In a typical cell deployment, interference regions can be mitigated in space, time and frequency. Overlaid but not co-located base stations can interfere with each others thereby create regions, called interference region (IR), in which a terminal, which could be fixed or mobile, receives signals from more than one base station. If a single channel is used across the network where there are plurality of base stations, communication in interference regions can be disruptive if there is no resource management. For a channel with a given bandwidth, we define the total resource available as RES. The basic unit in RES is called slot, and each slot occupies a frequency bin and a symbol time. Multiple slots can be combined into a unit called Block. We partition RES into Blocks where each Block contains different slots, and size of each Block is not necessary the same.
Typically, a base station can use some of these Blocks, and up to RES. Let Bi to be the ith Block in RES. If IR doesn't exist in the network or there is no active terminal in the IR(s), each base station can use the entire RES for its terminals. Otherwise, the same Bi used by a base station for terminals in its IR can not be used by any base stations in which it shares the IR with. Define BC(j) to be the Block allocated to station j for its associated mobiles in its IR.
Intuitively, if the resource in the network is not managed properly, the resource available to a base station i would only be
where {interferer(i)} is the set of base stations that base station i interferes with. As {interferer(i)} or each BC(j) grows, the RES(i) diminishes. Since BC(i) is the resource for terminals in the IR of station i, the terminals attached to station i who are not in its IR can only have the remaining RES(i)−BC(i).
The resource management method proposed here tries to maximize the overall network throughput
we want the throughput to approach M*RES, where M is total number of stations. The underlying mechanism is that we want to increase the resource reuse in IR(s) (i.e. for any j, k∈{int erferer(i)}, we want BC(j)⊂BC(k)) such that
is minimized for all station i).
Proposed system 100 has a Central Controller 102, plurality of Base Stations 103-105, and plurality of Terminals 110-118 as entities. Central Controller is attached to the Backbone Network 101, and it captures the incoming traffic and routes to the base stations. Besides having the routing functionality, Central Controller does high-level resource management across the network for the base stations. Base stations are entities that has wired and wireless interface. They talk to terminals through their wireless interfaces. Each base station has a fixed amount of resource per frame and is required to distribute this resource to its terminals.
In order to satisfy every traffic demand and network topology, a feed back control method 200 is proposed. The system diagram shown in
1. Life Cycle of a Communication Request
a contains the process of a terminal requesting access to the network.
2. Resource Management Overview
3. Approaches to Resource Management
There are three approaches to resource management.
The first is the centralized approach called centralized micro-resource management, where the central controller handles the entire resource management across the entire network. The second approach is called the split-resource management, where the central controller performs macro-level resource assignments and Base Station performs micro-level resource assignments.
The third is the distributed approach called distributed micro-resource management, where each Base Station coordinates with its neighbors to perform resource management locally. The last approach is not considered here since typically frequent communication between base stations is not feasible if performance is considered. The methods for first and second approach are discussed below.
3.1 Centralized Micro-Resource Management
The centralized micro-resource manager 501 performs resource management in the centralized controller. Consider the inputs and outputs of this component in
If the resource manager is executed very infrequently, any new requests will incur large delay. However, if it is run very frequently, there will be a lot of traffic between the centralized controller and base stations. One advantage of this scheme is that it maximizes the overall throughput of the network due to its global view.
3.2 Split-Resource Management
In the split-resource management 600, we divide the whole resource management responsibilities into two parts. The Macro-Level Managements defined in
3.2.1 Macro-Resource Manager
The tasks of Macro-Resource Manager are: 1) Minimize interference in the IR(s). 2) Optimize entire network performance according but not limit to throughput and fairness. 3) Allocate Blocks to base station. The flow diagram of Macro-Resource Manager is described in
3.2.1.1 Interference Detection 701
The resource manager first identifies the IR(s). A terminal is considered to be in the IR(s) if a terminal is within the communication range of two or more base stations or it is able to communicate more than two base stations. This can be done based on terminal and base stations locations or the connectivity table of terminal and base stations. If no conflict is detected, then there is no IR.
3.2.1.2 Resource Partitioning and Assignment 702
The RES 1100 is partitioned into Blocks, and each base station inherits the same partition (see
3.2.1.3 Cost Association 703
Each terminal is assigned to a cost weight or a series of cost weights such as one per station it can communicate. The weight can be a function of a terminal's receive/transmit signal strength, traffic demand and etc. For example, suppose only one cost weight is assigned to each terminal. If the objective is to achieve fairness (i.e. assign each terminal same number of slots), each terminal will be assigned an equal weight. On the other hand, if the objective is to maximize network utilization, each terminal will be assigned according to its demand for resource (i.e. average traffic demand for each terminal divided by its current highest available rate). No resource is assigned to inactive terminals. This cost weight is used in the next step.
3.2.1.4 Terminal Association 704
Here, we associate terminals to base stations. The terminals who are not in the IR(s) are immediately assigned to the base station in which they can communicate with. For the terminals who are in the IR(s), we associate them with a base station in a way that maximizes the overall network utilization. The algorithm can be described as follows:
Suppose Bi is assigned to each base station. The size of each Bi is initially zero and their size is interactively incremented. The size for each Bi here is not necessary corresponding to the actual occupancy in the RES. The method in determining the exact size of Bi is given later. Consider a terminal, who can communicate with base station i and j, where B1 is allocated to base station i and B2 is allocated to base station j. Define B1* and B2* to be the estimate occupancy of B1 and B2 in base station i and j. We need to decide whether to associate the mobile to the base station i or base station j. Once the terminal is assigned, the estimated occupancy of that base station will be updated. Consider the following rules: 1) Suppose B1* and B2* are currently empty, pick the one that has the minimum number of base stations using (e.g. if there are M base stations assigned to B1 and N base stations assigned to B2, where M>N, we will attach the mobile to base station j and B2*=B2*+C, where C is the estimated load/cost of the mobile station). 2) Suppose both base station i and j currently have enough space to accommodate the terminal with cost C, pick the one that has the maximum available space (i.e. max((B1-B1*), (B2-B2*))). Once the terminal is assigned, the Bi* will be updated as described in the case. 3) Suppose both B1 and B2 do not have enough space to accommodate the cost C, pick the one that maximize the overall network utilization (i.e. min(M*(C−(B1-B1*)), N*(C−(B2-B2*))). For this case, once the base station is chosen, the Block size has to be updated for the entire network (e.g. suppose base station i is chosen, we have to increment B1 by C−(B1-B1*) across the network).
We perform this algorithm iteratively on every mobile in the IR(s). The order at which the algorithm acts on the terminals affects the final result. To pick the order at which the algorithm yields the optimal result is NP hard. The method proposed here acts on the terminals according to terminal's connectivity with the base stations, and the terminal with the lowest connectivities is first assigned. By assigning the lowest connectivities first, the algorithm can achieve the optimal with greater chance. On the other hand, if the method assigns the terminals in the reversed order, and the sequence of assignments is not already optimal, it would be more difficult for an algorithm to achieve optimal since the later assignments/terminals have lower number of connectivities, thus imposes more constraint on the algorithm.
3.2.1.5 Allocation Fine Tuning 705
One optional embodiment of the invention proposes to bring down the size of the Bi for i≠0. The algorithm is described as followed:
3.2.1.6 Resource Sizing 706
In this step, the size of each Bi determined here corresponds to the fraction of the RES allocated to each Bi. The determination is based on the cost assignments and the terminal assignments in the previous step (see
The size of Bi is defined as S(i)*RES.
Here is a list of policy considered for terminals in the IR(s):
3.2.2 Micro-Resource Manager
The Micro-Resource Manager runs in each Base Station.
Once the resource is granted to a connection, the resource manager will enhance the quality of the connection through channel diversity. Packet transmissions per connection are reshuffled both in frequency and in time to combat narrowband noise and fading.
3.2.3 System Update
The Feedback Control is used by the central controller to resize the Bi during run-time. Since the network topology and the traffic demand keep changing over time, some Bi can be over-utilized or under-utilized at any given time. The method proposed here allows the central controllers to resize Bi to meet traffic demand. The mechanism is described as follows: Each base station periodically reports to the central controller the average utilization of the Block used by the terminals attached to it who are in its IR as well as for the block used by terminals attached to it who are not in the IR.
The following are the rules for system update:
These rules can be generalized and service provider can configure these rules appropriately according to the topology and utilization. An example definition of the utilization could be ratio of allocated over total resources as well as number of dropped sessions.
This non-provisional application is claiming the priority date of an earlier-filed U.S. provisional application Ser. No. 60/753,709 filed on Dec. 22, 2005 under 35 U.S.C. §119(e)
Number | Name | Date | Kind |
---|---|---|---|
5666649 | Dent | Sep 1997 | A |
6493331 | Walton et al. | Dec 2002 | B1 |
6496700 | Chawla et al. | Dec 2002 | B1 |
6993333 | Laroia et al. | Jan 2006 | B2 |
7636334 | Gerlach | Dec 2009 | B2 |
7664193 | Jalali et al. | Feb 2010 | B2 |
20050141450 | Carlton et al. | Jun 2005 | A1 |
20050169229 | Cho et al. | Aug 2005 | A1 |
20060003767 | Kim et al. | Jan 2006 | A1 |
20060018347 | Agrawal | Jan 2006 | A1 |
20060072501 | Toshimitsu et al. | Apr 2006 | A1 |
20060239264 | Kang et al. | Oct 2006 | A1 |
20070253367 | Dang et al. | Nov 2007 | A1 |
20070297363 | Jalil et al. | Dec 2007 | A1 |
20100220696 | Jalil et al. | Sep 2010 | A1 |
Number | Date | Country | |
---|---|---|---|
20090080375 A1 | Mar 2009 | US |
Number | Date | Country | |
---|---|---|---|
60753709 | Dec 2005 | US |