CN102215082B - Midamble shift allocation method and device - Google Patents
Midamble shift allocation method and device Download PDFInfo
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- CN102215082B CN102215082B CN201010144368.7A CN201010144368A CN102215082B CN 102215082 B CN102215082 B CN 102215082B CN 201010144368 A CN201010144368 A CN 201010144368A CN 102215082 B CN102215082 B CN 102215082B
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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 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, multiple high speed uplink bag access (HSUPA) subscriber equipmenies (UE) can be shared identical scheduling enhanced dedicated channel physical uplink channel (E-PUCH) resource; At down direction, multiple high-speed downstream bag access (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, to share identical scheduling E-PUCH resource, for descending, to share identical scheduling HS-PDSCH resource) there is different training sequence deviation (Midamble Shift), described training sequence deviation is as the foundation of the wireless channel of these UE of differentiation.
In 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 mapping relations between each training sequence deviation and channel code are defined with the form of tree graph in 3GPP agreement TS25.221.
Fig. 1 has provided an example of the mapping relations tree graph between training sequence deviation and the channel code of prior art.Wherein, the total K=8 of training sequence deviation.In 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 code number in the bracket of the upper right corner.
In tree graph, being positioned at the spreading factor minimum of the top channel code of tree graph as shown in Figure 1, is SF=1; Be positioned at the spread spectrum of channel code of the tree graph second layer 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,, for top (the spreading factor SF=1) of tree graph, only has available training sequence deviation, i.e. a m
(1); The second layer (spreading factor SF=2) of tree graph, 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, first, according to the channel resource of this channel occupancy, determine the spreading factor of the channel code of distributing to this channel; Then, in the channel code that adopts this spreading factor, select an idle channel code to distribute to this channel.
When giving this channel allocation training sequence deviation according to first method of salary distribution, in each training sequence deviation corresponding with this channel code, select an idle training sequence deviation to distribute to this channel.
For example,, by K in community
mindividual training sequence deviation is divided into 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∈ during 4,6,8,10,12,14,16}, 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 M group training sequence deviation, m ∈ { 0,1, ..., mapping relations between each training sequence deviation and Orthogonal Variable Spreading Factor OVSF (OVSF) channel code that M-1} group training sequence deviation comprises are defined with special default training sequence deviation configuration mode in 3GPP agreement.
Work as K
uEwhen≤M UE shares identical scheduling resource, distribute different training sequence deviation need to each UE.For K
uEk UE in individual UE, can organize and in training sequence deviation, select m at M
kgroup training sequence deviation.Then according to shared OVSF channel code and the m of scheduling resource that distributes to this UE
kmapping relations between each training sequence deviation and the OVSF channel code comprising in group training sequence deviation, determine the training sequence deviation of distributing to this UE.K in addition
uE-1 UE can not select m again
kgroup 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 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 yet assigned to other UE or up channel, this training sequence deviation is distributed to this UE; If this training sequence deviation is assigned with, distributes training sequence deviation cannot to this UE, or 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, there will be following unreasonable situation:
High-speed shared information channel (HS-SICH) takies the channel code of 1 SF=16, by time slot 1(TS1) interior channel code number is that the channel code of 1 idle SF=16 is distributed to HS-SICH.Under the default training sequence deviation method of salary distribution, training sequence deviation corresponding to this channel code 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 at TS1 the channel code of other channel configurations SF=1.Because training sequence deviation corresponding to the channel code 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 idle channel code is also unreasonable.To tree graph analysis shown in Fig. 1, can find out, 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)in tree graph, every one deck all occurs, has occurred altogether 6 times (wherein at the 5th layer, occurring twice); The 5th training sequence deviation occurred 5 times, and the 3rd and the 7th training sequence deviation occurred respectively 4 times, and the 2nd, the 4th, the 6th and the 8th training sequence deviation occurs respectively 3 times.Occurrence number is more, shows that the possibility that this training sequence deviation is assigned with is larger, and namely the scarcity of this training sequence deviation is just higher.This tree graph also has following features: the training sequence deviation that higher level occurs is bound to occur at lower level; Level is higher, and the number of optional training sequence deviation is fewer.
If comparatively rare training sequence deviation is distributed to the channel that spreading factor is larger, for the less channel of spreading factor, optional training sequence deviation is just subject to certain limitation, even can cause there is no 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 channel that spreading factor is less more easily be assigned to training sequence deviation.
The embodiment of the present 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 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 training sequence deviation that is positioned at lower level; The level of described tree graph according to spreading factor order from small to large successively from high to low; If a training sequence deviation occurs repeatedly in tree graph, the highest level in the level that level of this training sequence deviation occurs for this training sequence deviation;
B, giving during a channel allocation training sequence deviation, according to the channel resource of this channel occupancy, determine the spreading factor of the channel code of distributing to this channel;
C, according to described spreading factor, search the mapping relations tree graph between predefined training sequence deviation and channel code, 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 there is the training sequence deviation that best result is joined priority, and distributed to described channel.
It is characterized in that, described steps A comprises:
A1, judge the training sequence deviation that whether also has undefined distribution priority in described tree graph current layer, if, the level number of current layer is defined as to the distribution priority of described training sequence deviation, and described training sequence deviation is labeled as to defined distribution priority; While carrying out first, what current layer was tree graph is top;
A2, judge whether that current layer is the lowermost layer of tree graph, if so, end step A, otherwise, using lower one deck of tree graph as current layer, and return to 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 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 channel code equals the packet count M of training sequence deviation.
Preferably, according to described spreading factor, search the mapping relations tree graph between predefined training sequence deviation and channel code described in step C, determine that the training sequence deviation that this spreading factor can be used is:
According to described spreading factor, search each tree graph in a described M tree graph, determine the training sequence deviation that in each tree graph, this spreading factor can be used, the set of the training sequence deviation that in described each tree graph, this spreading factor can be used is that this spreading factor can be by of a training sequence deviation set subset.
The embodiment of the present invention also proposes a kind of distributor of training sequence deviation, comprising:
Tree graph module, for storing the mapping relations tree graph between training sequence deviation and channel code;
Distribute priority that module is set, be used for the level of the tree graph of storing according to described tree graph module, setting is positioned at 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 training sequence deviation that is positioned at lower level; In the level of described tree graph according to spreading factor order from small to large successively from high to low; If a training sequence deviation occurs repeatedly in tree graph, the highest level in the level that level of this training sequence deviation occurs for this training sequence deviation;
Spreading factor module, for when giving a channel allocation training sequence deviation, determines the spreading factor of the channel code of distributing to this channel according to the channel resource of this channel occupancy;
Search module, be used for according to the definite spreading factor of described spreading factor module, search the tree graph of storing in 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 in described training sequence deviation of searching the selected current free time of module, 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 is distributed to described channel.
Preferably, described distribution priority arranges module and further comprises:
The first judging unit, for judging that whether described tree graph current layer also has the training sequence deviation of undefined distribution priority, is if so, sent to setting unit by the training sequence deviation of described undefined distribution priority; While carrying out first, what current layer was tree graph is top;
Setting unit, for the level number of current layer being defined as to the distribution priority of received training sequence deviation, and is labeled as defined distribution priority by described training sequence deviation, and backward the second judging unit that is finished sends index signal;
The second judging unit, for judging whether that current layer is the lowermost layer of tree graph, if send index signal to output unit, otherwise, using lower one deck of tree graph, as current layer, notify the first judging unit;
Output unit, after the index signal receiving from the second judging unit, exports the distribution priority of the defined training sequence deviation of setting unit to described distribution module.
Preferably, for given training sequence deviation sum K, stored the mapping relations tree graph between M training sequence deviation and channel code in described tree graph module, M equals the packet count of training sequence deviation.
Preferably, the described module of searching is for each tree graph in M the tree graph of searching described tree graph module according to described spreading factor and storing, determine the set of the training sequence deviation that in each tree graph, this spreading factor can be used, the set of the training sequence deviation that in described each tree graph, this spreading factor can be used is that this spreading factor can be by of a training sequence deviation set subset; Can be by the training sequence deviation of selecting all current free time in training sequence deviation set at described this spreading factor.
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, and comparatively rare training sequence deviation can be remained as much as possible, supplies with the channel that spreading factor is less and uses.
Accompanying drawing explanation
Fig. 1 is the mapping relations tree graph between training sequence deviation and the channel code stipulating in 3GPP agreement;
Fig. 2 is the flow chart of the distribution method of the training sequence deviation of embodiment of the present invention proposition;
Fig. 3 is the block diagram of the distributor of the training sequence deviation of embodiment of the present invention proposition.
Embodiment
The allocation flow of the training sequence deviation that the embodiment of the present 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: according to tree graph level, the distribution priority that is arranged in tree graph training sequence deviation at all levels is set.That is:
The corresponding training sequence deviation of channel code that is positioned at tree graph top (spreading factor is SF=1) has minimum distribution priority, represents the distribution priority of the training sequence deviation that is positioned at this layer with the level number 1 of this layer.
The corresponding 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 the distribution priority of the training sequence deviation that is positioned at this layer with the level number 2 of this layer.
The corresponding 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 the distribution priority of the training sequence deviation that is positioned at this layer with the level number 3 of this layer.
The corresponding 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 the distribution priority of the training sequence deviation that is positioned at this layer with the level number 4 of this layer.
The corresponding 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 the distribution priority of the training sequence deviation that is positioned at this layer with the level number 5 of this layer.
If a training sequence deviation is positioned at many levels simultaneously, the highest level occurring with this training sequence deviation defines the distribution priority of this training sequence deviation.In other words, when giving according to level order from high to low, be positioned at training sequence deviation definition distribution priority at all levels, after the distribution priority of a training sequence deviation is defined, even if still there is this training sequence deviation in other layers, 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 (channel code of the most rare channel code or granularity maximum) of SF=1 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; Training sequence deviation corresponding to channel code (channel code that more rare channel code or granularity are larger) of SF=2 has time minimum distribution priority in these two kinds of training sequence deviation methods of salary distribution; Training sequence deviation corresponding to the channel code of SF=4 (number moderate and the moderate channel code of granularity) has the 3rd low distribution priority; The training sequence deviation of channel code (channel code of the channel code that number is maximum or the granularity minimum) correspondence of the channel code of SF=8 (number time maximum channel code 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 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, under each K value, only has a unique tree graph.
When adopting the special default training sequence deviation method of salary distribution, K training sequence deviation is divided into M group, 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.For the value combination of every a pair of K and M, every group of training sequence deviation comprising is different.Therefore,, for the value combination of a pair of given K value and M value, there is M tree graph.The m(1≤m≤M) individual tree graph defines the mapping relations between each training sequence deviation and Orthogonal Variable Spreading Factor OVSF (OVSF) channel code that m group comprises.In each tree graph in this M tree graph, the definition mode of the distribution priority of training sequence deviation is identical.
Step 202: when giving a channel allocation training sequence deviation, determine the spreading factor of the channel code of distributing to this channel according to the channel resource of this channel occupancy.Described channel includes but not limited to the channels such as HS-SICH, Physical Random Access Channel (PRACH), uplink special physical channel (UL DPCH).
Step 203: search the mapping relations tree graph between predefined training sequence deviation and 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, under each K value, only has a unique tree graph.Describedly according to spreading factor, search the mapping relations tree graph between predefined training sequence deviation and channel code, determine that the training sequence deviation that this spreading factor can be used is: search the unique tree graph under 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, the lower corresponding M tree graph of each K value.Describedly according to spreading factor, search the mapping relations tree graph between predefined training sequence deviation and channel code, determine that the training sequence deviation that this spreading factor can be used is: according to described spreading factor, search each tree graph in a described M tree graph, determine the training sequence deviation that in each tree graph, this spreading factor can be used, the set of the training sequence deviation that in described each tree graph, this spreading factor can be used is that this spreading factor can be by of a training sequence deviation set subset.
Step 204: the training sequence deviation of selecting all current free time in described available training sequence deviation.
Step 205: in the training sequence deviation of described current free time, select to there is the training sequence deviation that best result is joined priority, and distributed to described channel.
When thering is best result and join more than one of the training sequence deviation of priority, select at random a training sequence deviation, this training sequence deviation and the corresponding channel code of this training sequence deviation are distributed to this channel.
Defining according to the method described above the distribution priority of each training sequence deviation, and the distribution priority based on each training sequence deviation is during to channel allocation channel code and training sequence deviation, the training sequence deviation that just can avoid distributing to a channel code by the training sequence deviation of more rare channel code to the problem taking.In other words, the problem of having avoided training sequence deviation corresponding to rare channel code to be taken by not rare channel code.
The embodiment of the present invention also proposes a kind of distributor of training sequence deviation, and as shown in Figure 3, device 300 comprises its block diagram:
When adopting the default training sequence deviation method of salary distribution, under each K value, only has a unique tree graph.301 of described tree graph modules need to be stored the tree graph under described K value.Or each tree graph under each probable value of storage K.When concrete application, according to K value, from the tree graph of storage, extract the tree graph of described K value.
When adopting the special default training sequence deviation method of salary distribution, the lower corresponding M tree graph of each K value.Described tree graph module 301, for storing to M tree graph under defining K value and given M value.Or, determine all possible value combination of K and M, store M tree graph under the value combination of every kind of K and M.When concrete application, according to K value and M value, from the tree graph of storage, extract M tree graph under described K value and M value.
Distribute priority that module 302 is set, be used for according to the level of 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 training sequence deviation that is positioned at lower level; If a training sequence deviation occurs repeatedly in tree graph, the highest level in the level that level of this training sequence deviation occurs for this training sequence deviation;
Spreading factor module 303, for when giving a channel allocation training sequence deviation, determines the spreading factor of the channel code of distributing to this channel according to the channel resource information of this channel occupancy;
Preferably, described distribution priority arranges module 302 and can further include:
The first judging unit, for judging that whether described tree graph current layer also has the training sequence deviation of undefined distribution priority, is if so, sent to setting unit by the training sequence deviation of described undefined distribution priority; While carrying out first, what current layer was tree graph is top;
Setting unit, for the level number of current layer being defined as to the distribution priority of received training sequence deviation, and is labeled as defined distribution priority by described training sequence deviation, and backward the second judging unit that is finished sends index signal;
The second judging unit, for judging whether that current layer is the lowermost layer of tree graph, if send index signal to output unit, otherwise, using lower one deck of tree graph, as current layer, notify the first judging unit;
Output unit, after the index signal receiving from the second judging unit, exports the distribution priority of the defined training sequence deviation of setting unit to described distribution module.
When adopting the special default training sequence deviation method of salary distribution, the described module 304 of searching is for searching each tree graph in M tree graph of described tree graph module 301 storages according to described spreading factor, determine the set of the training sequence deviation that in each tree graph, this spreading factor can be used, the set of the training sequence deviation that in described each tree graph, this spreading factor can be used is that this spreading factor can be by of a training sequence deviation set subset; Can be by the training sequence deviation of selecting all current free time in training sequence deviation set at described this spreading factor.
The distribution method of the training sequence deviation proposing according to the present invention, in Fig. 1, m
(2), m
(4), m
(6), m
(8)there is the highest distribution priority 4, m
(3)and m
(7)there is distribution priority 3, m
(5)there is distribution priority 2; m
(1)there is minimum distribution priority 1.When giving during 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.The channel code of distributing to HS-SICH is the channel code of training sequence deviation correspondence in as Fig. 1 of selection.Such as, select m
(2)give HS-SICH, the channel code of distributing to HS-SICH is that channel code number is the channel code of 3 or 4 SF=16.Under which, m
(1), m
(5), m
(3), m
(7)can be for distributing more rare channel code.
The foregoing is only preferred embodiment of the present invention, in order to limit the present invention, within the spirit and principles in the present invention not all, any modification of making, be equal to replacement, improvement etc., within all should being included in the scope of protection of the invention.
Claims (9)
1. a distribution method for 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 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 training sequence deviation that is positioned at lower level; The level of described tree graph according to spreading factor order from small to large successively from high to low; If a training sequence deviation occurs repeatedly in tree graph, the highest level in the level that level of this training sequence deviation occurs for this training sequence deviation;
B, giving during a channel allocation training sequence deviation, according to the channel resource of this channel occupancy, determine the spreading factor of the channel code of distributing to this channel;
C, according to described spreading factor, search the mapping relations tree graph between predefined training sequence deviation and channel code, 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 there is the training sequence deviation that best result is joined priority, and distributed to described channel.
2. method according to claim 1, is characterized in that, steps A comprises:
A1, judge the training sequence deviation that whether also has undefined distribution priority in described tree graph current layer, if, the level number of current layer is defined as to the distribution priority of described training sequence deviation, and described training sequence deviation is labeled as to defined distribution priority; While carrying out first, what current layer was tree graph is top;
A2, judge whether that current layer is the lowermost layer of tree graph, if so, end step A, otherwise, using lower one deck of tree graph as current layer, and return to 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 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 channel code equals the packet count M of training sequence deviation.
5. method according to claim 4, is characterized in that, searches the mapping relations tree graph between predefined training sequence deviation and channel code described in step C according to described spreading factor, determines that the training sequence deviation that this spreading factor can be used is:
According to described spreading factor, search each tree graph in a described M tree graph, determine the training sequence deviation that in each tree graph, this spreading factor can be used, the set of the training sequence deviation that in described each tree graph, this spreading factor can be used is that this spreading factor can be by of a training sequence deviation set subset.
6. a distributor for training sequence deviation, is characterized in that, comprising:
Tree graph module, for storing the mapping relations tree graph between training sequence deviation and channel code;
Distribute priority that module is set, be used for the level of the tree graph of storing 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 training sequence deviation that is positioned at lower level; The level of described tree graph according to spreading factor order from small to large successively from high to low; If a training sequence deviation occurs repeatedly in tree graph, the highest level in the level that level of this training sequence deviation occurs for this training sequence deviation;
Spreading factor module, for when giving a channel allocation training sequence deviation, determines the spreading factor of the channel code of distributing to this channel according to the channel resource of this channel occupancy;
Search module, be used for according to the definite spreading factor of described spreading factor module, search the tree graph of storing in 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 in described training sequence deviation of searching the selected current free time of module, 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 is distributed to described channel.
7. device according to claim 6, is characterized in that, described distribution priority arranges module and further comprises:
The first judging unit, for judging that whether described tree graph current layer also has the training sequence deviation of undefined distribution priority, is if so, sent to setting unit by the training sequence deviation of described undefined distribution priority; While carrying out first, what current layer was tree graph is top;
Setting unit, for the level number of current layer being defined as to the distribution priority of received training sequence deviation, and is labeled as defined distribution priority by described training sequence deviation, and backward the second judging unit that is finished sends index signal;
The second judging unit, for judging whether that current layer is the lowermost layer of tree graph, if send index signal to output unit, otherwise, using lower one deck of tree graph, as current layer, notify the first judging unit;
Output unit, after the index signal receiving from the second judging unit, exports the distribution priority of the defined training sequence deviation of setting unit to described distribution module.
8. according to the device described in claim 6 or 7, it is characterized in that, for given training sequence deviation sum K, stored the mapping relations tree graph between M training sequence deviation and channel code in 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 for each tree graph in M the tree graph of searching described tree graph module according to described spreading factor and storing, determine the set of the training sequence deviation that in each tree graph, this spreading factor can be used, the set of the training sequence deviation that in described each tree graph, this spreading factor can be used is that this spreading factor can be by of a training sequence deviation set subset; Can be by the training sequence deviation of selecting all current free time in training sequence deviation set at described this spreading factor.
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|---|---|---|---|---|
| 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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| CN102215082A (en) | 2011-10-12 |
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