This application claims priority under 35 U.S.C. §119(a) to a Korean patent application filed in the Korean Intellectual Property Office on Jan. 26, 2007 and assigned Serial No. 2007-8419, the entire disclosure of which is hereby incorporated by reference.
The present invention relates to a scheduling apparatus and method in a wireless communication system. More particularly, the present invention relates to a scheduling apparatus and method using channel prediction in a Broadband Wireless Access (BWA) system.
Recently, with the increasing interest on wireless multimedia contents and Internet services, there is a growing demand on data transmission techniques with a high capacity and a high speed. For example, research is being conducted for the effective use of limited wireless resources in various methods, such as, Code Division Multiple Access (CDMA), Orthogonal Frequency Division Multiplexing (OFDM), and Multiple Input Multiple Output (MIMO). In particular, the OFDM can transmit large volume data and video data (e.g., Moving Picture Experts Group (MPEG) 4) by using a broadband modulation/demodulation method, and is recently used in a Digital Video Technology (DVT) and an Institute of Electrical and Electronics Engineers (IEEE) 802.11g. Along with the MIMO, the OFDM has now been recognized a core technology of 4th Generation (4G).
Although the BWA system using the OFDM technique can transmit higher volume data in comparison with any other techniques used up to now, a Quality of Service (QoS) for various multimedia services cannot be ensured when the OFDM technique is used alone. That is, in a next generation mobile communication system, not only voice data but also QoS of traffic classes having different characteristics must be satisfied. Therefore, control (i.e., packet scheduling) needs to be performed in a Media Access Control (MAC) layer.
Conventionally, packet scheduling has been proposed by considering throughput, delay, and complexity. For fairness, various algorisms have been proposed, such as, a lead and lag model (i.e., leading, lagging, in sync) or a compensation model.
For example, a Proportional Fairness (PF) algorithm used in the CDMA2000 is designed to provide all terminals with fair services. However, the PF algorithm has a demerit in that throughput sharply decreases when the number of users exceeds a predetermined level. In a max Carrier to Interference (C/I) algorithm, a user having the best channel status has priority. Although the max C/I algorithm may show good performance in terms of throughput, disadvantageously, a wireless resource may be exclusively used by a user located near a Base Station (BS).
As such, algorithms proposed up to now are designed by considering one aspect (e.g., fairness), and thus it is difficult to apply these algorithms without alteration to the next generation system which concurrently provides services each having a different feature. A BS uses channel information fed back from a terminal. In this case, if the channel information does not indicate a channel used at a time when data is transmitted, a complex scheduling operation may result in an adverse effect. Therefore, in an environment where channel information used in scheduling does not indicate a channel used at a time when data is transmitted in practice, there is a need for a method of increasing reliability of channel information by considering mobility of a terminal.
Meanwhile, scheduling may be understood as an operation of selecting users to which a service is provided in a current frame. As mentioned above, a complex scheduling algorithm is useless in a situation where a channel cannot be correctly known at a time when data is transmitted in practice. Therefore, there is a need for a method of selecting users by using a much simpler algorithm.
To address the above-discussed deficiencies of the prior art, it is a primary aspect of the present invention to address at least the above-mentioned problems and/or disadvantages and to provide at least the advantages described below. Accordingly, an aspect of the present invention is to provide an apparatus and method for predicting a future channel status and for scheduling by using the predicted channel status in a wireless communication system.
Another aspect of the present invention is to provide an apparatus and a method for predicting a future channel status for each user and for assigning a scheduling priority to each user according to the predicted channel status in a wireless communication system.
Another aspect of the present invention is to provide an apparatus and a method for scheduling by considering mobility of a user in a wireless communication system.
Another aspect of the present invention is to provide an apparatus and a method for scheduling by assigning a high priority to a terminal of which a channel level has a possibility of becoming worse in a wireless communication system.
Another aspect of the present invention is to provide an apparatus and a method for scheduling by assigning a low priority to a terminal of which a channel level has possibility of becoming better in a wireless communication system.
According to an aspect of the present invention, a transmitting apparatus in a Broadband Wireless Access (BWA) system is provided. The apparatus includes a storage for buffering a predetermined number of pieces of past channel information with respect to all terminals; a predictor for predicting a future channel status for each terminal by using the predetermined number of pieces of past channel information; and a scheduler for scheduling by assigning a high priority to a terminal of which the future channel status has possibility of becoming worse, by using channel prediction values obtained from the predictor.
According to another aspect of the present invention, a transmitting method in a BWA system is provided. The method includes buffering a predetermined number of pieces of past channel information with respect to all terminal; predicting a future channel status for each terminal by using the predetermined number of pieces of past channel information; and scheduling by assigning a high priority to a terminal of which the future channel status has possibility of becoming worse, by using channel prediction values obtained from the predictor.
Before undertaking the DETAILED DESCRIPTION OF THE INVENTION below, it may be advantageous to set forth definitions of certain words and phrases used throughout this patent document: the terms “include” and “comprise,” as well as derivatives thereof, mean inclusion without limitation; the term “or,” is inclusive, meaning and/or; the phrases “associated with” and “associated therewith,” as well as derivatives thereof, may mean to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, or the like. Definitions for certain words and phrases are provided throughout this patent document, those of ordinary skill in the art should understand that in many, if not most instances, such definitions apply to prior, as well as future uses of such defined words and phrases.
For a more complete understanding of the present disclosure and its advantages, reference is now made to the following description taken in conjunction with the accompanying drawings, in which like reference numerals represent like parts:
Hereinafter, a method of the present invention will be described in which a future channel status is predicted for respective users, and a scheduling priority is assigned to each user by using the predicted channel status in a Broadband Wireless Access (BWA) system.
The BWA system is a communication system using Orthogonal Frequency Division Multiplexing (OFDM) or Orthogonal Frequency Division Multiple Access (OFDMA). Although the BWA system will hereinafter be described for example, the present invention may also apply to any other mobile communication systems as long as a terminal has mobility.
An OFDMA-Time Division Duplexing (OFDMA-TDD) system is a promising candidate for a next generation mobile communication system. In the OFDMA-TDD system, a frame with a specific length (e.g., 5 ms) is divided into an UpLink (UL) region and a DownLink (DL) region. Resource allocation information (e.g., MAP) for indicating UL/DL resources allocated to terminals is provided to a front portion of each frame. A data transmission period is constructed of slots including a sub-channel and an OFDMA symbol. A data size that can be transmitted in each slot varies depending on a channel status. That is, data modulation is carried out in different manners according to the channel status. The better the channel status, the higher a data transmission rate.
In an OFDMA-based cellular system, the channel status is divided into several states, and a suitable modulation level (e.g., MCS level) is defined for each state.
Now, mobility modeling and channel modeling of a terminal according to the present invention will be described.
First, the mobility modeling will be described. Examples of the mobility modeling for making a movement pattern of the terminal include a fluid model, a random movement model, a Markov model, etc. In the present invention, a Gauss-Markov model, which has a linear directivity and a smooth movement pattern, is assumed to be used. When directivity and speed are considered in the linear movement, the Gauss-Markov model is more appropriate in a metropolitan environment than other mobility models.
Next, the channel modeling will be described. The wireless channel modeling can show a channel status between a BS and a terminal in a realistic way. The wireless channel modeling may be used when one cell range is divided into several level zones each having a different data transmission rate and a modulation method. The modulation method Hk(t) for each zone can be expressed by Equation 1 below:
H
k(t)=√{square root over (HkP(t)·HkS)}(t). [Eqn. 1]
In Equation 1, HkP(t) denotes a path loss, and HkS denotes shadow fading. The path loss HkP(t) and the shadow fading HkS can be expressed as Equation 2 below:
H
k
P(t)=C·(max(rk(t),r0))−αC=10−2.86(path loss)
H
k
S(t)=10X
In Equation 2, rk(t) denotes a distance between the terminal and the BS, and r0 denotes a minimal distance between the terminal and the BS. Xk(t) and ρ(d) can be expressed as Equation 3 below:
X
k(t)=ρ(d)·Xk(t−1)+√{square root over (1−ρ2(d))}·X′
ρ(dk)=exp(−dk1n2/dcor). [Eqn. 3]
In Equation 3, Xk(t) denotes a ‘zero-mean Gaussian random process’, dk denotes a movement distance of the terminal, and dcor denotes a correlation distance of the shadow fading.
In the mobile communication system, the channel status resulted from the movement of the terminal is determined by a distance between the BS and the terminal and the fading. However, a channel change of the terminal is closely related to a speed. For example, the channel change resulted from the movement of the terminal within one cell range is shown in
Therefore, the BS can predict a future channel status by applying channel information to a time-series prediction method, wherein the channel information is periodically fed back from the terminal. That is, an average channel variation is computed by using a plurality of pieces of channel information which are recently fed back, and the future channel status is predicted by using a latest channel status and the computed channel variation. This can be expressed as Equation 4 below:
In Equation 4, Vi(tn) denotes a channel status for an ith terminal at an nth time.
The present invention is provided to control a scheduling priority of a terminal when DL scheduling is performed in a condition where a modulation method of the terminal may change according to the predicted channel state.
Referring to
Referring to
The feedback receiver 400 receives a plurality of pieces of channel information periodically fed back from terminals, and provides the pieces of channel information to the scheduler 402.
The scheduler 402 buffers, for each terminal, the channel information in a specific window size, computes an average channel variation by using a predetermined number of pieces of buffered channel information, and predicts a next channel status by using latest channel information and the average channel variation. Further, the scheduler 402 determines a scheduling priority of each terminal by using a channel status prediction value for each terminal, performs resource allocation according to the determined priority, and controls data transmission according to the result of the resource allocation. Detailed operations of the scheduler 402 will be described below in detail with reference to
The buffer 404 buffers data to be transmitted to each terminal, and outputs data to be transmitted to a specific terminal under the control of the scheduler 402. That is, the buffer 404 selects and outputs data of terminals to which resources are allocated during a current frame. The packet generator 406 assembles data received from the buffer 404 into a Packet Data Unit (PDU) of a Media Access Protocol (MAC) layer, and outputs the assembled data.
The encoder 408 encodes packets received from the packet generator 406 in a burst unit, and outputs the encoded data. An encoding rate of a burst is determined according to a scheduling result of the scheduler 402. For example, the encoder 408 may be a convolutional encoder, a turbo encoder, a Convolutional Turbo Code (CTC) encoder, or a Low Density Parity Check (LDPC) encoder.
The modulator 410 modulates symbols encoded by the encoder 408 in a predetermined modulation method, and thus generates modulated symbols. Examples of the modulation method used by the modulator 410 include Quadrature Phase Shift Keying (QPSK), a 16Quardrature Amplitude Modulation (QAM), and a 32QAM.
The resource mapper 412 maps complex symbols, which are provided from the modulator 410, to sub-carriers according to the scheduling result of the scheduler 402. Specifically, the resource mapper 412 maps the complex symbols to the sub-carrier, sorts the complex symbols in a frame unit, and sequentially outputs the sorted complex symbols on the basis of time synchronization.
The OFDM modulator 414 performs an Inverse Fast Fourier Transform (IFFT) operation on the complex symbols received from the resource mapper 412, and thus converts the complex symbols into sample data in a time domain. Then, the OFDM modulator 414 outputs sample data by appending a Cyclic Prefix (CP).
The DCA 416 converts the sample data received from the OFDM modulator 414 into sample data. The RF processor 418 includes a frequency synthesizer, a filter, etc. Further, the RF processor 418 converts a baseband signal received from the DCA 416 into an RF signal so that the signal can be transmitted. Thereafter, the converted RF signal is transmitted through an antenna.
Referring to
The channel information storage 500 buffers a plurality of pieces of channel information fed back from terminals in a predetermined window size. The buffered channel information is latest information. When new channel information is received, oldest channel information is discarded, and the new channel information is stored as the latest information.
The channel predictor 502 accesses the channel information storage 500 periodically or when a specific event occurs, and then reads the buffered channel information. Then, the channel predictor 502 computes a channel variation for each terminal by using the read channel information. Further, the channel predictor 502 predicts a next channel status by using latest channel information of each terminal and the computed channel variation. That is, the channel predictor 502 predicts the next channel status by performing time-series prediction as expressed by Equation (4) above.
The sub-group classifier 504 classifies the terminals into three sub-groups by using channel prediction values provided from the channel predictor 502. As shown in
With respect to all sub-groups generated by the sub-group classifier 504, the channel group classifier 506 classifies the terminals according to a channel level. For example, if the system provides N channel levels (or modulation levels), as shown in
As shown in
The resource allocator 510 performs resource scheduling according to the priority list created by the priority determining unit 508. That is, the scheduling is performed in such a way that the resource allocator 510 first allocates a resource to a terminal of which a future channel status has a possibility of becoming worse in a later time, so that data can be transmitted as much as possible before the channel level changes.
Referring to
In step 603, the BS accesses to the pieces of buffered channel information periodically or when a specific event occurs, and then computes an average channel variation for each terminal by using the pieces of buffered channel information. The BS predicts a next channel status (a future channel status) by using latest channel information for each terminal and the computed average channel variation. The BS may predict the future channel status by performing the time-series prediction as expressed by Equation (4) above.
Upon predicting the future channel status for each terminal, in step 605, the BS classifies the terminals into three sub-groups by using the predicted channel values. As shown in
In step 609, for each sub-group, the BS classifies the terminals according to a channel level. For example, if the system provides N channel levels (or modulation levels), as shown in
In step 611, the BS sorts the previously generated 3×N channel groups according to priority, and also sorts the terminals for each channel group according to a transmission delay value of a signal (Transmission (Tx) data), and thus determines a priority for each terminal. In step 613, the BS creates a resource allocation priority list (i.e., a user priority list) according to the determined priority.
In step 615, the BS performs scheduling according to the priority list, and then allocates a resource to each terminal. In this case, scheduling is carried out in such a way that a terminal of which a future channel status has a possibility of becoming worse is preferentially allocated with a resource, and thus data can be transmitted as much as possible before a channel level changes.
As shown in
In
Now, a simulation result will be described which has been performed to evaluate performance of the present invention.
First, a simulation environment is assumed to be as follows.
One sub-channel is used in an OFDMA-TDD system. One frame has a length of 5 ms. The number of sub-carriers is 8. The number of DL symbols is 12. The number of all slots within a frame is 96.
A channel level depending on a Signal to Noise Ratio (SNR) is defined as shown in Table 1 below.
A cell radius is 1 km. A future channel status is predicted by using three pieces of old channel information. A traffic model is assumed to be a Web traffic model (i.e., On-Off module) which is defined by an Institute of Electrical and Electronics Engineers (IEEE) 802.20 Mobile BWA (MBWA) system simulation (i.e., IEEE 802.20-03/66).
Referring to
The graph of
The graph of
As described above, the present invention shows a better performance than the conventional algorithms (i.e., Max C/I and PF) in terms of total throughput, delay, and jitter.
According to the present invention, a scheduling priority is determined by predicting a future channel status of a mobile terminal which is currently receiving a service, that is, scheduling is performed by predicting a channel at a time when data is transmitted. Therefore, a further effective scheduling can be achieved. In addition, as described with reference to
Although the present disclosure has been described with an exemplary embodiment, various changes and modifications may be suggested to one skilled in the art. It is intended that the present disclosure encompass such changes and modifications as fall within the scope of the appended claims.
Number | Date | Country | Kind |
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2007-0008419 | Jan 2007 | KR | national |