CN102215082A - Midamble shift allocation method and device - Google Patents
Midamble shift allocation method and device Download PDFInfo
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- CN102215082A CN102215082A CN2010101443687A CN201010144368A CN102215082A CN 102215082 A CN102215082 A CN 102215082A CN 2010101443687 A CN2010101443687 A CN 2010101443687A CN 201010144368 A CN201010144368 A CN 201010144368A CN 102215082 A CN102215082 A CN 102215082A
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Abstract
The invention provides a midamble shift allocation method, which comprises the following steps of: according to levels of a tree graph indicating predefined mapping relationships between midamble shifts and channel codes, setting allocation priorities of the midamble shifts of each level in the tree graph; when the midamble shift is allocated to a channel, determining a spreading factor of the channel code allocated to the channel according to channel resources seized by the channel; searching for the tree graph indicating the predefined mapping relationships between the midamble shifts and the channel codes according to the spreading factor, determining the midamble shifts available for the spreading factor, and selecting all currently idle midamble shifts from the available midamble shifts; and selecting the midamble shift with the highest allocation priority from all the currently idle midamble shifts, and allocating the selected midamble shift to the channel. The invention also provides a midamble shift allocation device. By the scheme provided by the invention, the midamble shift can be easier to allocate to the channel with a relatively lower spreading factor.
Description
Technical field
The present invention relates to the mobile communication technology field, particularly high-speed packet access technology relates in particular to a kind of distribution method and device of training sequence deviation.
Background technology
At present, in high-speed packet access (HSPA), introduced multi-user (MU) multiple-input and multiple-output (MIMO) technology.That is: at up direction, a plurality of high speed uplink bags insert (HSUPA) subscriber equipment (UE) can share identical scheduling enhanced dedicated channel physical uplink channel (E-PUCH) resource; At down direction, a plurality of high-speed downstream bags insert (HSDPA) UE can share identical scheduling high-speed Physical Downlink Shared Channel (HS-PDSCH) resource.These UE that share identical scheduling resource are (for up, be to share identical scheduling E-PUCH resource, for descending, be to share identical scheduling HS-PDSCH resource) have different training sequence deviation (Midamble Shift), described training sequence deviation is as the foundation of the wireless channel of distinguishing these UE.
In the TD-SCDMA system, there are two kinds of training sequence deviation methods of salary distribution: the special default training sequence deviation method of salary distribution (being designated hereinafter simply as first method of salary distribution) and the default training sequence deviation method of salary distribution (being designated hereinafter simply as second method of salary distribution).Under these two kinds of training sequence deviation methods of salary distribution, the form with tree graph in 3GPP agreement TS 25.221 of the mapping relations between each training sequence deviation and the channel code is defined.
Fig. 1 has provided an example of the training sequence deviation of prior art and the mapping relations tree graph between the channel code.Wherein, the total K=8 of training sequence deviation.Among Fig. 1, symbol m represents training sequence deviation, the sequence number of the numeral training sequence deviation in the bracket of the m upper right corner; Symbol c represents channel code, the numeral spreading factor in the c lower right corner, the numeral channel code sign indicating number in the bracket of the upper right corner number.
In the tree graph, be positioned at the spreading factor minimum of the top channel code of tree graph as shown in Figure 1, be SF=1; The spread spectrum of channel code that is positioned at the tree graph second layer is because SF=2; The spreading factor that is positioned at the channel code of the 3rd layer of tree graph is SF=4; The spreading factor that is positioned at the channel code of the 4th layer of tree graph is SF=8; The spreading factor that is positioned at the channel code of tree graph layer 5 (lowermost layer) is SF=16.
As can be seen from Figure 1, top (the spreading factor SF=1) for tree graph has only available training sequence deviation, i.e. a m
(1)The second layer of tree graph (spreading factor SF=2), available training sequence deviation number is increased to 2, is respectively m
(1)And m
(5)The 3rd layer (SF=4) of tree graph, available training sequence deviation number is 4, is respectively m
(1), m
(3), m
(5)And m
(7)Below by that analogy.
When giving a channel allocation training sequence deviation, at first, determine to distribute to the spreading factor of the channel code of this channel according to the channel resource of this channel occupancy; Then, in the channel code that adopts this spreading factor, select the channel code of a free time to distribute to this channel.
When giving this channel allocation training sequence deviation, in each training sequence deviation corresponding, select the training sequence deviation of a free time to distribute to this channel with this channel code according to first method of salary distribution.
For example, with K in the sub-district
mIndividual training sequence deviation is divided into the M group, and the group number of M group training sequence deviation is respectively 0,1 ..., M-1.Work as K
m=2 o'clock, M=2; Work as K
m∈ 4,6,8,10,12,14, and during 16}, M=2 or 4.K
mHave with the value combination of M: 1+7 * 2=15 kind.
For every kind of K
mValue combination with M, in the M group training sequence deviation, m ∈ { 0,1, ..., each training sequence deviation that comprises in the M-1} group training sequence deviation and the mapping relations between Orthogonal Variable Spreading Factor OVSF (OVSF) channel code are defined with special default training sequence deviation configuration mode in the 3GPP agreement.
Work as K
UEWhen≤M UE shares identical scheduling resource, need to give each UE to distribute different training sequence deviation.For K
UEK UE among the individual UE can organize at M and select m in the training sequence deviation
kThe group training sequence deviation.Then according to shared OVSF channel code and the m of scheduling resource that distributes to this UE
kEach training sequence deviation that group comprises in the training sequence deviation and the mapping relations between the OVSF channel code determine to distribute to the training sequence deviation of this UE.K in addition
UE-1 UE can not select m again
kThe group training sequence deviation.Here, m
kOne may value be: m
k=k-1.
When giving this channel allocation training sequence deviation according to second method of salary distribution, according to the shared channel code of the scheduling resource of distributing to this UE, inquire about the mapping relations between each training sequence deviation and OVSF channel code under the default training sequence deviation configuration mode, determine the training sequence deviation of the unique correspondence of this channel code, if this training sequence deviation is not assigned to other UE or up channel as yet, then this training sequence deviation is distributed to this UE; If this training sequence deviation is assigned with, distribute training sequence deviation then can't for this UE, perhaps adopt other modes to redistribute channel code and training sequence deviation to UE.
When the training sequence deviation of allocated channel according to the method described above, following unreasonable situation can appear:
High-speed shared information channel (HS-SICH) takies the channel code of 1 SF=16, with the interior channel code of time slot 1 (TS1) number is that the channel code of the SF=16 of free time of 1 is distributed to HS-SICH.Under the default training sequence deviation method of salary distribution, the training sequence deviation of this channel code correspondence is m
(1)(first training sequence deviation).
After giving HS-SICH distributing channel mode and spreading factor in the manner described above, just can not give the channel code of other channel configurations SF=1 at TS1.Because the training sequence deviation of the channel code correspondence of SF=1 is similarly m
(1)And m
(1)Be assigned to HS-SICH.
So the above-mentioned method of channel allocation channel code and training sequence deviation of at will giving in the channel code of free time is also unreasonable.Tree graph shown in Figure 1 is analyzed as can be seen, and the number of times that different training sequence deviation occur in this tree graph is inconsistent.For example, the first training sequence deviation m
(1)Each layer all occurs in tree graph, has occurred altogether 6 times (wherein occurring twice at the 5th layer); The 5th training sequence deviation has occurred 5 times, and the 3rd and the 7th training sequence deviation has then occurred respectively 4 times, and the 2nd, the 4th, the 6th and the 8th training sequence deviation then occurs respectively 3 times.Occurrence number is many more, shows that the possibility that this training sequence deviation is assigned with is big more, and just the scarcity of this training sequence deviation is just high more.This tree graph also has following characteristics: the training sequence deviation that higher level occurs is bound to occur at lower level; Level is high more, and the number of optional training sequence deviation is few more.
If comparatively rare training sequence deviation is distributed to the bigger channel of spreading factor, then for the less channel of spreading factor, optionally training sequence deviation just is subjected to certain limitation, even can cause there is not optional training sequence deviation at all.
Summary of the invention
The invention provides a kind of distribution method and device of training sequence deviation, make the easier training sequence deviation that is assigned to of the less channel of spreading factor.
The embodiment of the invention has proposed a kind of distribution method of training sequence deviation, comprises the steps:
A, according to the level of the mapping relations tree graph between predefined training sequence deviation and the channel code, setting is arranged in the distribution priority of described tree graph training sequence deviation at all levels, and the distribution priority that is positioned at the training sequence deviation of higher level will be lower than the distribution priority of the training sequence deviation that is positioned at lower level; If a training sequence deviation occurs repeatedly in tree graph, then the level of this training sequence deviation is the highest level in the level that this training sequence deviation occurred;
B, when giving a channel allocation training sequence deviation, determine to distribute to the spreading factor of the channel code of this channel according to the channel resource of this channel occupancy;
C, search mapping relations tree graph between predefined training sequence deviation and the channel code according to described spreading factor, determine the training sequence deviation that this spreading factor can be used, and in described available training sequence deviation, select the training sequence deviation of all current free time; And
D, in the training sequence deviation of described current free time, select to have the training sequence deviation that best result is joined priority, and it distributed to described channel.
It is characterized in that described steps A comprises:
A1, judge whether described tree graph also has the training sequence deviation of undefined distribution priority in the anterior layer, if, the level number that then will work as anterior layer is defined as the distribution priority of described training sequence deviation, and described training sequence deviation is labeled as defines distribution priority; When carrying out first, when anterior layer is the top of tree graph;
A2, judge whether when anterior layer be the lowermost layer of tree graph, if, end step A then, otherwise, following one deck of tree graph as working as anterior layer, and is returned steps A 1.
Preferably, for given training sequence deviation sum, the number of the mapping relations tree graph between described predefined training sequence deviation and the channel code is 1.
Preferably, for given training sequence deviation sum K, the number of the mapping relations tree graph between described predefined training sequence deviation and the channel code equals the packet count M of training sequence deviation.
Preferably, step C is described to search mapping relations tree graph between predefined training sequence deviation and the channel code according to described spreading factor, determines that the training sequence deviation that this spreading factor can be used is:
Search each tree graph in the described M tree graph according to described spreading factor, determine the training sequence deviation that this spreading factor can be used in each tree graph, the set of the training sequence deviation that this spreading factor can be used in described each tree graph can be with a subclass of training sequence deviation set for this spreading factor.
The embodiment of the invention also proposes a kind of distributor of training sequence deviation, comprising:
The tree graph module is used to store the mapping relations tree graph between training sequence deviation and the channel code;
Distribute priority that module is set, the level that is used for the tree graph stored according to described tree graph module, setting is arranged in the distribution priority of described tree graph training sequence deviation at all levels, and the distribution priority that is positioned at the training sequence deviation of higher level will be lower than the distribution priority of the training sequence deviation that is positioned at lower level; If a training sequence deviation occurs repeatedly in tree graph, then the level of this training sequence deviation is the highest level in the level that this training sequence deviation occurred;
The spreading factor module is used for when giving a channel allocation training sequence deviation, determines to distribute to the spreading factor of the channel code of this channel according to the channel resource of this channel occupancy;
Search module, be used for the spreading factor definite according to described spreading factor module, search the tree graph of storing in the described tree graph module, determine the training sequence deviation that this spreading factor can be used, and in described available training sequence deviation, select the training sequence deviation of all current free time; And
Distribution module, be used for the training sequence deviation of searching the selected current free time of module described, according to the distribution priority that the training sequence deviation of module is set from described distribution priority, selection has the training sequence deviation that best result is joined priority, and it is distributed to described channel.
Preferably, described distribution priority is provided with module and further comprises:
First judging unit is used for judging whether described tree graph also has the training sequence deviation of undefined distribution priority when anterior layer, if the training sequence deviation of described undefined distribution priority is sent to the unit is set; When carrying out first, when anterior layer is the top of tree graph;
The unit is set, is used for being defined as the distribution priority of the training sequence deviation of being received when the level number of anterior layer, and described training sequence deviation is labeled as defines distribution priority, index signal is sent to second judging unit in the back that is finished;
Second judging unit is used to judge whether that working as anterior layer is the lowermost layer of tree graph, if send index signal to output unit, otherwise, notify first judging unit with following one deck of tree graph as working as anterior layer;
Output unit is used for after the index signal of receiving from second judging unit, exports the distribution priority that the defined training sequence deviation in unit is set to described distribution module.
Preferably, for given training sequence deviation sum K, stored the mapping relations tree graph between M training sequence deviation and the channel code in the described tree graph module, M equals the packet count of training sequence deviation.
Preferably, the described module of searching is used for searching each tree graph in M the tree graph that described tree graph module stores according to described spreading factor, determine the set of the training sequence deviation that this spreading factor can be used in each tree graph, the set of the training sequence deviation that this spreading factor can be used in described each tree graph can be with a subclass of training sequence deviation set for this spreading factor; In can gathering with training sequence deviation, described this spreading factor selects the training sequence deviation of all current free time.
As can be seen from the above technical solutions, to training sequence deviation corresponding distribution priority is set, the distribution priority of comparatively rare training sequence deviation is lower, makes that comparatively rare training sequence deviation can remain as much as possible, supplies with the less channel of spreading factor and uses.
Description of drawings
Fig. 1 is the training sequence deviation stipulated in the 3GPP agreement and the mapping relations tree graph between the channel code;
Fig. 2 is the flow chart of the distribution method of the training sequence deviation of embodiment of the invention proposition;
Fig. 3 is the block diagram of the distributor of the training sequence deviation of embodiment of the invention proposition.
Embodiment
The allocation flow of the training sequence deviation that the embodiment of the invention proposes as shown in Figure 2, this flow process is applicable to each training sequence deviation in the default training sequence deviation method of salary distribution and undefined each tree graph of the special default training sequence deviation method of salary distribution, specifically comprises the steps:
Step 201:, the distribution priority that is arranged in tree graph training sequence deviation at all levels is set according to the tree graph level.That is:
The pairing training sequence deviation of channel code that is positioned at tree graph top (spreading factor is SF=1) has minimum distribution priority, represents to be positioned at the distribution priority of the training sequence deviation of this layer with the level number 1 of this layer.
The pairing training sequence deviation of channel code that is positioned at the tree graph second layer (spreading factor is SF=2) has time minimum distribution priority, represents to be positioned at the distribution priority of the training sequence deviation of this layer with the level number 2 of this layer.
The pairing training sequence deviation of channel code that is positioned at the 3rd layer of tree graph (spreading factor is SF=4) has the 3rd low distribution priority, represents to be positioned at the distribution priority of the training sequence deviation of this layer with the level number 3 of this layer.
The pairing training sequence deviation of channel code that is positioned at the 4th layer of tree graph (spreading factor is SF=8) has the 4th low distribution priority, represents to be positioned at the distribution priority of the training sequence deviation of this layer with the level number 4 of this layer.
The pairing training sequence deviation of channel code that is positioned at tree graph layer 5 (spreading factor is SF=16) has the highest distribution priority, represents to be positioned at the distribution priority of the training sequence deviation of this layer with the level number 5 of this layer.
If a training sequence deviation is positioned at many levels simultaneously, then the highest level that occurs with this training sequence deviation defines the distribution priority of this training sequence deviation.In other words, be positioned at training sequence deviation definition distribution priority at all levels when giving according to level order from high to low, after the distribution priority of a training sequence deviation is defined, even in other layers, this training sequence deviation still occurs, no longer re-define the distribution priority of this training sequence deviation.
According to the distribution priority definition method of above-mentioned training sequence deviation, the channel code of SF=1 (channel code of the most rare channel code or granularity maximum) corresponding training sequence deviation under the special default training sequence deviation method of salary distribution or the default training sequence deviation method of salary distribution has minimum distribution priority; The corresponding training sequence deviation of the channel code of SF=2 (channel code that more rare channel code or granularity are bigger) has time minimum distribution priority in these two kinds of training sequence deviation methods of salary distribution; The corresponding training sequence deviation of the channel code of SF=4 (the moderate and moderate channel code of granularity of number) has the 3rd low distribution priority; The training sequence deviation of channel code (channel code of channel code that number is maximum or the granularity minimum) correspondence of the channel code of SF=8 (channel code that number is time maximum or granularity time minimum channel code) and SF=16 has that inferior best result is joined priority and best result is joined priority.
Mapping relations tree graph between above-mentioned predefined training sequence deviation and the channel code can be undefined each tree graph of the default training sequence deviation method of salary distribution or undefined each tree graph of the special default training sequence deviation method of salary distribution.
When adopting the default training sequence deviation method of salary distribution, has only a unique tree graph under each K value.
When adopting the special default training sequence deviation method of salary distribution, K training sequence deviation is divided into M to be organized, and the value of the total K of training sequence deviation and the packet count M of training sequence deviation has a lot of combinations.To the combination of value of K and M, the training sequence deviation that comprises in every group is different for each.Therefore, for a pair of given K value and the value combination of M value, there be M tree graph.(the individual tree graph of 1≤m≤M) defines each training sequence deviation that comprises in the m group and the mapping relations between Orthogonal Variable Spreading Factor OVSF (OVSF) channel code to m.The definition mode of the distribution priority of training sequence deviation is identical in each tree graph in this M tree graph.
Step 202: when giving a channel allocation training sequence deviation, determine to distribute to the spreading factor of the channel code of this channel according to the channel resource of this channel occupancy.Described channel includes but not limited to HS-SICH, Physical Random Access Channel (PRACH), uplink special physical channel channels such as (ULDPCH).
Step 203: search mapping relations tree graph between predefined training sequence deviation and the channel code according to described spreading factor, determine the training sequence deviation that this spreading factor can be used.
When adopting the default training sequence deviation method of salary distribution, has only a unique tree graph under each K value.Describedly search mapping relations tree graph between predefined training sequence deviation and the channel code according to spreading factor, determine that the training sequence deviation that this spreading factor can be used is: search the unique tree graph under the corresponding K value, determine the training sequence deviation that this spreading factor can be used.
When adopting the special default training sequence deviation method of salary distribution, each K value time corresponding M tree graph.Describedly search mapping relations tree graph between predefined training sequence deviation and the channel code according to spreading factor, determine that the training sequence deviation that this spreading factor can be used is: search each tree graph in the described M tree graph according to described spreading factor, determine the training sequence deviation that this spreading factor can be used in each tree graph, the set of the training sequence deviation that this spreading factor can be used in described each tree graph can be with a subclass of training sequence deviation set for this spreading factor.
Step 204: the training sequence deviation of in described available training sequence deviation, selecting all current free time.
Step 205: in the training sequence deviation of described current free time, select to have the training sequence deviation that best result is joined priority, and it is distributed to described channel.
When having more than one of training sequence deviation that best result joins priority, select a training sequence deviation at random, this training sequence deviation and the pairing channel code of this training sequence deviation are distributed to this channel.
Defining the distribution priority of each training sequence deviation according to the method described above, and when giving channel allocation channel code and training sequence deviation, just can avoid distributing to the training sequence deviation of the channel code that the training sequence deviation of a channel code will be more rare and give the problem that takies based on the distribution priority of each training sequence deviation.In other words, the problem that taken by not rare channel code of the training sequence deviation of having avoided rare channel code correspondence.
The embodiment of the invention also proposes a kind of distributor of training sequence deviation, and its block diagram installs 300 and comprises as shown in Figure 3:
When adopting the default training sequence deviation method of salary distribution, has only a unique tree graph under each K value.301 of described tree graph modules need the tree graph under the described K value of storage.Perhaps store each tree graph under each probable value of K.When concrete the application,, from the tree graph of storage, extract the tree graph of described K value according to the K value.
When adopting the special default training sequence deviation method of salary distribution, each K value time corresponding M tree graph.Described tree graph module 301 is used to store M tree graph under given K value and the given M value.Perhaps, determine all possible value combination of K and M, M tree graph under the value of store every kind of K and M makes up.When concrete the application,, from the tree graph of storage, extract M tree graph under described K value and the M value according to K value and M value.
Distribute priority that module 302 is set, be used for level according to the tree graph of described tree graph module 301 storages, setting is arranged in the distribution priority of described tree graph training sequence deviation at all levels, and the distribution priority that is positioned at the training sequence deviation of higher level will be lower than the distribution priority of the training sequence deviation that is positioned at lower level; If a training sequence deviation occurs repeatedly in tree graph, then the level of this training sequence deviation is the highest level in the level that this training sequence deviation occurred;
Spreading factor module 303 is used for when giving a channel allocation training sequence deviation, determines to distribute to the spreading factor of the channel code of this channel according to the channel resource information of this channel occupancy;
Preferably, described distribution priority is provided with module 302 and can further include:
First judging unit is used for judging whether described tree graph also has the training sequence deviation of undefined distribution priority when anterior layer, if the training sequence deviation of described undefined distribution priority is sent to the unit is set; When carrying out first, when anterior layer is the top of tree graph;
The unit is set, is used for being defined as the distribution priority of the training sequence deviation of being received when the level number of anterior layer, and described training sequence deviation is labeled as defines distribution priority, index signal is sent to second judging unit in the back that is finished;
Second judging unit is used to judge whether that working as anterior layer is the lowermost layer of tree graph, if send index signal to output unit, otherwise, notify first judging unit with following one deck of tree graph as working as anterior layer;
Output unit is used for after the index signal of receiving from second judging unit, exports the distribution priority that the defined training sequence deviation in unit is set to described distribution module.
When adopting the special default training sequence deviation method of salary distribution, the described module 304 of searching is used for searching each tree graph in M the tree graph of described tree graph module 301 storages according to described spreading factor, determine the set of the training sequence deviation that this spreading factor can be used in each tree graph, the set of the training sequence deviation that this spreading factor can be used in described each tree graph can be with a subclass of training sequence deviation set for this spreading factor; In can gathering with training sequence deviation, described this spreading factor selects the training sequence deviation of all current free time.
The distribution method of the training sequence deviation that proposes according to the present invention, among Fig. 1, m
(2), m
(4), m
(6), m
(8)Has the highest distribution priority 4, m
(3)And m
(7)Has the distribution priority 3, m
(5)Has the distribution priority 2; m
(1)Has minimum distribution priority 1.When giving the HS-SICH Resources allocation, because HS-SICH takies the channel code of 1 SF=16, from m
(2), m
(4), m
(6), m
(8)Training sequence deviation of middle selection is distributed this HS-SICH.Distribute to the channel code of the channel code of HS-SICH for training sequence deviation correspondence in of selection as Fig. 1.Such as, select m
(2)Giving HS-SICH, the channel code of then distributing to HS-SICH is that channel code number is the channel code of 3 or 4 SF=16.Under this mode, m
(1), m
(5), m
(3), m
(7)Can be used to distribute more rare channel code.
The above only is preferred embodiment of the present invention, and is in order to restriction the present invention, within the spirit and principles in the present invention not all, any modification of being made, is equal to replacement, improvement etc., all should be included within the scope of protection of the invention.
Claims (9)
1. the distribution method of a training sequence deviation is characterized in that, comprises the steps:
A, according to the level of the mapping relations tree graph between predefined training sequence deviation and the channel code, setting is arranged in the distribution priority of described tree graph training sequence deviation at all levels, and the distribution priority that is positioned at the training sequence deviation of higher level will be lower than the distribution priority of the training sequence deviation that is positioned at lower level; If a training sequence deviation occurs repeatedly in tree graph, then the level of this training sequence deviation is the highest level in the level that this training sequence deviation occurred;
B, when giving a channel allocation training sequence deviation, determine to distribute to the spreading factor of the channel code of this channel according to the channel resource of this channel occupancy;
C, search mapping relations tree graph between predefined training sequence deviation and the channel code according to described spreading factor, determine the training sequence deviation that this spreading factor can be used, and in described available training sequence deviation, select the training sequence deviation of all current free time; And
D, in the training sequence deviation of described current free time, select to have the training sequence deviation that best result is joined priority, and it distributed to described channel.
2. method according to claim 1 is characterized in that steps A comprises:
A1, judge whether described tree graph also has the training sequence deviation of undefined distribution priority in the anterior layer, if, the level number that then will work as anterior layer is defined as the distribution priority of described training sequence deviation, and described training sequence deviation is labeled as defines distribution priority; When carrying out first, when anterior layer is the top of tree graph;
A2, judge whether when anterior layer be the lowermost layer of tree graph, if, end step A then, otherwise, following one deck of tree graph as working as anterior layer, and is returned steps A 1.
3. method according to claim 1 and 2 is characterized in that, for given training sequence deviation sum, the number of the mapping relations tree graph between described predefined training sequence deviation and the channel code is 1.
4. method according to claim 1 and 2 is characterized in that, for given training sequence deviation sum K, the number of the mapping relations tree graph between described predefined training sequence deviation and the channel code equals the packet count M of training sequence deviation.
5. method according to claim 4 is characterized in that, step C is described to search mapping relations tree graph between predefined training sequence deviation and the channel code according to described spreading factor, determines that the training sequence deviation that this spreading factor can be used is:
Search each tree graph in the described M tree graph according to described spreading factor, determine the training sequence deviation that this spreading factor can be used in each tree graph, the set of the training sequence deviation that this spreading factor can be used in described each tree graph can be with a subclass of training sequence deviation set for this spreading factor.
6. the distributor of a training sequence deviation is characterized in that, comprising:
The tree graph module is used to store the mapping relations tree graph between training sequence deviation and the channel code;
Distribute priority that module is set, the level that is used for the tree graph stored according to described tree graph module, setting is arranged in the distribution priority of described tree graph training sequence deviation at all levels, and the distribution priority that is positioned at the training sequence deviation of higher level will be lower than the distribution priority of the training sequence deviation that is positioned at lower level; If a training sequence deviation occurs repeatedly in tree graph, then the level of this training sequence deviation is the highest level in the level that this training sequence deviation occurred;
The spreading factor module is used for when giving a channel allocation training sequence deviation, determines to distribute to the spreading factor of the channel code of this channel according to the channel resource of this channel occupancy;
Search module, be used for the spreading factor definite according to described spreading factor module, search the tree graph of storing in the described tree graph module, determine the training sequence deviation that this spreading factor can be used, and in described available training sequence deviation, select the training sequence deviation of all current free time; And
Distribution module, be used for the training sequence deviation of searching the selected current free time of module described, according to the distribution priority that the training sequence deviation of module is set from described distribution priority, selection has the training sequence deviation that best result is joined priority, and it is distributed to described channel.
7. device according to claim 6 is characterized in that, described distribution priority is provided with module and further comprises:
First judging unit is used for judging whether described tree graph also has the training sequence deviation of undefined distribution priority when anterior layer, if the training sequence deviation of described undefined distribution priority is sent to the unit is set; When carrying out first, when anterior layer is the top of tree graph;
The unit is set, is used for being defined as the distribution priority of the training sequence deviation of being received when the level number of anterior layer, and described training sequence deviation is labeled as defines distribution priority, index signal is sent to second judging unit in the back that is finished;
Second judging unit is used to judge whether that working as anterior layer is the lowermost layer of tree graph, if send index signal to output unit, otherwise, notify first judging unit with following one deck of tree graph as working as anterior layer;
Output unit is used for after the index signal of receiving from second judging unit, exports the distribution priority that the defined training sequence deviation in unit is set to described distribution module.
8. according to claim 6 or 7 described devices, it is characterized in that for given training sequence deviation sum K, stored the mapping relations tree graph between M training sequence deviation and the channel code in the described tree graph module, M equals the packet count of training sequence deviation.
9. device according to claim 8, it is characterized in that, the described module of searching is used for searching each tree graph in M the tree graph that described tree graph module stores according to described spreading factor, determine the set of the training sequence deviation that this spreading factor can be used in each tree graph, the set of the training sequence deviation that this spreading factor can be used in described each tree graph can be with a subclass of training sequence deviation set for this spreading factor; In can gathering with training sequence deviation, described this spreading factor selects the training sequence deviation of all current free time.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030210754A1 (en) * | 2002-05-09 | 2003-11-13 | Interdigital Technology Corporation | Method and apparatus for parallel midamble cancellation |
| CN101359953A (en) * | 2007-08-01 | 2009-02-04 | 中兴通讯股份有限公司 | Method for applying MIMO technique in TD-SCDMA system outdoor macrocell |
-
2010
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030210754A1 (en) * | 2002-05-09 | 2003-11-13 | Interdigital Technology Corporation | Method and apparatus for parallel midamble cancellation |
| CN101359953A (en) * | 2007-08-01 | 2009-02-04 | 中兴通讯股份有限公司 | Method for applying MIMO technique in TD-SCDMA system outdoor macrocell |
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