AU2021107065A4 - Optimal resource allocation in next-generation heterogeneous mobile network - Google Patents
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- 238000013468 resource allocation Methods 0.000 title claims abstract description 25
- 238000000034 method Methods 0.000 claims abstract description 36
- 239000011159 matrix material Substances 0.000 claims abstract description 16
- 230000001413 cellular effect Effects 0.000 claims abstract description 13
- 230000003044 adaptive effect Effects 0.000 claims description 3
- 238000005259 measurement Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 claims description 3
- 230000006978 adaptation Effects 0.000 claims 1
- 108091006146 Channels Proteins 0.000 description 41
- 230000008901 benefit Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 7
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- 230000005540 biological transmission Effects 0.000 description 3
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/04—Wireless resource allocation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/20—Control channels or signalling for resource management
- H04W72/21—Control channels or signalling for resource management in the uplink direction of a wireless link, i.e. towards the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
- H04W84/04—Large scale networks; Deep hierarchical networks
- H04W84/042—Public Land Mobile systems, e.g. cellular systems
Abstract
A system and a method for a resource allocation in heterogeneous
cellular network, comprises of: a plurality of resource block (RB) (102)
allocated to a plurality of user along with a quality of service (QoS)
using Heuristic optimal resource allocation (HORA) technique; an
allocation module (104) for allocating the plurality of RB (102) in
uplink (UL) direction to increase throughput using Chunk based RB
allocation (CRBA) algorithm; and an adaption module (106) for
changing system parameters based on actual channel quality by
adapting to channel conditions, wherein physical uplink control channel
(PUCCH) includes information such as multiple modulation and coding
schemes (MCS), rank information, precoder matrix, and MIMO modes.
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Description
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The present invention generally relates to mobile communication networks. More specifically, the present invention relates to a resource allocation in heterogeneous cellular network.
For high-speed data transfer over the air between wireless devices and the base station (BS) in cellular networks, a 3GPP LTE physical layer leverages the most effective multiple access mechanisms. The exponential growth of smart phone subscribers, as well as high-end rich multimedia applications, has created a huge need for wireless broadband access. Numerous new demanding applications must be supported in the next generation of 5G networks, and consumers can expect data rates of up to 100 Mbps peak. The essential strategies in LTE-A are RB allocation and multi-user MIMO technology, which combined achieve fantastic results in terms of user data rate, average cell throughput, and system cell coverage. This is still true for 5G networks. LTE-A uses constantly changing system resource parameters, such as rate, power levels, transmit antenna selection, and modulation and coding methods, to achieve excellent spectral efficiency and throughput in response to channel conditions (MCS).
The usage of available system bandwidth through the air interface is determined by resource allocation, which is the key to boosting performance. Because of significant growth in the number of UE within a network, there is a necessity to improve the QoS requirement. For the restricted resources, network capacity, and coverage, efficient resource allocation attempts to provide guaranteed QoS to priority users. A two-tier run process using a heuristic algorithm is used for RB allocation, however it consumed more time; therefore, to reduce the processing time an algorithm is proposed which performs contiguous RB assignment and sum throughput maximization in a single-tier run process. In the two-tier femtocell network, the sub-carrier and joint power allocation problem in the UL direction is addressed. Here, two constraints are considered, such as interference limit and QoS in which the channel conditions and QoS of the users decided the QoS capacity. To approximate channel uncertainty, a type-2 fuzzy logic controller is used. The ideal bandwidth is identified here, and the right slot is assigned to the UE in the scheduling subcarrier. It increased the system's throughput.
Therefore, there exists a need to develop a system, to meet the demands of network operators and using a multi-dimension MU-MIMO and higher modulation (QPSK, 16QAM, 64QAM) schemes to increase user throughput in noisy channel conditions. The technical advancements disclosed by the present invention overcomes the limitations and disadvantages of existing and convention systems and methods.
The present invention generally relates to a system and a method for resource allocation in heterogeneous cellular network.
An objective of the invention is to provide a resource allocation in heterogeneous cellular network.
Another objective of the invention is to increase user throughput in noisy channel conditions.
Another objective of this invention is to determine resource block (RB) allocation among users to satisfy the quality-of-service requirement. Another objective of this invention is to offer a tradeoff between computational complexity and performance.
Another objective of this invention is to perform RB and power allocation separately to reduce computational complexity.
According to an aspect of the present invention, a system for a resource allocation in heterogeneous cellular network, wherein the system comprises of: a plurality of resource block (RB) allocated to a plurality of user along with a quality of service (QoS) using Heuristic optimal resource allocation (HORA) technique, wherein remaining of the RBs are allocated among rest of the plurality of users; an allocation module associated with the plurality of the RBs for allocating the plurality of RB in uplink (UL) direction to increase throughput using Chunk based RB allocation (CRBA) algorithm, wherein the plurality of the RBs and the plurality of user equipment's (UEs) are divided into different sets for allocating the plurality of RB; and an adaption module associated with the plurality of resource block (RB) and the allocation module for changing system parameters based on actual channel quality by adapting to channel conditions, wherein physical uplink control channel (PUCCH) includes information such as multiple modulation and coding schemes (MCS), rank information, precoder matrix, and MIMO modes.
According to an aspect of the present invention, a method for a resource allocation in heterogeneous cellular network, wherein the method comprises of: allocating a plurality of user along with a quality of service (QoS) using a plurality of resource block (RB) of Heuristic optimal resource allocation (HORA) technique, wherein remaining of the RBs are allocated among rest of the plurality of users; allocating the plurality of RB using an allocation module associated with the plurality of the RBs in uplink (UL) direction to increase throughput using Chunk based RB allocation (CRBA) algorithm, wherein dividing the plurality of the RBs and the plurality of user equipment's (UEs) into different sets for allocating the plurality of RB; and changing system parameters using an adaption module associated with the plurality of resource block (RB) and the allocation module based on actual channel quality by adapting to channel conditions, wherein physical uplink control channel (PUCCH) includes information such as multiple modulation and coding schemes (MCS), rank information, precoder matrix, and MIMO modes.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:
Figure 1 illustrates a block diagram of a system for a resource allocation in heterogeneous cellular network,
Figure 2 illustrates a flow diagram of a method for a resource allocation in heterogeneous cellular network, and
Figure 3 illustrates a flow diagram of Resource blocks selection and allocation flow.
Further, skilled artisans will appreciate that elements in the drawings are illustrated for simplicity and may not have been necessarily been drawn to scale. For example, the flow charts illustrate the method in terms of the most prominent steps involved to help to improve understanding of aspects of the present invention. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having benefit of the description herein.
For the purpose of promoting an understanding of the principles of the invention, reference will now be made to the embodiment illustrated in the drawings and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the invention as illustrated therein being contemplated as would normally occur to one skilled in the art to which the invention relates.
It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the invention and are not intended to be restrictive thereof.
Reference throughout this specification to "an aspect", "another aspect" or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.
The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by "comprises...a" does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.
Unless otherwise defined, all 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 belongs. The system, methods, and examples provided herein are illustrative only and not intended to be limiting.
Embodiments of the present invention will be described below in detail with reference to the accompanying drawings.
Figure 1 illustrates a block diagram of a system for a resource allocation in heterogeneous cellular network, wherein the system (100) comprises of: a plurality of resource block (RB) (102), allocation module (104), and an adaption module (106).
The plurality of resource block (RB) (102) allocated to a plurality of user along with a quality of service (QoS) using Heuristic optimal resource allocation (HORA) technique, wherein remaining of the RBs (102) are allocated among rest of the plurality of users, wherein after every allocation, the power is subtracted from the available power pool, wherein upon the allocation of the RBs (102) to the plurality of users, the RB (102), power, and rate constraints are verified, wherein performing optimization for maximum data rate, wherein the plurality of users is initially arranged in a descending order as per the SNR values.
The allocation module (104) is associated with the plurality of the RBs (102) for allocating the plurality of RB (102) in uplink (UL) direction to increase throughput using Chunk based RB allocation (CRBA) algorithm, wherein the plurality of the RBs and the plurality of user equipment's (UEs) are divided into different sets for allocating the plurality of RB.
The adaption module (106) is associated with the plurality of resource block (RB) (102) and the allocation module (104) for changing system parameters based on actual channel quality by adapting to channel conditions, wherein physical uplink control channel (PUCCH) includes information such as multiple modulation and coding schemes (MCS), rank information, precoder matrix, and MIMO modes, wherein the MCS is selected for the higher SNR by using a link adaption technique along with a sub-band Channel quality indicator (CQI) adaptive modulation and coding scheme (AMC), wherein a mobile receiver measures channel characteristics parameters and decodes resource grid, wherein channel quality measurement includes the CQI, precoder matrix estimation (PMI), and RI (rank estimation).
Figure 2 illustrates a flow diagram of a method for a resource allocation in heterogeneous cellular network, wherein the method (200) comprises of:
Step (202) discloses about allocating a plurality of user along with a quality of service (QoS) using a plurality of resource block (RB) (102) of Heuristic optimal resource allocation (HORA) technique, wherein remaining of the RBs (102) are allocated among rest of the plurality of users.
Step (204) discloses about allocating the plurality of RB (102) using an allocation module (104) associated with the plurality of the RBs (102) in uplink (UL) direction to increase throughput using Chunk based RB allocation (CRBA) algorithm, wherein dividing the plurality of the RBs and the plurality of user equipment's (UEs) into different sets for allocating the plurality of RB (102).
Step (206) discloses about changing system parameters using an adaption module (106) associated with the plurality of resource block (RB) (102) and the allocation module (104) based on actual channel quality by adapting to channel conditions, wherein physical uplink control channel (PUCCH) includes information such as multiple modulation and coding schemes (MCS), rank information, precoder matrix, and MIMO modes.
In the HORA algorithm, a heuristic approach to decide the allocation of RBs amongst the users with the QoS (Rate) requirement of every user. Power allocation and RB allocation is carried out separately. Users with the highest SNR are the allocated a large set of RBs and the highest power with good channel gain until the QoS requirements of the users are met.
Figure 3 illustrates a flow diagram of Resource blocks selection and allocation flow.
The plurality of resource block (RB) (102) is allocated to a plurality of user along with a quality of service (QoS) using Heuristic optimal resource allocation (HORA) technique, wherein remaining of the RBs (102) are allocated among rest of the plurality of users, wherein after every allocation, the power is subtracted from the available power pool, wherein upon the allocation of the RBs (102) to the plurality of users, the RB (102), power, and rate constraints are verified, wherein performing optimization for maximum data rate, wherein the plurality of users is initially arranged in a descending order as per the SNR values.
The allocation module (104) is associated with the plurality of the RBs (102) (102) for allocating the plurality of RB (102) in uplink (UL) direction to increase throughput using Chunk based RB allocation (CRBA) algorithm, wherein the plurality of the RBs and the plurality of user equipment's (UEs) are divided into different sets for allocating the plurality of RB (102).
The adaption module (106) is associated with the plurality of resource block (RB) (102) and the allocation module (104) for changing system parameters based on actual channel quality by adapting to channel conditions, wherein physical uplink control channel (PUCCH) includes information such as multiple modulation and coding schemes (MCS), rank information, precoder matrix, and MIMO modes, wherein the MCS is selected for the higher SNR by using a link adaption technique along with a sub-band Channel quality indicator (CQI) adaptive modulation and coding scheme (AMC), wherein a mobile receiver measures channel characteristics parameters and decodes resource grid, wherein channel quality measurement includes the CQI, precoder matrix estimation (PMI), and RI (rank estimation).
The channel state reports are generated at the UE and transmitted to the Base station (BS). In the uplink, the UE sends a channel quality parameter within a physical uplink control channel (PUCCH). It transmits this information to eNB as a closed loop feedback to help scheduling and link adaption. The higher level of modulation index is used for good channel condition.
The UL radio channel quality is identified based on the CQI report. Based on the channel quality the MCS is selected to match the channel link and to ensure that the bit error rate (BER) does not exceed 10%. Many of these techniques choose the highest MCS as a function of signal to interference noise ratio (SINR) post-detection. Scheduling in the BS takes the feedback input synchronously or asynchronously from the UE that helps to calculate the required RBs to be assigned to each UE. The CSI channel status indicator is received by the BS periodically which decodes the SNR. The BS calculates the SNR from the CSI and appropriate MCS are selected for the given RBs.
In the UL transmission, channel coding structure selection of the MCS process is similar to the DL and is under the control of the BS. LTE adjusts the throughput of the UE based on the channel quality. The BS receives CQI feedback from the UE. The appropriate CQI is selected based on a set of BER threshold. In response to the CQI, the MCS and the channel coding rate are selected. Based on the SINR values the modulation schemes are changed between QPSK, 16QAM, 64QAM,
256QAM for the highest capacity of the UE. The code rate depends on the radio link condition. Therefore, in poor radio link conditions, a lower code rate is used and in higher SNR, a higher code rate is used for the given modulation.
There are two types of CQI reports, namely, wideband and sub-band. In a wideband adaption, a given subframe assigns all the RBs that have the same modulation scheme. A wideband CQI report recommends a single MCS value to the RBs available in the bandwidth, while a sub-band CQI report selects multiple modulation and coding scheme (MCS) values to different continuous RBs i.e., different adaption assigns different RBs in each subframe. It represents 32 different MCS and TLB sizes. The BS uses one of the 32 MCS values. Its corresponding transport block size is based on the SNR value and BER. At any TTI, the AMC chooses the MCS that expands the expected transport block size (TBz). The expected TB size is a component of TBS and block error probability (BLEP), which reduces the probability of the TB.
The Precoder matrix estimation (PMI) report recommends the pre coding codebook index for closed-loop spatial multiplying of the D UL transmission. A reporting PMI is a single wideband value or multiple sub-band values.
The Rank estimation (RI) estimates the rank of the channel matrix which indicates the number of transmission layers or independent transmit information for a spatial multiplexing framework. These methods conduct a selection depending on the SINR post-detection. The same process is used for the selection of MCS. The rank of the channel matrix is a ratio of the maximum and the minimum eigen values of the channel matrix.
The Quality of Service (QoS) helps to improve the satisfaction of users in the throughput and the BW allocation using load sharing and policy management. QoS is associated with evolved packet core (EPC) bearer and multiple bearers can be established based on different QoS streams or connectivity to the different packet data networks (PDN) for single user. The difference in the BS has different QoS constraints. The QoS influences the behavior of the BS resource scheduling algorithm. QoS potentially updates each service for a user based on radio and traffic conditions.
The drawings and the forgoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts necessarily need to be performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples. Numerous variations, whether explicitly given in the specification or not, such as differences in structure, dimension, and use of material, are possible. The scope of embodiments is at least as broad as given by the following claims.
Benefits, other advantages, and solutions to problems have been described above with regard to specific embodiments. However, the benefits, advantages, solutions to problems, and any component(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or component of any or all the claims.
Claims (7)
1. A system (100) for a resource allocation in heterogeneous cellular network, wherein the system (100) comprises of:
a plurality of resource block (RB) (102) allocated to a plurality of user along with a quality of service (QoS) using Heuristic optimal resource allocation (HORA) technique, wherein remaining of the RBs (102) are allocated among rest of the plurality of users;
an allocation module (104) associated with the plurality of the RBs (102) for allocating the plurality of RB (102) in uplink (UL) direction to increase throughput using Chunk based RB allocation (CRBA) algorithm, wherein the plurality of the RBs and the plurality of user equipment's (UEs) are divided into different sets for allocating the plurality of RB (102); and
an adaption module (106) associated with the plurality of resource block (RB) and the allocation module (104) for changing system parameters based on actual channel quality by adapting to channel conditions, wherein physical uplink control channel (PUCCH) includes information such as multiple modulation and coding schemes (MCS), rank information, precoder matrix, and MIMO modes.
2. The system as claimed in claim 1, wherein the MCS is selected for the higher SNR by using a link adaption technique along with a sub band Channel quality indicator (CQI) adaptive modulation and coding scheme (AMC).
3. The system as claimed in claim 1, wherein after every allocation, the power is subtracted from the available power pool.
4. The system as claimed in claim 1, wherein upon the allocation of the RBs (102) to the plurality of users, the RB (102), power, and rate constraints are verified, wherein performing optimization for maximum data rate.
5. The system as claimed in claim 1, wherein the plurality of users is initially arranged in a descending order as per the SNR values.
6. The system as claimed in claim 1, wherein a mobile receiver measures channel characteristics parameters and decodes resource grid, wherein channel quality measurement includes the CQI, precoder matrix estimation (PMI), and RI (rank estimation).
7. A method (200) for a resource allocation in heterogeneous cellular network, wherein the method (200) comprises of:
allocating a plurality of user along with a quality of service (QoS) using a plurality of resource block (RB) (102) of Heuristic optimal resource allocation (HORA) technique, wherein remaining of the RBs (102) are allocated among rest of the plurality of users;
allocating the plurality of RB (102) using an allocation module (104) associated with the plurality of the RBs in uplink (UL) direction to increase throughput using Chunk based RB allocation (CRBA) algorithm, wherein dividing the plurality of the RBs (102) and the plurality of user equipment's (UEs) into different sets for allocating the plurality of RB (102); and
changing system parameters using an adaption module (106) associated with the RB (102) and the allocation module (104) based on actual channel quality by adapting to channel conditions, wherein physical uplink control channel (PUCCH) includes information such as multiple modulation and coding schemes (MCS), rank information, precoder matrix, and MIMO modes.
102 106 A PLURALITY OF RESOURCE ADAPTATION MODULE BLOCK (RB) 104 ALLOCATION MODULE
FIGURE. 1
allocating a plurality of user along with a quality of service (QoS) using a plurality of resource block (RB) (102) of Heuristic optimal resource allocation (HORA) technique, wherein remaining of the RBs (102) are allocated among rest of the 202 plurality of users
allocating the plurality of RB (102) using an allocation module (104) associated with the plurality of the RBs in uplink (UL) direction to increase throughput using Chunk based RB allocation (CRBA) algorithm, wherein dividing the plurality of the RBs (102) and the plurality of user equipment's (UEs) into different sets for allocating 204 the plurality of RB (102);
changing system parameters using an adaption module (106) associated with the RB (102) and the allocation module (104) based on actual channel quality by adapting 206 to channel conditions, wherein physical uplink control channel (PUCCH) includes information such as multiple modulation and coding schemes (MCS), rank information, precoder matrix, and MIMO modes. FIGURE. 2
FIGURE.3
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