KR102074301B1 - Power control method for radio remote head using user mobility prediction - Google Patents

Abstract

A power control method of a remote wireless device reflecting a mobility prediction result of a user is provided. According to an embodiment of the present invention, the power control method of a remote wireless device comprises the steps of: predicting the remote wireless device to be serviced by each user terminal in a cell; and determining a remote wireless device to be activated and a remote wireless device to be deactivated by using information on the predicted remote wireless devices for each user terminal. According to the present invention, it is possible to control power of the remote wireless devices so that the overall energy consumption and a data transmission rate that users should receive are optimized.

Description

{Power control method for radio remote head using user mobility prediction}

The present invention relates to a power control method for a remote wireless device, and more particularly, to a power control method for a remote wireless device reflecting a user's movement prediction result.

As data demands of users using mobile data services increase, various 5G network environments are being studied. However, providing high data service requires a lot of energy consumption. In fact, as 75% of the total power consumed by mobile services is consumed by base stations for providing mobile services, researches for reducing energy consumption and efficient energy consumption have been actively conducted. For this purpose, interest in the field of reducing energy consumption by controlling power of base stations in a 5G network environment and increasing energy efficiency by reducing interference received from other base stations is increasing.

H-CRAN (Heterogeneous Cloud Access Networks), one of the network structures considered as 5G network environment, divides the existing base station into BBU (Base Band Unit) which is a signal processing stage and RRH (Radio Remote Head) which is a signal transmission / reception stage. . In addition, the BBU was clouded and centralized to form a BBU pool to efficiently manage resource allocation, and the RRH was distributed to allow users to be serviced closer to users. Base station power control in this environment is called RRH power control, and by deactivating the power of the RRH to reduce the energy consumption of the system and to improve the energy efficiency by adjusting the interference received by the user.

When controlling RRH power, the signal strength received by the user depends on which RRH is controlled, and the signal strength is related to the data rate. Users are serviced by the RRH that provides the most optimal signal, and then serviced by the RRH that provides the next best signal when the power is deactivated. Therefore, RRH power control requires not only minimizing the overall energy consumption but also considering the data rate that users must receive.

Therefore, there is a growing demand for a power control method of a remote wireless device in consideration of energy consumption and data rate.

United States Patent Application Publication No. 9,973,923 United States Patent Application Publication No. 9,813,204 Republic of Korea Patent Publication No. 10-1801074 Republic of Korea Patent Publication No. 10-2015-0126137

It is an object of one embodiment of the present invention to provide a method for controlling power supply of remote wireless equipment in consideration of energy consumption and data rate.

 According to an embodiment of the present invention, a method for controlling power of a remote wireless device through user mobility prediction includes estimating remote wireless devices to be serviced by each user terminal in a cell, and predicting the remote wireless devices for each user terminal. Determining information on the remote wireless device to be activated and the remote wireless device to be deactivated using the related information.

Predicting the remote wireless equipment to be serviced by each user terminal may include generating a list of remote wireless equipments that have been serviced for one day for each user terminal, and using the list, there is a probability that each user terminal is serviced at this time. And selecting the highest remote wireless devices.

Predicting the remote wireless equipment to be serviced by each user terminal includes storing the remote wireless equipments serviced for one day for each user terminal in the cell together with the time of service and a plurality of lists according to the time of service. Dividing into three time intervals, selecting the most frequently connected remote wireless equipment in each time interval as a representative base station of the corresponding time interval to create a representative history, and the most recent predetermined number at the present time in the representative history of each user terminal. Generating a pattern consisting of the remote wireless devices of the user; combining the generated patterns of each user for all remote wireless devices accessible in the cell; and using the combined pattern, for each user terminal. The user terminal with each remote wireless device in the cell May include the step of predicting the remote radio equipment with the highest probability with respect to the step, each of the user nodes to obtain the probability is determined in the following a remote wireless device to be connected to the user terminal.

In determining the remote wireless device to be activated and the remote wireless device to be deactivated, if the sum of the minimum resource blocks by the data demand of the user terminals in the cell is larger than the resource block capacity of the current cell, the resource block capacity of the cell If the remote radios are activated until they become smaller and the sum of the minimum resource blocks by the user's data demand in the cell is less than the current cell's resource block capacity, the energy efficiency of the entire system will no longer increase. Disable remote radios until

In one embodiment, in the step of activating the remote wireless devices, activate the remote wireless devices, the maximum number of users to be serviced at the optimal base station when activated, and in the step of deactivating the remote wireless devices, optimal when deactivated Deactivates the remote wireless devices in which the number of users to be serviced by the next-generation base station is reduced the most.

In one embodiment, for activated remote wireless equipment, gradient power may be used to calculate the transmit power.

According to one embodiment of the present invention, the power of the remote wireless equipment can be controlled to optimize the overall energy consumption and the data rate that the users should be provided with.

1 is a system diagram showing an example of a wireless communication system to which the power control method of the present invention is applied.
2 is a block diagram showing the internal configuration of the BBU, RRH and the user terminal.
3 is a flowchart illustrating a schematic configuration of a power control method of a remote wireless device according to an embodiment of the present invention.
4 is a flowchart illustrating a procedure of estimating an RRH to be serviced by each user terminal.
5 is a graph showing energy efficiency experiments using the San Francisco dataset.
6 is a graph showing energy efficiency experiments using the Beijing dataset.
FIG. 7 is a graph of energy efficiency in an environment with double user speeds in the San Francisco dataset.
FIG. 8 is a graph of energy efficiency in an environment with user speed quadrupled in a San Francisco dataset.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, in the following description and the accompanying drawings, detailed descriptions of well-known functions or configurations that may obscure the subject matter of the present invention will be omitted. In addition, it should be noted that like elements are denoted by the same reference numerals as much as possible throughout the drawings.

The terms or words used in the specification and claims described below should not be construed as being limited to the ordinary or dictionary meanings, and the inventors are properly defined as terms for explaining their own invention in the best way. It should be interpreted as meaning and concept corresponding to the technical idea of the present invention based on the principle that it can.

Therefore, the embodiments described in the specification and the drawings shown in the drawings are only the most preferred embodiments of the present invention, and do not represent all of the technical idea of the present invention, various modifications that can be substituted for them at the time of the present application It should be understood that there may be equivalents and variations.

In the accompanying drawings, some components are exaggerated, omitted, or schematically illustrated, and the size of each component does not entirely reflect the actual size. The invention is not limited by the relative size or spacing drawn in the accompanying drawings.

When any part of the specification is to "include" any component, this means that it may further include other components, except to exclude other components unless specifically stated otherwise. In addition, when a part is "connected" with another part, this includes not only the case where it is "directly connected" but also the case where it is "electrically connected" with another element between them.

Singular expressions include plural expressions unless the context clearly indicates otherwise. The terms "comprise" or "have" are intended to indicate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features, numbers, steps It is to be understood that the present disclosure does not exclude the possibility of the presence or the addition of any operation, a component, a part, or a combination thereof.

In addition, the term "part" as used herein refers to a hardware component such as software, FPGA or ASIC, and "part" plays certain roles. However, "part" is not meant to be limited to software or hardware. The “unit” may be configured to be in an addressable storage medium and may be configured to play one or more processors. Thus, as an example, a "part" refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, procedures, Subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functionality provided within the components and "parts" may be combined into a smaller number of components and "parts" or further separated into additional components and "parts".

DETAILED DESCRIPTION Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and like reference numerals designate like parts throughout the specification.

As the number of terminals receiving services increases, researches on location-based services have been conducted to increase the quality of services provided to users. A user in a city has a uniform mobility pattern by providing a specific pattern or discipline to the user's movement such as traffic lights and commute time. In particular, when using a vehicle such as a car can not be sudden change of speed or direction change and have a more uniform pattern.

In the present invention, in order to maximize energy efficiency, a base station to which a user is connected is predicted based on a Markov technique using a user mobility pattern. Based on the prediction result, power control of the RRH is performed, and transmission power is controlled using a gradient method. In order to consider the quality of service, the algorithm is performed so that the outage probability set to the maximum value is not exceeded, considering the outage probability. Outage probability is the percentage of users who do not meet the minimum Signal to Interference plus Noise Ratio (SINR) set by the system.

Energy efficiency is calculated as follows. First, calculate the total energy consumption in the cell. Total energy is the sum of the energy in the fronthaul link where the total RRHs and RRHs in the cell are connected to the BBU pool, and the backhaul link where the MBS and BBU pools are connected. In the active RRH, the energy consumed by data communication at the user terminal connected to the basic energy is calculated, and in the inactive RRH, the basic energy value in the sleep state is added. In the fronthaul link, the base energy value is calculated by adding the energy consumed by the data communication and the switch for each connected RRH, and the backhaul link adds a fixed energy value. Second, the sum of data rates of all users in a cell is obtained. Third, the energy efficiency is obtained by dividing the sum of data rates by the total energy consumption.

Hereinafter, a power control method for a remote wireless device according to an embodiment of the present invention will be described with reference to the drawings.

1 is a system diagram showing an example of a wireless communication system to which the power control method of the present invention is applied.

The present invention is directed to a single cell environment. The UEs 400 receive data service through one of the plurality of RRHs 300a and 300b. Each RRH (300a, 300b) is only a wireless communication transmission and reception function and data processing is performed in the BBU pool (200). The MBS may be directly connected to the user terminal 400 to process a voice service. The BBU pool 200 is connected to a core network 100. The core network 100 stores information of the RRH 300 serving the user terminal 400 in order to manage the quality of service and the handover of the user terminal 400, and uses the information to provide the method of the present invention. As a result, each user predicts an RRH to be serviced and determines an RRH to be activated and deactivated.

2 is a block diagram illustrating an internal configuration of the BBU 200, the RRH 300, and the user terminal 400. The terminal includes a transmitter 430 and a receiver 440 for wirelessly transmitting and receiving data with the RRH 300, and a processor 410 and a memory 420 for controlling overall operations. The RRH 300 includes a transmitter 310 and a receiver 320 for wireless communication with the user terminal 400, and the BBU 200 transmits data to the user terminal 400 through the RRH 300. And a processor 210 and a memory 220 for processing data received from the user terminal 400 through the RRH 300.

Next, a power control procedure of a remote wireless device according to an embodiment of the present invention will be described with reference to FIG. 3. 3 is a flowchart illustrating a schematic configuration of a power control method of a remote wireless device according to an embodiment of the present invention.

The core network 100 predicts the RRH 300 to be serviced by each user terminal 400 in a cell (S100). To this end, each user terminal generates and stores a list of RRHs 300 that have been serviced for one day, and selects the RRHs 300 having the highest probability that each user terminal is serviced at this point in time. This is done for all user terminals in the cell.

Next, the RRH to be activated and the RRH to be deactivated are determined using the information on the RRHs having the highest probability of receiving the service predicted for each user terminal (step S200). Determination of the RRH to be activated and the RRH to be deactivated is made by the following procedure. That is, if the sum of the minimum resource blocks (hereinafter referred to as 'RBs') by the data demand of the user in the cell is larger than the RB capacity of the current cell, the RRH ( Activate 300). In one embodiment, when activated, the RRH 300 is activated in which the number of users to be serviced at the optimal base station increases the most. If the sum of the minimum RBs by the user's data demand in the cell is smaller than the RB capacity of the current cell, the RRH 300 is deactivated until the energy efficiency of the entire system no longer increases. In one embodiment, the deactivation of the RRH (300), which is the most reduced when the number of users to be serviced in the next base station is not the optimal base station.

When the RRH to be activated and the RRH to be deactivated are determined, the core network 100 requests RRH information (ID and current state of the RRH) from the BBU pool 200 (step S300), and receives the RRH information from the BBU pool 200. (Step S400). Then, the RRH power control is performed through a standard procedure according to the result determined in step S200 (step S500).

Next, the step S100 of estimating the RRH to be serviced by each user terminal will be described in more detail with reference to FIG. 4.

First, each of the user terminals in the cell stores the RRHs serviced for one day as a list together with the service time (step S110). For example, each user terminal is stored in the form of {[09:10, RRH5], [09:25, RRH3], [09:31, RRH2], ...}.

Next, the list is divided into t time intervals according to the service time, and a representative history is generated by selecting the most frequently connected RRHs in each time interval as a representative base station of the corresponding interval (step S120). For example, 24 hours per day are divided into 24 intervals in 30 minute increments, and the most frequently connected RRHs are selected in each time interval. Representative history is constantly updated over time. Representative history of a user terminal in the case of dividing the day into 24 time intervals is as follows.

(RRH5, RRH5, RRH4, RRH4, RRH4, RRH5, RRH2, RRH5, RRH5, RRH3, RRH4, RRH4, RRH5, RRH5, RRH5, RRH5, RRH4, RRH5, RRH4, , RRH4, RRH5, RRH1}

After the representative history of each user terminal is constructed, the k most recent RRHs are extracted from the representative history of each user terminal at this point in time to generate a pattern (step S130). For example, the pattern pattern _k of the user terminal is configured as {RRH5, RRH1} (when k = 2).

를 셀 내의 모든 사용자 및 셀 내의 모든 접속 가능한 RRH에 대해서 만든다. 예를 들면

는 다음과 같이 구성될 수 있다(k=2인 경우).It then combines with each user's pattern for every RRH s accessible in the cell. That is, the pattern of RRH s

For every user in the cell and every accessible RRH in the cell. For example

May be configured as follows (when k = 2).

{RRH5, RRH1, RRH1}, {RRH5, RRH1, RRH2}, {RRH5, RRH1, RRH3}, {RRH5, RRH1, RRH4},... , {RRH5, RRH1, RRHS}

는 pattern _k 에 모든 셀 내의 모든 접속 가능한 RRH, 즉 RRH1~RRHS를 각각 추가한 것이다.Where S represents the total number of RRHs in the cell. In other words,

Adds to the pattern _k all accessible RRHs in all cells, that is, RRH1 to RRHS, respectively.

가 다음 시간 구간에 나타날 확률을 구한다(단계 S140). 이 확률은 예를 들면 수학식 1을 사용하여 구할 수 있다. Then, for all user terminals, the probability that each user terminal is connected to the RRH s in the next interval, ie, each

Calculates the probability of appearing in the next time interval (step S140). This probability can be obtained using, for example, Equation 1.

_s 는 리스트에서 RRH s 가 등장한 횟수를 나타내며, S는 총 RRH의 수를 나타낸다. 그리고

와

는 각각 히스토리에서 pattern _k 와

가 등장한 횟수이다. In Equation 1 | T _d | represents the size of the RRH list,

_s represents the number of times RRH s has appeared in the list, and S represents the total number of RRHs. And

Wow

Are pattern _k and

Is the number of appearances.

로 예측한다(단계 S150). 이 계산은 셀 내 모든 사용자 집합 U에 대해 수행된다.Through this equation, the RRH s with the highest probability

(Step S150). This calculation is performed for every user set U in the cell.

Next, the step of controlling the RRH power supply (S200) based on the predicted base station result for each user terminal will be described in detail. In this step, if the sum of the minimum resource blocks (RB) due to the data demand of the user in the cell is larger than the RB capacity of the cell, the RRH is activated until it is smaller than the RB capacity of the cell. If the opposite is true, deactivate the RRH until the energy efficiency of the entire system no longer increases. At this time, the selection of the RRH to control the power may be selected by the calculation of Equation 2.

는 예측된 RRH

에서 연결될 사용자 단말의 최소 데이터 요구량 의해 계산된 최소 요구 RB의 합을 셀의 RB용량으로 나눠 역수를 취한 것이다.

는 사용자 단말 u가 예측 RRH

에게 서비스 받을지에 대한 여부로, 1이면 서비스 받음을, 0이면 서비스 받지 않음을 의미한다.

를 전체 사용자 집합 U에 대해 계산하면 예측 RRH

가 서비스 할 것으로 예측되는 사용자 단말의 수가 나오게 된다. 즉,

는 RRH가 서비스 할 것으로 예상되는 사용자가 많으면 많을수록 값이 작아지고, RRH가 서비스 할 것으로 예상되는 최소 RB의 비율이 커질수록 값이 작아진다. 따라서

값이 클수록 비활성화 했을 때 최적의 기지국이 아닌 차선의 기지국에서 서비스 받을 사용자 단말의 수가 감소함을 뜻한다. 따라서 RRH 전원 제어에서는

값이 큰 RRH를 비활성화하고, 작은 RRH를 활성화한다.In this expression

Is the predicted RRH

The sum of the minimum required RBs calculated by the minimum data requirements of the UEs to be connected is divided by the RB capacity of the cell to obtain the inverse.

User terminal u predict RRH

Whether or not to receive the service, 1 means that the service is received, 0 means that the service is not received.

Is calculated over the entire set of users, U

The number of user terminals predicted to serve will be shown. In other words,

The smaller the number of users that the RRH is expected to serve, the smaller the value becomes, and the larger the ratio of the minimum RB that the RRH is expected to serve. therefore

The larger the value, the less the number of user terminals to be serviced by the next-generation base station instead of the optimal base station. So in RRH power control

Disable large RRHs and enable small RRHs.

For active RRHs, we can calculate the transmission power to maximize energy efficiency. The gradient method can be used for this calculation. In other words, the energy efficiency is partially divided by the transmission power, multiplied by a number α having a value between 0 and 1, and updated to the existing transmission power value. This update is repeated until a specific convergence condition is satisfied, and when the convergence condition is satisfied, the transmission power at that time is set to an optimal transmission power. The update may be performed by equation (3).

는 시간 t+1에서의 전송파워를, η는 시간 t에서의 에너지 효율을 전송 파워

를 기준으로 편미분한 값이다. In equation (3)

Is the transmission power at time t + 1 and η is the energy efficiency at time t.

It is a partial derivative.

In order to confirm the performance of the power control method of the remote wireless device of the present invention, a simulation using a taxi movement dataset in two cities of San Francisco and Beijing was conducted. In this simulation, the minimum data requirements of the user are applied to a Gaussian distribution and a uniform distribution. In addition, the simulation was conducted in the 2x and 4x environment to check the performance by the user's speed. Finally, the simulation was conducted in an environment where the number of RRHs was increased. Also, 'Activation algorithm in HetNet (A-HN)' considering the traffic load and the number of users serving for performance comparison [1] and 'Activation algorithm in H-CRAN (A-HC)' considering the total energy consumption and traffic load [2] is compared with the two techniques. In addition, a comparison with 'Full Activation (FA)', a model without RRH power control, was made to suggest a reference point.

[1] Ren, P .; Tao, M. A decentralized sleep mechanism in heterogeneous cellular networks with QoS constraints. IEEE Wirel. Commun. Lett. 2014, 3, 509-512.

[2] Lee, Y. L .; Wang, L .; Chuah, T. C .; Loo, J. Joint Resource Allocation and User Association for Heterogeneous Cloud Radio Access Networks. Proceedings of International Teletraffic Congress, Wuerzburg, Germany, 12-16 Sep. 2016, 87-93.

5A and 5B are graphs showing energy efficiency experiments using the San Francisco dataset, and FIGS. 6A and 6B are Beijing datasets. When the method of the present invention is compared with A-HN and A-HC, in FIGS. 5 and 6 (a) using Gaussian distribution, about 42-68% and 58-77%, and FIG. 5 and FIG. 6 (b) showed better performance of about 32-68% and 37-68%. And in all scenarios, the performance was 43-70% higher than FA.

7 and 8 are graphs of energy efficiency in an environment with varying user speeds in a San Francisco dataset. In FIG. 7, the speed is set at 2 times the speed and in FIG. 8 at 4 times the speed. The proposed algorithm compares A-HN and A-HC with about 18-64% and 24-64% in (a) using Gaussian distribution and about 10-60% and 19- in (b) using uniform distribution. 59% better performance. And in all scenarios, the performance increased by 30-67% compared to FA.

Although the foregoing description has been focused on the novel features of the invention as applied to various embodiments, those skilled in the art will appreciate that the apparatus and method described above without departing from the scope of the invention. It will be understood that various deletions, substitutions, and changes in form and detail of the invention are possible. Accordingly, the scope of the invention is defined by the appended claims rather than in the foregoing description. All modifications within the scope of equivalents of the claims are included in the scope of the present invention.

100 core network,
200 BBU pool,
300 remote wireless equipment (RRH),
400 user terminal (UE).

Claims (6)

A first step of predicting remote wireless equipment to be serviced by each user terminal in the cell in the next time interval from data on the remote wireless equipment to which each user terminal in the cell is most frequently connected for each time interval;
A second step of determining a remote wireless device to be activated and a remote wireless device to be deactivated by using information about the predicted remote wireless devices for each user terminal;
Equipped with
The second step is
If the sum of the minimum resource blocks by the data demand of the user terminals in the cell is greater than the resource block capacity of the current cell, activate the remote radio equipment until it is smaller than the resource block capacity of the cell,
If the sum of the minimum resource blocks by the user's data demand in the cell is less than the current cell's resource block capacity, then disabling the remote wireless devices until the total system energy efficiency no longer increases. How to control the power of wireless equipment.
delete The method of claim 1, wherein the first step
Storing a list of remote wireless devices serviced for one day for each user terminal in the cell together with the time of service;
Dividing the list into a plurality of time intervals according to a service time, and selecting a remote base station which is most frequently connected in each time interval as a representative base station of the corresponding time interval to create a representative history;
Generating a pattern composed of a predetermined number of remote wireless devices most recent at this time in the representative history of each user terminal;
Combining each generated user pattern for all remote wireless devices accessible within the cell;
Using the combined pattern, for each user terminal, obtaining a probability that each user terminal is connected with each remote wireless device in the cell in the next interval;
Predicting the remote wireless device having the greatest probability for each user terminal as the next remote wireless device of the corresponding user terminal.
Including, the method of controlling power of a remote wireless equipment. delete The method of claim 1,
In the step of activating the remote wireless devices, activate the remote wireless devices that, when activated, increase the number of users to be served at the optimal base station,
In the step of deactivating the remote wireless devices, deactivating the remote wireless devices in which the number of users to be serviced by the sub-base station that is not the optimal base station is most reduced when the remote wireless devices are deactivated. The method of claim 1,
Calculating a transmission power using a gradient method for the activated remote wireless device.

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