Communication energy efficiency optimization method based on QoS differentiation

Abstract

The present invention provides a communication energy efficiency optimization method based on QoS differentiation, comprising the following steps: Step 1, a baseband unit obtains the terminal distribution code UEm-n of the terminal UE distributed under each remote unit and the service characteristics Sm-n of each terminal, wherein m is the remote unit number, taking values ​​of 1, ..., M; n is the number of the terminal distributed under each remote unit, taking values ​​of 1, ..., N; Step 2, the baseband unit closes the remote unit without the preset characteristic A service demand, and opens the remote unit with the preset characteristic A service demand. The present invention performs intelligent start and stop of the remote unit according to the difference in QoS characteristics of the user terminal through the perception of the access service, thereby effectively optimizing the energy efficiency of the access network.

Description

Technical Field

[0001] The present invention belongs to the field of communications, and in particular relates to a communication energy efficiency optimization method based on QoS differentiation. Background Art

[0002] With the rapid development of mobile communications, the demand for traffic is increasing day by day. At the same time, the construction of communication networks is in full swing. The number of mobile communication base stations has increased exponentially, and the demand for the total power consumption of base stations is increasing. Reducing power consumption and reducing electricity bills have become issues of concern to access network owners. From the perspective of industry attributes, the companies that care about this issue are mainly companies with their own networks, such as companies in the power system industry, companies in the coal mining industry, operators, etc.

[0003] At present, the industry mainly has the following solutions to the problem of energy conservation and emission reduction in the mobile communications field:

[0004] Introducing highly integrated designs and replacing old high-energy-consuming traditional equipment with low-energy-consuming equipment to achieve energy conservation;

[0005] Introduce new generation energy-saving technologies such as cloud computing platforms. Through cloud platform construction, gradually move the communication network service system to the cloud platform. Through cloud platform resource sharing, effectively reduce the number of server equipment, thereby achieving the goal of energy saving;

[0006] The existing network adopts a distributed base station architecture, which divides the traditional base station equipment into two functional modules according to its functions. The baseband, main control, transmission, clock and other functions of the base station are integrated into a module called the baseband unit BBU (Base Band Unit), which is small in size and has a very flexible installation location; the radio frequency such as the transceiver and power amplifier are integrated into another module called the remote radio frequency module, which is also called the remote radio unit RRU (Remote Radio Unit). The remote unit and the baseband unit are connected by optical fiber to form a new distributed base station solution.

[0007] The remote unit is responsible for terminal coverage, and its number is closely related to traffic demand and coverage area. With the explosive growth of traffic and the ubiquitous development of mobile communications, the number of remote units will increase exponentially, and the energy consumption of remote units will account for the vast majority of the energy consumption of the access network. However, as analyzed above, the existing technology focuses on energy consumption control of the access network on the one hand from product design (corresponding to the first solution), and on the other hand from energy consumption control of equipment in the computer room during product application (such as core side equipment and base station baseband pool equipment, corresponding to the second solution), but fails to control energy consumption from remote devices that occupy a considerable share, which leads to the need to improve the energy consumption optimization effect of the entire network. Therefore, proposing a system based on energy consumption control of remote units to achieve energy consumption optimization of the access network is a problem to be solved in the industry. Summary of the invention

[0008] The technical problem to be solved by the present invention is: to overcome the shortcomings of the existing technology and provide a communication energy efficiency optimization method based on QoS differentiation. By perceiving the access service and according to the differences in QoS characteristics of user terminals, the remote unit is intelligently started and stopped, thereby effectively optimizing the energy efficiency of the access network.

[0009] The technical solution adopted by the present invention to solve the problems existing in the prior art is:

[0010] The present invention provides a communication energy efficiency optimization method based on QoS differentiation, comprising the following steps:

[0011] Step 1, the baseband unit obtains the terminal distribution code UEm-n of the terminal UE distributed under each remote unit and the service characteristics Sm-n of each terminal, where m is the remote unit number, and takes values ​​of 1, ..., M; n is the number of the terminal distributed under each remote unit, and takes values ​​of 1, ..., N;

[0012] Step 2: The baseband unit turns off the remote unit without the preset characteristic A service requirement, and turns on the remote unit with the preset characteristic A service requirement;

[0013] In step 1, the service characteristics Sm-n include any one or a combination of QoS characteristics and custom characteristics, and the custom characteristics include at least one network transmission performance indicator. The specific method for obtaining the terminal distribution code UEm-n distributed under each remote unit is:

[0014] Step 1.1, the baseband unit obtains the measurement information of each terminal and the position coordinates of each remote unit, and the position coordinates of the remote unit are entered in a preset manner;

[0015] Step 1.2, the baseband unit calculates the location coordinates of each terminal based on the positioning algorithm and the measurement information;

[0016] Step 1.3, the baseband unit calculates the remote unit closest to each terminal, and determines the terminal to be distributed in the nearest remote unit;

[0017] In step 2, the preset characteristic A is a subset of the service characteristic Sm-n, including at least one network transmission performance indicator in the service characteristic Sm-n. The shutdown operation refers to configuring the remote unit to be in a low power consumption state, and the low power consumption state refers to a state in which energy consumption is reduced compared to the normal operating mode. The startup operation refers to configuring the remote unit to return to the normal operating mode.

[0018] Preferably, the measurement information of each terminal in step 1.1 includes any one or a combination of uplink measurement information and downlink measurement information of each terminal; the measurement quantity specifically included in the measurement information is determined by the positioning algorithm in step 1.2.

[0019] Preferably, in step 2, the remote unit without service demand for preset characteristic A means that all terminals distributed under the remote unit do not have service demand for preset characteristic A; the remote unit with service demand for preset characteristic A means that among the terminals distributed under the remote unit, there is at least one terminal with service demand for preset characteristic A.

[0020] Preferably, the specific method for the baseband unit subsystem and the remote unit subsystem to cooperate with each other to optimize energy efficiency also includes a method of executing step 1 and step 2 based on a preset time period.

[0021] Preferably, the specific method for the baseband unit subsystem and the remote unit subsystem to cooperate with each other to optimize energy efficiency also includes a method for executing step 1 and step 2 in a conditional triggering manner.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] The present invention perceives the access services and, based on the differences in user QoS characteristics, provides on-demand services for areas with high priority service demands and best-effort services for areas with ordinary service demands. Based on this, remote units are started and stopped intelligently, thereby achieving effective energy consumption control for remote units with a relatively large energy consumption in the access network and effectively optimizing the energy efficiency of the access network. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0025] Figure 1 It is a schematic flow chart of the method of the present invention;

[0026] Figure 2 It is a schematic diagram of the system structure of the present invention;

[0027] Figure 3 It is a schematic diagram of the implementation of the present invention. DETAILED DESCRIPTION

[0028] In order to make the technical solutions and beneficial effects of the present invention clearer, the embodiments of the present invention are further explained in detail below.

[0029] like Figure 1 and Figure 2 As shown, the present invention provides a communication energy efficiency optimization system based on service level differentiation, including: a baseband unit subsystem and a remote unit subsystem, and the functions of each subsystem are as follows:

[0030] Baseband unit subsystem: receives terminal measurement information and calculates the terminal location, and then calculates the distribution of each terminal in each remote unit based on the remote unit location information and terminal location information; and according to the service characteristics, closes the remote unit without the preset characteristic A service demand, and opens the remote unit with the preset characteristic A service demand;

[0031] Remote unit subsystem: responsible for communicating with the baseband unit subsystem and responding to start and stop operations;

[0032] The specific method for the baseband unit subsystem and the remote unit subsystem to cooperate with each other to optimize energy efficiency is:

[0033] Step 1: The baseband unit obtains the terminal distribution code UEm-n of the terminal UE distributed under each remote unit and the service characteristics S of each terminal m-n , where m is the remote unit number, which takes values ​​from 1, ..., M; n is the number of the terminal distributed under each remote unit, which takes values ​​from 1, ..., N;

[0034] Step 2: The baseband unit turns off the remote units that do not have the preset characteristic A service requirement, and turns on the remote units that have the preset characteristic A service requirement.

[0035] The preset characteristic A service demand refers to the service demand within a certain time period.

[0036] Most existing communication base stations adopt a distributed base station architecture. The distributed base station divides the traditional base station equipment into two functional modules according to its functions. The baseband, main control, transmission, clock and other functions of the base station are integrated in a module called the baseband unit BBU (Base Band Unit). The baseband unit is small in size and has a very flexible installation location; the radio frequency such as the transceiver and power amplifier are integrated in another module called the remote radio frequency module, and the radio frequency unit RRU (Remote Radio Unit) is installed at the antenna end. The radio frequency unit and the baseband unit are connected by optical fiber to form a new distributed base station solution.

[0037] Distributed base station architecture is divided into indoor and outdoor types. Outdoor coverage is composed of BBU+RRU mentioned above; indoor coverage is composed of BBU+HUB+PRRU. HUB is a multi-port repeater (hub) that plays the role of aggregating data and converting formats. PRRU is pico+RRU, where pico means small or micro. RRU and PRRU are remote units, and BBU is baseband unit.

[0038] In step 1, the specific method for obtaining the terminal distribution codes UEm-n distributed under each remote unit is:

[0039] Step 1.1, the baseband unit obtains the measurement information of each terminal and the position coordinates of each remote unit, and the position coordinates of the remote unit are entered in a preset manner;

[0040] Step 1.2, the baseband unit calculates the location coordinates of each terminal based on the positioning algorithm and the measurement information;

[0041] Step 1.3: The baseband unit calculates the remote unit closest to each terminal, and determines the terminal to be distributed under the nearest remote unit.

[0042] The measurement information of each terminal in step 1.1 includes any one or a combination of uplink measurement information and downlink measurement information of each terminal;

[0043] The measurement quantity specifically included in the measurement information is determined by the positioning algorithm in step 1.2.

[0044] The positioning algorithm includes any one or a combination of fingerprint positioning method, TDOA positioning method, AOA+TA positioning method.

[0045] The measurement quantities involved in the fingerprint positioning method are received power, TDOA (time difference of arrival), the measurement quantity involved is timing advance, and the measurement quantities involved in AOA+TA (angle of arrival + timing advance) are angle of arrival and timing advance.

[0046] The fingerprint localization algorithm is a set of algorithms proposed based on the complex indoor environment and the different signal strength information formed by signal reflection and refraction at different locations. The fingerprint algorithm can make good use of the signal information formed by reflection and refraction. The fingerprint signal strength database is first generated offline, and the position distance is calculated through a set of RSSI values ​​(Received Signal Strength Indication) actually measured in online positioning.

[0047] TDOA positioning is a method of positioning using time difference. By measuring the time it takes for a signal to reach a monitoring station, the distance of the signal source can be determined. Using the distance from the signal source to each monitoring station (using the monitoring station as the center and the distance as the radius to draw a circle), the position of the signal can be determined. However, absolute time is generally difficult to measure. By comparing the absolute time difference of the signal reaching each monitoring station, a hyperbola with the monitoring station as the focus and the distance difference as the major axis can be drawn. The intersection of the hyperbola is the position of the signal.

[0048] The AOA positioning method mainly measures the arrival angle of the signal between the mobile station and the base station. The ray formed with the base station as the starting point must pass through the mobile station, and the intersection of the two rays is the position of the mobile station. This method only requires two base stations to determine the estimated position of the MS; the TA+AoA positioning method is usually only used for network-based positioning. The main reason is that AoA can only be measured by the base station, that is, all the measurement quantities related to this positioning method are provided by the base station. These measurement quantities can be provided by the base station to the positioning server, so the purpose of positioning can be achieved by supporting network-based positioning. Therefore, this also brings an advantage of this method, that is, for terminals that do not support positioning services, they can also be positioned by this method.

[0049] For the AOA+TA positioning algorithm, the measured quantity corresponds to the angle and time advance; for the fingerprint positioning algorithm, the measured quantity corresponds to the received power; for the TDOA positioning algorithm, the measured quantity corresponds to the time advance.

[0050] In step 1, the service characteristic S m-n It includes any one of QoS characteristics and custom characteristics or a combination of the two; the custom characteristics include at least one network transmission performance indicator.

[0051] QoS (Quality of Service) refers to a network's ability to use various basic technologies to provide better service capabilities for specified network communications. It is a network security mechanism and a technology used to solve problems such as network delays and congestion. The QoS characteristics are used to repair some minor flaws in the network data transmission process, such as resource type (GBR, non-GBR, delayed GBR, etc.), packet error rate (10^-1, 10^-2, etc.), etc., which are not limited here.

[0052] GBR (Guaranteed Bit Rate) Guaranteed bit rate. The so-called GBR refers to the minimum bit rate guaranteed by the system. Even in the case of tight network resources, the corresponding bit rate can be maintained. On the contrary, non-GBR means that in the case of network congestion, the service (or bearer) needs to bear the requirement of reducing the rate. Since Non-GBR bearers do not need to occupy fixed network resources, they can be established for a long time. GBR bearers are generally established only when needed.

[0053] In step 2, the remote unit without service requirements of preset characteristic A means that all terminals distributed under the remote unit do not have service requirements of preset characteristic A;

[0054] The remote unit with service requirements of preset characteristic A refers to the terminal distributed under the remote unit, among which there is at least one terminal with service requirements of preset characteristic A.

[0055] In step 2, the preset characteristic A is the service characteristic S m-n A subset of m-n At least one network transmission performance indicator.

[0056] In step 2, the shutdown operation refers to configuring the remote unit to be in a low power consumption state, where the low power consumption state refers to a state where energy consumption is reduced compared to a normal operating mode;

[0057] The start-up operation refers to configuring the remote unit to return to normal operating mode.

[0058] The low power consumption state includes shutting down some modules (such as shutting down the RF link amplifier), shutting down some time-frequency resources (such as sending only some broadcast channels and not sending other channels), lowering the transmission power (such as reducing the overall transmission power by 3db), etc., and there is no restriction here.

[0059] The specific method for the baseband unit subsystem and the remote unit subsystem to cooperate with each other to optimize energy efficiency also includes a method of executing step 1 and step 2 based on a preset time period.

[0060] The specific method for the baseband unit subsystem and the remote unit subsystem to cooperate with each other to optimize energy efficiency also includes a method for executing step 1 and step 2 in a conditional triggering manner.

[0061] After the preset conditions are triggered, steps 1 and 2 are executed to start and stop the remote units. The preset conditions include that the value obtained by dividing the number of remote units turned on by the number of access terminals is greater than threshold 1, the value obtained by dividing the number of remote units turned on by the total traffic throughput is greater than threshold 2, etc.

[0062] The following is a specific example to describe the specific implementation of the communication energy efficiency optimization method based on QoS differentiation:

[0063] Example: Figure 3 As shown, the present implementation includes four remote units, namely, remote unit 1, remote unit 2, remote unit 3, and remote unit 4. There are four terminal UEs accessing the present network, namely, UE1, UE2, UE3, and UE4. The present embodiment adopts fingerprint positioning to calculate the position of the terminal based on the uplink signal receiving power (measurement information). The present embodiment adopts a periodic triggering scheme, that is, according to a preset period (2 seconds in the present embodiment), the remote unit start / stop determination and start / stop operation are triggered once per period. In addition, in the present embodiment, the service characteristics are described by resource types, and the resource types are divided into GBR (guaranteed bit rate) and non-GBR. The preset characteristic A described in the present embodiment corresponds to the GBR characteristic, that is, if the UE is configured with a GBR service, it means that the UE has a preset characteristic A service requirement. If the UE is configured with a non-GBR service, it means that the UE does not have a preset characteristic A service requirement. When a certain start / stop cycle triggering moment arrives, the operation is performed as follows:

[0064] The baseband module calculates the position coordinates of the four UEs based on the fingerprint method according to the uplink received power measurement of each remote unit about the four UEs. The baseband module determines the remote unit where the UE is distributed by calculating the distance between the UE and the remote unit based on the position coordinates of the four remote units. After calculation, it is determined that at the triggering moment, UE1 is closest to remote unit 1, UE2 is closest to remote unit 2, UE3 and UE4 are closest to remote unit 4, and there is no UE under remote unit 3. Therefore, it is considered that UE1 is distributed under remote unit 1, UE2 is distributed under remote unit 2, and UE3 and UE4 are distributed under remote unit 4;

[0065] Next, the baseband unit determines that UE1 and UE3 carry GBR services, and UE2 and UE4 carry non-GBR services according to the service characteristics of the four UEs (see Table 1 for details, whether they carry GBR). Since all UEs distributed under remote unit 2 carry non-GBR services, and there is no UE distributed under remote unit 3, this cycle triggers remote units 2 and 3 to be in the off mode, and since UEs with GBR service requirements are distributed under remote units 1 and 4, remote units 1 and 4 are determined to be in the on mode;

[0066] Next, the baseband unit sends information to the remote units that remote units 1 and 4 are in the on mode and remote units 2 and 3 are in the off mode, and each remote unit performs its own on or off operation according to the instructions of the baseband unit.

[0067] After the method of the present invention is adopted, the remote unit is started and stopped intelligently. Since the remote unit where the UE of the GBR service is located is in the turned-on state, the UE of the GBR service can enjoy good coverage service and the corresponding rate is not affected. However, since the remote unit where the UE of the non-GBR service is located is in the turned-off state, it can only be provided with service by the surrounding remote units. Since the coverage is relatively weak, its rate is reduced, but since it is a non-GBR service, there is no rate guarantee requirement, therefore, its use is not affected. However, in the entire access network system, two of the four remote units can be turned off, thereby effectively saving energy consumption and achieving the purpose of optimizing the energy consumption of the access network.

[0068] It can be seen from the present invention that by adopting the method of the present invention, through the perception of access services and according to the differences in user QoS characteristics, on-demand services are provided for high-priority service demand areas, and best-effort services are provided for ordinary-level service demand areas. Based on this, remote units are intelligently started and stopped, thereby achieving effective energy consumption control for remote units that account for a relatively large proportion of energy consumption in the access network, and effectively optimizing the energy efficiency of the access network.

[0069] Table 1

[0070]

[0071] The embodiments of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of ordinary technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. A communication energy efficiency optimization method based on QoS differentiation, characterized in that: The steps include: Step 1: The baseband unit obtains the terminal distribution code UE of the terminal UE distributed under each remote unit m-n and the service characteristics S of each terminal m-n , where m is the remote unit number, which takes values ​​from 1, ..., M; n is the number of the terminal distributed under each remote unit, which takes values ​​from 1, ..., N; Step 2: The baseband unit turns off the remote unit without the preset characteristic A service requirement, and turns on the remote unit with the preset characteristic A service requirement; In step 1, the service characteristic S m-n Including any one or a combination of QoS characteristics and custom characteristics, wherein the custom characteristics include at least one network transmission performance indicator, and the specific method for obtaining the terminal distribution code UEm-n distributed under each remote unit is: Step 1.1, the baseband unit obtains the measurement information of each terminal and the position coordinates of each remote unit, and the position coordinates of the remote unit are entered in a preset manner; Step 1.2, the baseband unit calculates the location coordinates of each terminal based on the positioning algorithm and the measurement information; Step 1.3, the baseband unit calculates the remote unit closest to each terminal, and determines the terminal to be distributed in the nearest remote unit; In step 2, the preset characteristic A is the service characteristic S m-n A subset of S, including service characteristics S m-n At least one network transmission performance indicator is measured, the closing operation refers to configuring the remote unit to be in a low power consumption state, wherein the low power consumption state refers to a state in which energy consumption is reduced compared to the normal operating mode, and the opening operation refers to configuring the remote unit to return to the normal operating mode.

2. The communication energy efficiency optimization method based on QoS differentiation according to claim 1 is characterized in that: The measurement information of each terminal in step 1.1 includes any one or a combination of uplink measurement information and downlink measurement information of each terminal; The measurement quantity specifically included in the measurement information is determined by the positioning algorithm in step 1.

2.

3. The communication energy efficiency optimization method based on QoS differentiation according to claim 1 is characterized in that: In step 2, the remote unit without service requirements of preset characteristic A means that all terminals distributed under the remote unit do not have service requirements of preset characteristic A; The remote unit with service requirements of preset characteristic A refers to the terminal distributed under the remote unit, among which there is at least one terminal with service requirements of preset characteristic A.

4. The communication energy efficiency optimization method based on QoS differentiation according to claim 1 is characterized in that: The specific method for the baseband unit subsystem and the remote unit subsystem to cooperate with each other to optimize energy efficiency also includes a method of executing step 1 and step 2 based on a preset time period.

5. The communication energy efficiency optimization method based on QoS differentiation according to claim 1 is characterized in that: The specific method for the baseband unit subsystem and the remote unit subsystem to cooperate with each other to optimize energy efficiency also includes a method for executing step 1 and step 2 in a conditional triggering manner.

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