CN102547898A - Switch optimizing method for femtocell under non-closed mode - Google Patents

Abstract

The invention discloses a femtocell switching optimization method in a non-closed mode, comprising: after the femtocell is re-deployed, it enters the speed threshold self-learning stage, and the switching decision adopts a femtocell priority switching strategy combined with a differentiated hysteresis Hys_qos, and only uses the remaining resources to satisfy user services The required target cell initiates a handover request. The method of the invention comprehensively considers user mobility characteristics, service characteristics, and cell load conditions to realize switching optimization, reduces unnecessary repeated switching, reduces switching blocking rate, and improves user experience satisfaction.

Description

A switching optimization method of femtocell in non-closed mode

technical field

The present invention relates to the technical field of mobile communication, in particular to a cell handover optimization method for a femtocell (femtocell base station) in an LTE system in a non-closed access mode

Background technique

Femtocell base station (Femtocell), also known as home base station (HeNB, Home enodeB), is an ultra-miniature mobile base station launched in response to the development of mobile communication and the trend of broadband in recent years. It is a low-power wireless access point, working in the authorized frequency band, using the IP protocol, connecting and accessing through the user's existing ADSL, LAN and other broadband circuits, and remotely realizing the interconnection from the IP network to the mobile core network by a dedicated gateway intercommunication. Its size is similar to that of an ADSL modem, and it has the characteristics of easy installation, automatic configuration, automatic network planning, and plug-and-play. For operators, femtocell can save operation and maintenance costs, and at the same time, quickly and effectively improve indoor coverage problems while ensuring the quality of indoor air interfaces. For users, the adoption of femtocell means that they can obtain indoor high-quality voice services and higher-speed broadband data service experience, and at the same time users can enjoy lower tariffs.

At present, femtocells are mainly deployed in private places such as families, groups, and companies as exclusive resources for private users, or deployed in schools, shopping malls, and large stores as an effective supplement to the insufficient coverage of macrocellular wireless communication systems. Correspondingly, femtocell mainly has three access modes: open mode, closed mode, and hybrid mode. Open mode allows access to all users. Closed mode allows access only to authorized users, such as family members or group members. The hybrid mode also allows all users to access, but users belonging to CSG enjoy preferential or preferential conditions.

As an important mobility management function, handover directly affects the performance of the entire system. With the large-scale deployment of femtocells, new requirements are put forward for handover processing methods, and traditional handover methods can no longer adapt to the new features of femtocells.

Femtocell provides users with tariff discounts. Considering the impact of tariffs on user preferences, femtocell should be selected as the target cell for handover in priority during the handover process. The traditional handover algorithm, especially the handover algorithm used in the same-frequency deployment scenario, requires that the signal quality of the neighboring cell is definitely better than that of the local cell and there is a certain hysteresis margin before triggering event reporting. However, the transmission power of the femtocell is much smaller than that of the macrocell. In this case, the traditional handover algorithm has the disadvantage of being unable to trigger the femtocell priority handover in time.

In addition, considering the limited coverage of femtocells, a speed threshold should be set to optimize the switching algorithm to prevent users moving at high speeds from quickly switching back and forth between femtocells and macrocells, so as to reduce unnecessary system overhead. On the other hand, the femtocell-first handover algorithm is likely to cause a large number of users to flood the femtocell in advance, resulting in overloading of the cell, resulting in a decrease in the overall user experience of the network. In view of this, the handover algorithm should be further optimized in full consideration of the remaining resources of the cell and the service characteristics of the user.

Contents of the invention

Purpose of the invention: the main purpose of the present invention is to provide a femtocell-first handover method, and this method combines user moving speed, user service characteristics, and remaining resources of the cell to adapt to the new requirements of femtocell for handover processing.

The design concept of the present invention is that, after the femtocell is redeployed, it enters the speed threshold self-learning stage, and the handover decision adopts the femtocell priority handover strategy combined with the differentiated hysteresis Hys_qos, and only initiates a handover request to the target cell whose remaining resources meet the user's business needs. The method of the invention comprehensively considers user mobility characteristics, service characteristics, and load status of cells to realize switching optimization, reduces unnecessary repeated switching, reduces switching blocking rate, and improves user experience satisfaction.

Technical scheme of the present invention: the switching optimization method of femtocell (femtocell type base station) under the non-closed mode of the present invention, comprises the steps:

(1) The femtocell first enters the self-learning phase of the speed threshold after each re-deployment and power-on, and determines the maximum moving speed of the user that is allowed to initiate a handover request to the femtocell with the dwell time as a reference.

(2) The network configures handover measurement parameters, and the UE detects the reference signal reception strength and reference signal reception quality of the adjacent femtocell, user speed information, service status information, speed threshold and load status of the adjacent femtocell.

(3) The UE analyzes the user's mobility characteristics and service characteristics, specifically, when the user's movement speed exceeds the speed threshold of a femtocell in a neighboring cell, it is forbidden to initiate a handover request to the femtocell. When the mobile speed of the user is lower than the speed threshold, the differentiated hysteresis Hys_qos is selected in combination with the user's service QOS requirements, and the next step is entered.

(4) The UE analyzes the reference signal reception strength and reference signal reception quality of femtocells in neighboring cells, adopts the differentiated hysteresis Hys_qos, takes femtocell priority as the handover strategy, and adds femtocells in neighboring cells that meet the handover conditions to the target cell list in an orderly manner. The event is reported to the source cell; at the same time, the user speed information, service status information, speed threshold and load status of the target femtocell are reported to the source cell, and the next step is entered.

(5) The source cell uses the handover measurement information reported by the UE to analyze the available load of the target femtocell, specifically when the remaining resources of the femtocell meet the needs of user services, initiate a handover request to the femtocell; otherwise, prohibit the handover request to the femtocell Initiate a switch request.

It can be seen from the above technical solutions that the method of the present invention comprehensively considers user mobility characteristics, service characteristics, and load conditions of cells to realize handover optimization. Compared with the prior art, the beneficial effect is that unnecessary repeated switching is reduced, the blocking rate of switching is reduced, and user experience satisfaction is improved.

Description of drawings

FIG. 1 is a flowchart of switching optimization according to an embodiment of the present invention;

FIG. 2 is a detailed disassembly schematic diagram of step 101 of the switching optimization flow chart of the embodiment of the present invention;

FIG. 3 is a detailed disassembly schematic diagram of step 103 of the switching optimization flow chart of the embodiment of the present invention;

FIG. 4 is a detailed disassembly schematic diagram of step 104 of the switching optimization flow chart of the embodiment of the present invention;

FIG. 5 is a detailed disassembly schematic diagram of step 105 of the handover optimization flow chart of the embodiment of the present invention.

Detailed ways

The preferred embodiments will be described in detail below in conjunction with the drawings, but the scope of protection of the present invention is not limited to the embodiments.

Embodiment: a switching optimization method of femtocell under a kind of non-closed mode, Fig. 1 is the general flowchart of this embodiment, comprises the following steps:

Step 101: After the femtocell is turned on, it completes the self-study of the speed threshold. As shown in Figure 2, the femtocell enters the speed threshold learning stage after starting up, and takes the dwell time as the judgment standard (for example: the dwell time is 10s) to determine the speed threshold of the femtocell in the corresponding installation scenario after a period of learning .

Step 102: The UE periodically monitors and collects some information of the serving cell and neighboring cells, including the received reference signal strength RSRP, the reference signal received quality RSRQ, the round-trip time of the signal RTT, the signal angle of arrival AoA, the service QOS level QCI, the neighbor remaining resources in the area.

Step 103: The UE estimates the distance between the user and the base station by measuring RTT: d=c×RTT/2, combines AoA to obtain an estimate of the user's position, and compares the UE's position changes at two measurement times to obtain an estimate of the user's movement speed. As shown in FIG. 3 , only when the speed of the user is not greater than the speed threshold of the adjacent femtocell, the UE is allowed to initiate a handover request to the femtocell shown. The UE determines differentiated hysteresis based on the service resource type and service priority by measuring the service QOS level QCI. Determining Hys_qos specifically follows the following principles: GBR services are higher than Non-GBR services, and when the resource types are the same (that is, both are GBR or Non-GBR), services with higher priority are higher than services with lower priority.

Step 104: UE compares whether the handover measurement result satisfies the femtocell priority handover condition, triggers A3 event when Mn-Hys_qos>Ms+off, and triggers A4 event when Mn-Hys_qos>femto_first_threshold. Where Mn is the RSRP or RSRQ of the neighboring cell, Ms is the RSRP or RSRQ of the source cell, off is the cell-specific offset, and femto_first_threshold is the femtocell priority handover threshold.

As shown in FIG. 4 , when the source cell is a macrocell and the neighboring cell is a femtocell, the UE reports an A4 event, triggering a femtocell-first handover decision. In other cases, when reporting the A3 event, the UE needs to compare the signal strength or signal quality of the source cell with the necessary handover threshold handover_threshold to prevent unnecessary handover.

Usually, there are more than one cell that meets the trigger condition, and the system needs to select the most suitable one from many candidate cells as the handover target cell. Therefore, the quality of the cells is evaluated, and a list of target cells is generated according to the pros and cons. According to the RSRP and RSRQ reported by the measurement, the following cell quality evaluation algorithm cell_performance is used:

$\mathrm{<span\; class="notranslate">\; Cell</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; value</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; w</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; rsrp</span>}<span\; class="notranslate">\; \&times;</span>\frac{\mathrm{<span\; class="notranslate">\; mea</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; rsrp</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; index</span>}}{\mathrm{<span\; class="notranslate">\; MAX</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; RSRP</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; INDEX</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; w</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; rsrq</span>}<span\; class="notranslate">\; \&times;</span>\frac{\mathrm{<span\; class="notranslate">\; mea</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; rsrq</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; index</span>}}{\mathrm{<span\; class="notranslate">\; MAX</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; RSRQ</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; INDEX</span>}}$

w_rsrp+w_rsrq=1

w_rsrp and w_rsrq are the weights of RSRP and RSRQ respectively. The larger the value of Cell_value, the better the quality of the candidate cell, and the handover should be given priority.

Step 105: Analyze the load situation of the target cell by comparing the remaining resources of the target cell, the remaining resources of the target cell are represented by remaining resource blocks:

$\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; \&Delta;T</span>}}<span\; class="notranslate">\; -</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; reserver</span>}}<span\; class="notranslate">\; ,</span>& \mathrm{<span\; class="notranslate">\; for\; new\; call</span>}\\ {\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; \&Delta;T</span>}}<span\; class="notranslate">\; -</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; ,</span>& \mathrm{<span\; class="notranslate">\; forhandoff</span>}\end{array}\right.$

为ΔT的测量周期内映射的资源数总和，N_ΔT为基站在测量周期内能分配的资源总数

N _ΔT is the total number of resources that the base station can allocate in the measurement period

The resource reservation strategy is adopted to improve the priority of the handover service, and R _reserver is a reserved resource.

When the remaining resources of the target cell cannot meet the user's business needs, delete the cell from the target cell list; when the target cell list is not empty, take a new target cell for analysis until a target cell that meets the load requirements is found and initiates a handover ask.

Step 106: If the femtocell is re-deployed, return to Step 101; otherwise, use the speed threshold obtained in Step 101 to analyze the measurement report result of the UE.

Those skilled in the art will appreciate that, although specific embodiments have been described herein for purposes of explanation, various changes may be made without departing from the spirit and scope of the invention. Accordingly, the invention is not to be limited except as by the appended claims.

Claims (7)

1. the switching optimization method of femtocell under the non-closed mode is characterized in that comprising the steps:

(1) femtocell formula base station femtocell is after redeploying start at every turn, at first the self study speed threshold;

(2) be that user terminal is monitored the femtocell of adjacent area and collected handoff parameter by UE, these parameters comprise: the speed threshold and the load state that comprise reference signal receiving intensity RSRP, Reference Signal Received Quality RSRQ, user velocity information, business state information, signal RTT two-way time, signal angle of arrival AoA, professional QOS rank QCI, adjacent area femtocell;

(3) mobility of UE analysis user and service feature are specially:

When the user moving speed of this UE surpasses certain adjacent area femtocell speed threshold, then forbid initiating handoff request to this femtocell; When the user moving speed of this UE was no more than certain adjacent area femtocell speed threshold, the sluggish Hys_qos in conjunction with user's professional QOS requires to choose differentiation got into step 4);

(4) analyze adjacent area femtocell loading condition by UE:

UE analyzes adjacent area femtocell reference signal receiving intensity and Reference Signal Received Quality; Adopt the sluggish Hys_qos of differentiation; Be preferably switchover policy with femtocell, the adjacent area femtocell that satisfies switching condition is added the Target cell tabulation, report the cell-of-origin through trigger event; And, get into step 5) simultaneously to speed threshold and the load state of cell-of-origin report of user velocity information, business state information, Target cell femtocell;

(5) cell-of-origin utilizes the handover measurement information that UE reports, the load state of evaluating objects sub-district femtocell, and the load state of Target cell femtocell is characterized by the surplus resources of Target cell; Be specially, take, then initiate handoff request to this Target cell femtocell when the surplus resources of Target cell femtocell can satisfy customer service; Take when the surplus resources of Target cell femtocell can not satisfy customer service, then forbid initiating handoff request to this Target cell femtocell;

(6), then return step 1), otherwise continue to use the measurement and report result that step 1) gained speed threshold is analyzed UE if femtocell redeploys.

2. according to the switching optimization method of femtocell under the described a kind of non-closed mode of claim l, it is characterized in that:

In the step (1), femtocell is judgement standard with the residence time, confirms that through study femtocell installs the speed threshold under the scene in correspondence.

3. according to the switching optimization method of femtocell under the described a kind of non-closed mode of claim l; It is characterized in that: in the step (3); User moving speed information is united sign by signal RTT two-way time and signal angle of arrival AoA; UE estimates to obtain the distance of user and base station: d=c * RTT/2 through measure R TT, in conjunction with the estimation that AoA obtains customer location, compare two change in location of measuring moment UE and obtain the estimation to user movement speed.

4. the switching optimization method of femtocell under a kind of non-closed mode according to claim 1; It is characterized in that: in the step 3); Professional QOS in conjunction with the user requires the sluggish Hys_qos that chooses differentiation to be; UE confirms the sluggish Hys_qos of differentiation through measuring the rank QCI of professional QOS with service resources type and service priority;

Confirm that the principle that the sluggish Hys_qos of differentiation specifically follows is: GBR is professional is higher than the Non-GBR business, and when resource type was identical, when promptly being all GBR or Non-GBR, the business that priority is high was higher than the low business of priority.

5. the switching optimization method of femtocell under a kind of non-closed mode according to claim 1 is characterized in that: in the step (4), the method that judgement adjacent area femtocell satisfies switching condition is:

By UE relatively the result of handover measurement whether satisfy the preferential condition of switching of femtocell, when Mn-Hys_qos＞Ms+off, trigger the A3 incident, when Mn-Hys_qos＞femto_first_threshold, trigger the A4 incident; Wherein Mn is adjacent cell reference signals receiving intensity or Reference Signal Received Quality, and Ms is cell-of-origin reference signal receiving intensity or Reference Signal Received Quality, and off is a Cell Individual Offset, and femto_first_threshold is the preferential handoff threshold of femtocell.

When the cell-of-origin is macrocell, when adjacent sub-district was femtocell, UE reported the A4 incident, triggered the preferential switch decision of femtocell; Under other situations, UE reports the A3 incident need cell-of-origin signal strength signal intensity or signal quality and necessary handoff threshold handover_threshold comparison be prevented inessential switching.

6. the switching optimization method of femtocell under a kind of non-closed mode according to claim 5; It is characterized in that: in the step (4), the method that generates the Target cell tabulation is that one of selection is only as switching target small area from candidate cell; Then need carry out quality evaluation to the sub-district; And by good and bad ordering, the method for quality evaluation is, according to the reference signal receiving intensity and the Reference Signal Received Quality of measurement and report; Adopt cell quality assessment algorithm cell_performance to assess, the cell_performance algorithm is following:

w_rsrp+w_rsrq＝1

W_rsrp, w_rsrq are respectively the weight of reference signal receiving intensity and Reference Signal Received Quality; The quality of big more this candidate cell of explanation of the value of Cell_value is good more, should pay the utmost attention to switching.

7. the switching optimization method of femtocell under a kind of non-closed mode according to claim 1; It is characterized in that: in the step (4); Characteristic is in the said step 5); The loading condition of surplus resources evaluating objects sub-district femtocell through the comparison object sub-district, the surplus resources of Target cell is represented by surplus resources piece R:

The number of resources summation of shining upon in the measuring period for Δ T, N _{Δ T}Be the resource sum that femtocell can distribute in measuring period, adopt resource reservation policy to improve service switchover priority, R _ReserverIt is reserved resource;

When can not satisfying customer service, the surplus resources of Target cell takes, with the deletion from the Target cell tabulation of this sub-district; When Target cell tabulation be empty, then get new Target cell analyze up to discovery meet Target cell femtocell load request Target cell and initiate handoff request.

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