such that it integrates with FR. Since an explicit selection rule is not necessary, there is no need to negotiate and maintain handover thresholds for the users. Instead, the transmission strategies are computed by WSR optimizations (multi-user scheduling) at the transmitters and only a minor overhead is caused to coordinate resource allocation and weight updates between the transmitters. Additionally, in accordance with embodiments, the DCS approach is tied to the interference management so that more flexibility for the downlink coordination is provided. For example, cell-edge users may be moved to neighboring cells and the transmitter can be temporarily shut off in order not to interfere with these users.
Thus, the main contributions of embodiments of the invention are:
In the following, the definition of the fractional reuse will be explained (see also A. Dotzler, W. Utschick, and G. Dietl, “Fractional reuse partitioning for MIMO networks, in Proc. IEEE Global Telecommunications Conference (GLOBECOM 2010), December 2010). A set of reuse factors N=|N| is considered to be available and a reuse pattern is defined as follows:
A reuse pattern with a factor nεN is given by a partition of transmitters T into subsets total T(n1) . . . T(nm). Orthogonal resources are assigned to each subset given by the fractions f(n1), . . . , f(nn), such that Σi=1nf(ni)=fn, where fn is the fraction of the total resources assigned to factor n.
Typically, patterns are designed such that transmitters within the subset T(ni) are geographically separated and therefore interference is reduced by the attenuation, due to the pathlosses. The interdependence of the user rates within one reuse pattern is described by an achievable rate region R(ni). The dynamic allocation of resources to reuse patterns is known as fractional reuse which is formally defined as follows:
The dynamic assignment of
such that f=ΣnεNΣi=1nf(ni)=1, respectively fεF,F={f≧0:∥f∥1=1}, is called fractional reuse.
An operation point of a network,
r=f
(11)
c
(11)
+ . . . +f
(NN)
c
(NN)
=[c
(11)
, . . . ,c
(NN)
]f, (1.3)
is determined by the resource allocation fεF and the rate assignment c(11)εR(11), . . . , c(NN)εR(NN). Based on these definitions, an efficient operating point of the network can be found as the solution of the following optimization problem:
Equation (1.3) implies an achievable rate region R, achieved by scheduling multiple physical layer modes
={[c(11), . . . ,c(NN)]f:c(11)ε
(11), . . . ,c(NN)ε
(NN),fε
}=co{
(11), . . . ,
(NN)}
which leads to a formulation that is of the same structure as Equation (1.2):
Under the assumption that R is convex, which is true by definition in the applied model, and the utility is jointly concave in all user rates, Algorithm 1 depicted in
Following the above short explanation of the fractional reuse definition as it can also be derived from A. Dotzler, W. Utschick, and G. Dietl, “Fractional reuse partitioning for MIMO networks, in Proc. IEEE Global Telecommunications Conference (GLOBECOM 2010), December 2010, a first aspect in accordance with embodiments of the invention is described. Contrary to state-of-the-art methods, in accordance with embodiments of the invention, there is no explicit cell (transmitter) selection mechanism. Instead, the selection is performed inherently by the resource allocation and rate assignment. Users that may benefit from a dynamic selection are those on the cell edge or boundary and therefore also the ones with significant interference from neighboring transmitters, which are in turn the transmitters that are candidates for transmission. In case a resource block is assigned to the transmitters in the subset T(ni), the transmitter a user can potentially receive data from is called an “active transmitter”, and is determined by:
and a set of active transmitters for a user k is
k
={a
(11),k
, . . . ,a
(NN),k}.
The assignment of the transmitter a(ni),k is a consequence of the resource allocation to the candidate configurations c(ni), found by a weighted sum-rate optimization, where c(ni),k>0. From a network's perspective, the set of candidate users of a transmitter t in case the resource block is assigned to pattern (m) is
t={(11),t, . . . ,
(Ni′),t},,
The collection of all active user sets for a transmitter t is
t={(11),t, . . . ,
(Ni′),t},,
where i′ is such that tεT(Ni′).
In case the transmitter partitions T(11), . . . , T(NN) are known to a user, Ak can be determined by the user and fed back to the transmitters. The feedback can be implemented either by sending one message that is then distributed among the transmitters in Ak or by a message that is sent to every user, wherein Ak indicates the user's membership in K(ni),t.
The active transmitter set for a user and the associated collection of all active user sets for a transmitter may also be calculated in a centralized manner, for example by the central controller. This is shown in
Thus, in accordance with the first aspect of embodiments of the invention, all transmitters that fulfill a predefined criterion, for example an average channel quality, are selected to define the active transmitter set, which will now be described in further detail, on the basis of the network illustrated in
a
1=2,a2−2,a3−7,a4−7,a3−6,a6−6.
The fractional reuse is established by allocating fractions of the resources f(11), f(31), f(32), f(33) to the transmitter sets T(11)={1, . . . . , 9}, T(31)={1,4,7}, T(32)={2,5,8}, and T(33)={3,6,9}. According to Equation (1.3) the operating point of such a network is given by:
The above-described example is now extended to illustrate the inventive approach in accordance with the first aspect.
On the basis of this information, an operating point of the network is given by:
In the following, the second aspect of the inventive approach will be described, namely the estimation of instantaneous channels. More specifically, after a user k knows the set of active transmitters Ak an estimation of the instantaneous channels, for example the channel matrix in MIMO systems, between the user k and the transmitters Ak is performed. It is assumed that within each pattern, interference of other transmitters is approximated such that it only depends on the set of active transmitters T(ni)\a(ni),k, but not on their transmission strategy, for example, the transmission power or transmit signal covariance matrix in MIMO systems. The interdependence of data rates achieved by the users K(ni),t assigned to a transmitter t in case a pattern (ni) is active, is modeled by the rate region R(ni),t. The set of users that cannot be served in case the pattern (ni) is active, is given by:
The rate region R(ni) can be obtained from:
by permutation of the users. The weighted sum-rate optimization
can be performed in three steps:
(1) for each transmitter tεT, a weighted sum-rate optimization is performed for every pattern (ni), where tεT(ni). The rate vector c(ni),t is a solution of
(2) find the best network-wide pattern as a solution of
(3) the solution to the network-wide weighted sum-rate optimization c* is given by
The complete algorithm of the method in accordance with the second aspect is shown in
Turning again to the example shown in
It is noted that, basically, the user may also be served by all transmitters (in the active transmitter set) in consecutive time slots, but not by more than one in a single timeslot. Whether a user is actually served by all three transmitters depends on the entries of the candidate configurations found as the result of the weighted sum-rate optimization (see Equation (1.6)).
The above-described algorithm for solving the problem in equation (1.2) may use two different signaling approaches for implementing the algorithm, namely either a centralized version or a decentralized version.
As mentioned above, also a decentralized version of the implementation of the algorithm is possible, and
is communicated by messages 342 and 344 between the transmitters t1 and t2 so that every transmitter t1 and t2 can compute (ni)l in accordance with Equation (1.5). It is noted that it is not necessary that all transmitters communicate directly with each other, rather the communication on the rated sum-rates may also be done via the network controller or other suitable means. The calculation of (m)l at each transmitter is depicted in
In the following, on the basis of
The performance of the coordination algorithm described above was evaluated by Monte-Carlo-simulations for a wrap-around configuration, following the guidelines as outlined in “Working document towards proposed draft new report [guidelines for evaluation of radio interface technologies for IMT-advanced],” International Telecommunication Union (ITU), Geneva, Switzerland, ITU-R Document 5D/TEMP/46-E, February 2008. Channel matrices generated for a realistic channel model were used, as this is described in 3GPP, “Further Advancements for E-UTRA Physical Layer Aspects (Release X),” 3rd Generation Partnership Project (3GPP), TR 36.814, January 2009, and the parameters are summarized in the table shown in
Thus, embodiments of the invention provide for an approach combining dynamic cell selection and frequency reuse partitioning for multi-user networks as a selection of active transmitters per user (active transmitter set) matched to predefined reuse patterns, wherein the active transmitter sets are used to determine candidate configurations by weighted sum-rate optimization. The active transmitter set may comprise transmitters with the largest long-term average channel quality for all given reuse patterns. Further, a singling procedure between the transmitters, users and a central unit or controller may be provided allowing resource allocation and weight updates both in a centralized and decentralized manner. When compared to conventional approaches, embodiments of the invention provide for a more flexible dynamic cell selection with fractional frequency reuse also for multi-user systems. There is no exchange of channel state information necessitated. Load balancing can be used to switch off cells, thereby reducing the power consumption of base stations or eNBs, saving energy (green communications), and reducing OPEX. Further, throughput (special efficiency) of cell-edge users is increased, leading to more satisfied customers and higher ARPU.
Although some aspects have been described in the context of an apparatus, it is clear that these aspects also represent a description of the corresponding method, where a block or device corresponds to a method step or a feature of a method step. Analogously, aspects described in the context of a method step also represent a description of a corresponding block or item or feature of a corresponding apparatus.
Depending on certain implementation requirements, embodiments of the invention can be implemented in hardware or in software. The implementation can be performed using a digital storage medium, for example a floppy disk, a DVD, a CD, a ROM, a PROM, an EPROM, an EEPROM or a FLASH memory, having electronically readable control signals stored thereon, which cooperate (or are capable of cooperating) with a programmable computer system such that the respective method is performed. Some embodiments according to the invention comprise a data carrier having electronically readable control signals, which are capable of cooperating with a programmable computer system, such that one of the methods described herein is performed.
Generally, embodiments of the present invention can be implemented as a computer program product with a program code, the program code being operative for performing one of the methods when the computer program product runs on a computer. The program code may for example be stored on a machine readable carrier. Other embodiments comprise the computer program for performing one of the methods described herein, stored on a machine readable carrier. In other words, an embodiment of the inventive method is, therefore, a computer program having a program code for performing one of the methods described herein, when the computer program runs on a computer.
A further embodiment of the inventive methods is, therefore, a data carrier (or a digital storage medium, or a computer-readable medium) comprising, recorded thereon, the computer program for performing one of the methods described herein. A further embodiment of the inventive method is, therefore, a data stream or a sequence of signals representing the computer program for performing one of the methods described herein. The data stream or the sequence of signals may for example be configured to be transferred via a data communication connection, for example via the Internet.
A further embodiment comprises a processing means, for example a computer, or a programmable logic device, configured to or adapted to perform one of the methods described herein. A further embodiment comprises a computer having installed thereon the computer program for performing one of the methods described herein. In some embodiments, a programmable logic device (for example a field programmable gate array) may be used to perform some or all of the functionalities of the methods described herein. In some embodiments, a field programmable gate array may cooperate with a microprocessor in order to perform one of the methods described herein. Generally, the methods may be performed by any hardware apparatus.
While this invention has been described in terms of several embodiments, there are alterations, permutations, and equivalents which will be apparent to others skilled in the art and which fall within the scope of this invention. It should also be noted that there are many alternative ways of implementing the methods and compositions of the present invention. It is therefore intended that the following appended claims be interpreted as including all such alterations, permutations, and equivalents as fall within the true spirit and scope of the present invention.
Number | Date | Country | Kind |
---|---|---|---|
11163941.5 | Apr 2011 | EP | regional |
This application is a continuation of PCT/EP2012/057533 filed on Apr. 25, 2012, which claims priority to the European Application No. 11163941.5 filed on Apr. 27, 2011. The entire contents of these applications are incorporated herein by reference.
Number | Date | Country | |
---|---|---|---|
Parent | PCT/EP2012/057533 | Apr 2012 | US |
Child | 14063856 | US |