CN112838905B - Interference suppression method, device and equipment - Google Patents
Interference suppression method, device and equipment Download PDFInfo
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- CN112838905B CN112838905B CN202110432498.9A CN202110432498A CN112838905B CN 112838905 B CN112838905 B CN 112838905B CN 202110432498 A CN202110432498 A CN 202110432498A CN 112838905 B CN112838905 B CN 112838905B
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- H04J11/0023—Interference mitigation or co-ordination
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Abstract
The application provides an interference suppression method, device and equipment,the method obtains the interference and noise value N on the first slot in the current interference detection period1(ii) a According to the interference and noise value N1Determining an interference scene reference parameter corresponding to each RB on a first slot; determining the current target scene type of each RB according to the interference scene reference parameter corresponding to each RB; and when the determined target scene type is an interference-free scene, the adopted load balancing mode is an MRC mode, and when the determined target scene type is a strong interference scene or a weak interference scene, the adopted load balancing mode is an IRC mode. Therefore, by applying the technical scheme provided by the embodiment of the application, the calculation process for determining the interference scene reference parameter of the current scene type is simplified, the consumption of hardware DSP resources can be reduced, the time delay is small, and the demodulation performance is improved.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a method, an apparatus, and a device for interference suppression.
Background
Currently, the 5G technology is increasingly applied to different technical fields due to the low delay characteristic, and during the application process, the inter-cell co-channel interference problem is a long-standing technical problem in the application of the 5G technology.
To solve this technical problem, a cell interference suppression technique is developed. The currently used cell interference suppression technology is to select an interference suppression mode corresponding to each scene according to different scenes where a frequency band of a received signal is located, for example, when the frequency band of the signal is located in an interference-free scene, the adopted load balancing mode is an MRC (Maximum Ratio Combining) mode, and when the frequency band of the signal is located in an interference scene, the adopted load balancing mode is an IRC (Maximum Ratio Combining) mode.
However, in practical application, when determining a scene where a frequency band where a received Signal is located, the existing interference suppression technology performs adaptive judgment calculation once on each Resource Block (RB) on each slot (referred to as slot) in a Signal time domain to determine the scene where the RB is located, so as to determine which interference suppression mode to select according to an adaptive judgment calculation result, and this adaptive judgment calculation Processing is performed on each RB corresponding to each slot, which obviously consumes a large amount of hardware DSP (Digital Signal Processing) resources.
Disclosure of Invention
The application provides an interference suppression method, device and equipment, which are used for reducing consumption of hardware DSP resources.
Specifically, the method is realized through the following technical scheme:
in one aspect, an embodiment of the present application provides an interference suppression method, where the method includes:
obtaining the interference and noise value N on the first slot in the current interference detection period1；
According to the interference and noise value N1Determining an interference scene reference parameter corresponding to each RB on the first slot; the interference scene reference parameter is used for determining the current scene type;
determining the current target scene type of each RB according to the interference scene reference parameter corresponding to each RB; and when the determined target scene type is an interference-free scene, the adopted load balancing mode is an MRC mode, and when the determined target scene type is a strong interference scene or a weak interference scene, the adopted load balancing mode is an IRC mode.
In another aspect, an embodiment of the present application provides an interference suppression apparatus, including:
an interference and noise value determining unit for obtaining an interference and noise value N on a first slot in a current interference detection period1；
An interference scene reference parameter determining unit for determining an interference scene reference parameter according to the interference and noise value N1Determining an interference scene reference parameter corresponding to each RB on the first slot; the interference scene reference parameter is used for determining the current scene type;
the mode determining unit is used for determining the current target scene type of each RB according to the interference scene reference parameter corresponding to each RB; and when the determined target scene type is an interference-free scene, the adopted load balancing mode is an MRC mode, and when the determined target scene type is a strong interference scene or a weak interference scene, the adopted load balancing mode is an IRC mode.
Through the technical scheme of the application, in the application, the adaptive judgment calculation is not performed on each RB in each slot in the interference detection period once, the interference scene reference parameter corresponding to each RB in the first slot is determined only according to the interference and noise value in the first slot in the current interference detection period, the target scene type where each RB is located currently is determined according to the interference scene reference parameter corresponding to each RB, and then the load balancing mode corresponding to the target scene type is adopted. Therefore, the technical scheme provided by the embodiment of the application introduces the interference detection period, and only each RB on the first slot in the interference detection period is calculated, so that the calculation process of the interference scene reference parameter for determining the current scene type is simplified, and the consumption of hardware DSP resources can be reduced.
Drawings
Fig. 1 is a schematic flow chart of interference suppression according to an embodiment of the present application;
fig. 2 is a schematic flow chart of another interference suppression provided in the embodiment of the present application;
fig. 3 is a schematic structural diagram of an interference suppression apparatus according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
Currently, inter-cell interference suppression techniques have received sufficient attention. Cell interference suppression techniques such as interference randomization, interference coordination, interference cancellation, and inter-cell power control to improve the peak rate and throughput of cell-edge users, thereby improving the throughput, spectrum utilization, and cell coverage of the cell as a whole. However, from the system evaluation results, the above techniques still cannot sufficiently satisfy the requirements of the system for edge spectrum efficiency and cell average spectrum efficiency, and the inter-cell interference control technique needs to be developed more greatly. Based on this, some cell interference suppression technologies are proposed, and the currently commonly used cell interference suppression technologies select an interference suppression mode corresponding to each scene according to different scenes where a frequency band where a received signal is located, for example, when the frequency band where the signal is located is in an interference-free scene, the adopted load balancing mode is an MRC mode, and when the frequency band where the signal is located is in an interference scene, the adopted load balancing mode is an IRC mode.
However, in practical application, when determining a scene where a frequency band where a received signal is located, the existing interference suppression technology performs adaptive judgment calculation once for each RB on each slot in a signal time domain to determine the scene where the RB is located, so as to determine which interference suppression mode to select according to the result of the adaptive judgment calculation, and this adaptive judgment calculation processing is performed for each RB corresponding to each slot, which obviously consumes a large amount of hardware DSP resources.
In order to solve the above technical problem, an embodiment of the present application provides an interference suppression method, including: obtaining the interference and noise value N on the first slot in the current interference detection period1(ii) a According to the interference and noise value N1Determining an interference scene reference parameter corresponding to each RB on the first slot; the interference scene reference parameter is used for determining the current scene type; determining the current target scene type of each RB according to the interference scene reference parameter corresponding to each RB; and when the determined target scene type is an interference-free scene, the adopted load balancing mode is an MRC mode, and when the determined target scene type is a strong interference scene or a weak interference scene, the adopted load balancing mode is an IRC mode. The technical scheme provided by this embodiment does not perform adaptive judgment calculation on each RB in each slot in the interference detection period any more, but determines an interference scene reference parameter corresponding to each RB in a first slot in the current interference detection period only according to the interference and noise values in the first slot, determines a current target scene type of each RB according to the interference scene reference parameter corresponding to each RB, and further adopts a load balancing mode corresponding to the target scene type. Therefore, the technical scheme provided by the embodiment of the application introduces the interference detection period, and only each RB on the first slot in the interference detection period is calculated, so that the method for determining the current scene is simplifiedThe calculation process of the type interference scene reference parameter can further reduce the consumption of hardware DSP resources.
Referring to fig. 1, fig. 1 is a schematic flow chart of interference suppression provided in the embodiment of the present application, and the method is applied to a DSP in a base station, and may also be applied to a CPU in the base station.
As shown in fig. 1, the process may include the following steps:
In this embodiment, the slot number N included in each interference detection periodslotIs pre-configured, wherein NslotThe method is based on the angle setting that the IRC mode is more excellent in stability and resource utilization rate and the load balancing mode is prevented from being frequently switched.
Interference and noise figure N1The determined implementation manners are many, and are not described herein one by one, and as an embodiment, the implementation manner of step 101 may include:
according to the set transmission signal
Interference signal XiChannel parameter HsWhite noise signal
Channel HiAnd the pilot signal sent by the currently received terminal
Determining the interference and noise value N on the first slot in the current interference detection period according to the following expression1。
The expression is
，
。
In the present embodiment, the transmission signal is set as described above
Including at least signals that may be data signals, noise signals, and pilot signals.
102, according to the interference and noise value N1And determining an interference scene reference parameter corresponding to each RB on the first slot.
In this step, the interference scene reference parameter is used to determine the current scene type.
As an embodiment, the implementation manner of the step 102 may include the following steps A-C:
and step A, aiming at each RB in the first slot, determining an RB covariance proportion average value of the RB in the first slot according to the interference and noise value N1.
The Slot is divided into a plurality of symbols, each symbol corresponds to an RB, and the RB includes a plurality of resource elements REs.
As an embodiment, the implementation manner of the step A can comprise the following steps A1-A2:
step A1, calculating the interference degree parameter between noise parameters corresponding to RB according to the interference and noise value N1
。
As an embodiment, for each RE (Resource Element) of each RB, a covariance value corresponding to the RE may be calculated according to the following expression
The expression is:
。
for each RB, covariance value for that RB
Carrying out mean value processing according to the following expression to obtain an interference degree parameter
The expression is:
。
is an empirical value obtained from experience and simulation.
Step A2, interference degree parameter is determined
Substituting the obtained value into an RB covariance ratio average value formula to obtain an RB covariance ratio average value
。
As an example, the RB covariance ratio average formula may be:
In the present embodiment, it is preferred that,
the number of REs included for one RB is preset, and is also referred to as an average grain size number. The selection of the number of the REs is related to the strength of interference and the interference bandwidth, and the conventional interference judgment is that the number of the average granularity of the REs of each RB is the same when the noise covariance of the REs is calculated, so that the RE adaptive method cannot be adapted more optimally under various different scenes such as the strength of interference, the coverage bandwidth and the like. In the present step, the first step is carried out,
and adapting scenes of different frequency bands.
Step B, the RB covariance proportion average value of each RB on the first slot
And determining the interference scene reference parameter corresponding to the RB.
103, determining a current target scene type of each RB according to the interference scene reference parameter corresponding to each RB; and when the determined target scene type is an interference-free scene, the adopted load balancing mode is an MRC mode, and when the determined target scene type is a strong interference scene or a weak interference scene, the adopted load balancing mode is an IRC mode.
In the embodiment, the IRC mode suppresses co-channel interference, and based on this, the IRC mode has a negative gain in an interference-free scene, so that the MRC mode is selected in the interference-free scene.
As an embodiment, the implementation manner of determining the current target scene type of each RB according to the interference scene reference parameter corresponding to each RB in step 103 may include the following steps C to D:
step C, aiming at each RB on the first slot, determining a target RB covariance ratio average value range matched with the RB covariance ratio average value of the RB from the set RB covariance ratio average value range; when the target RB covariance ratio average range is the RB covariance ratio average range corresponding to the non-interference scene, determining that the candidate scene type corresponding to the RB is the non-interference scene; when the target RB covariance ratio average range is the RB covariance ratio average range corresponding to the strong interference scene, determining that the candidate scene type corresponding to the RB is the strong interference scene; and when the target RB covariance ratio average range is the RB covariance ratio average range corresponding to the weak interference scene, determining that the candidate scene type corresponding to the RB is the weak interference scene.
In this embodiment, the set range of the proportional mean of covariance of each RB may be greater than or equal to 0 and less than or equal to a first threshold, greater than the first threshold and less than or equal to a second threshold, and greater than the second threshold, where the second threshold is greater than the first threshold.
The determination of the target RB covariance ratio average range matching the RB covariance ratio average of the RB from the set RB covariance ratio average ranges may be:
determining the RB covariance ratio mean greater than or equal to 0 and less than or equal to a first threshold as the target RB covariance ratio mean range if the RB covariance ratio mean belongs to the first threshold greater than or equal to 0 and less than or equal to the first threshold.
And if the RB covariance ratio mean belongs to a range which is larger than the first threshold and smaller than or equal to the second threshold, determining the RB covariance ratio mean larger than the first threshold and smaller than or equal to the second threshold as a target RB covariance ratio mean range.
And if the RB covariance ratio mean value belongs to a range greater than a second threshold value, determining the range greater than the second threshold value as a target RB covariance ratio mean value range.
And D, determining the current target scene type of each RB according to the determined candidate scene type corresponding to each RB.
As an embodiment, the implementation manner of the implementation step D can include the following steps D1-D4:
step D1, determining a first RB coverage range when the candidate scene type is an interference-free scene, and determining the intersection P of the first RB coverage range and the RB coverage range occupied by the interference-free scene in the last interference detection period1。
In this step, the first RB coverage is only named for convenience of distinguishing from the following RB coverage, and is not intended to limit a certain RB coverage.
Here, the second RB coverage is named only for convenience of description and is not intended to limit a certain RB coverage.
The third RB coverage is named for convenience of description only and is not intended to limit a certain RB coverage.
The first RB coverage may be understood as an RB occupied by a non-interference scene in the current interference detection period. The RB coverage area occupied by the non-interference scene in the last interference detection period is the RB occupied by the non-interference scene in the last interference detection period.
The second RB coverage may be understood as an RB occupied by a weak interference scenario in the current interference detection period. The coverage area of the RB occupied by the weak interference scenario in the previous interference detection period is the RB occupied by the strong interference scenario in the previous interference detection period.
The third RB coverage may be understood as an RB occupied by a strong interference scenario in the current interference detection period. The coverage area of the RB occupied by the strong interference scenario in the previous interference detection period is the RB occupied by the strong interference scenario in the previous interference detection period.
As an example, the intersection P of RB coverage1Difference value of RB coverage range occupied by non-interference scene in the first RB coverage range and the last interference detection period
。
Step D2, determining a second RB coverage range when the candidate scene type is a strong interference scene, and determining an intersection P of the second RB coverage range and the RB coverage range occupied by the strong interference scene in the last interference detection period2。
As an example, the intersection P of RB coverage2Difference value of RB coverage range occupied by strong interference scene in the last interference detection period and second RB coverage range
。
Step D3, determining a third RB coverage range when the candidate scene type is a weak interference scene, and determining an intersection P of the third RB coverage range and the RB coverage range occupied by the weak interference scene in the last interference detection period3。
As an example, the intersection P of RB coverage3Difference value of RB coverage range occupied by weak interference scene in the last interference detection period and third RB coverage range
。
Step D4, when the intersection P is defined1Intersect P2Intersect P3When the interference state in the last interference detection period is determined to be updated, determining the candidate scene type corresponding to each RB on the first slot in the current interference detection period as the target scene type, and determining the candidate scene type according to the intersection P1Intersect P2Intersect P3When the interference state in the last interference detection period is determined to be kept, determining the target scene type corresponding to each RB on the first slot in the current interference detection period according to the interference state in the last interference detection period; and the interference state in the last interference detection period at least comprises the scene type corresponding to each RB in the first slot in the last interference detection period.
In this step, the interference state may include at least an RB coverage in a non-interference scene, an RB coverage in a weak interference scene, and an RB coverage in a strong interference scene. As an example, according to the intersection P1Intersect P2Intersect P3The implementation manner for determining and updating the interference state in the last interference detection period is as follows: when in use
Less than or equal to the threshold value
Then the last trunk is updatedInterference states within the interference detection period.
According to the intersection P1Intersect P2Intersect P3The implementation manner for determining to maintain the interference state in the last interference detection period is as follows: when in use
Greater than a threshold value
And keeping the interference state in the last interference detection period.
Determining a first RB coverage range when the candidate scene type is an interference-free scene, and determining an intersection S of the first RB coverage range and an RB coverage range occupied by the interference-free scene on the 2 nd slot in the current interference detection period1；
As another embodiment, the type of the target interference scene in the second slot is determined according to the method described in the step 101 to the step 103. The implementation mode for implementing the step D can comprise the following steps D5-D8:
step D5, determining a first RB coverage range when the candidate scene type is an interference-free scene, and determining an intersection S of the first RB coverage range and an RB coverage range occupied by the interference-free scene in a second slot in the current interference detection period1。
Step D6, determining a second RB coverage range when the candidate scene type is a strong interference scene, and determining an intersection S of the second RB coverage range and the RB coverage range occupied by the strong interference scene on a second slot in the current interference detection period2。
Step D7, determining a third RB coverage range when the candidate scene type is a weak interference scene, and determining an intersection S of the third RB coverage range and the RB coverage range occupied by the weak interference scene on a second slot in the current interference detection period3；
Step D8, when the intersection S is relied on1The intersection S2The intersection S3When the interference state in the current interference detection period is determined to be updated, the candidate scenes corresponding to all RBs on the second slot in the current interference detection period are determinedThe type is determined as the type of the target scene according to the intersection S1The intersection S2The intersection S3And when the interference state in the current interference detection period is determined to be kept, determining the target scene type corresponding to each RB on the first slot in the current interference detection period according to the interference state in the current interference detection period.
As an embodiment, for IRC mode division, the present embodiment divides a scene into strong, weak, and none dimensions, and according to the complexity of the scene, the method described in the above embodiment may be further divided into strong, sub-strong, medium, sub-weak, and none dimensions to realize more detailed scenes, and different covariance distribution granularities are assigned to each scene.
Thus, the flow shown in fig. 1 is completed.
Therefore, through the flow shown in fig. 1, instead of performing adaptive judgment calculation once for each RB on each slot in the interference detection period, the interference scene reference parameter corresponding to each RB on the first slot is determined only according to the interference and noise value on the first slot in the current interference detection period, so as to determine the current target scene type of each RB according to the interference scene reference parameter corresponding to each RB, and then a load balancing mode corresponding to the target scene type is adopted. Therefore, the technical scheme provided by the embodiment of the application introduces the interference detection period, and only each RB on the first slot in the interference detection period is calculated, so that the calculation process for determining the interference scene reference parameter of the current scene type is simplified, the consumption of hardware DSP resources can be reduced, the delay is reduced, and the demodulation performance is improved.
After the flow shown in fig. 1 is completed, as shown in fig. 2, the method may further include the following steps 104 to 108:
And 105, determining a scene interference degree parameter corresponding to the average particle value matched with the target scene type according to the interference and noise value N1 on the slot and the average particle value matched with the target scene type for each RB on each slot in the current interference detection period.
As an example, each target scene type has a matching average particle size value, which may be obtained from empirical values and simulations.
Average particle size value corresponding to each target scene type
All are different, and the average particle size value corresponding to the non-interference scene is set as
(ii) a The average particle size corresponding to the weak interference scene is
The average particle size corresponding to a scene with strong interference is
The three satisfy the following relationship:
。
as an example, the average granularity is divided when
Greater than the number of RBs of the currently demodulated UE,
equal to the number of UE RBs; when in use
When the particles cannot be averaged within the RB of the current mode of the UE, the last particle size is also used as the minimum particle size.
As an embodiment, for each RB in each slot in the current interference detection period, determining a scene interference degree parameter corresponding to an average particle value matched with a target scene type according to the interference and noise value N1 in the slot and the average particle value matched with the target scene type is implemented as steps E to G:
step E, determining a scene interference degree parameter corresponding to the RB in the non-interference scene according to the interference and noise value N1 on the slot and the average particle size value matched with the non-interference scene according to the following expression aiming at the non-interference scene of the target scene type
。
The expression is:
。
step F, determining a scene interference degree parameter corresponding to the RB in the weak interference scene according to the interference and noise value N1 on the slot and the average particle size value matched with the weak interference scene according to the following expression aiming at the weak interference scene in the target scene type
。
The expression is:
。
step G, aiming at the situation that the type of the target scene is a strong interference scene, determining a scene interference degree parameter corresponding to the RB in the strong interference scene according to the interference and noise value N1 on the slot and the average particle size value matched with the strong interference scene according to the following expression
。
The expression is:
。
and step 106, determining an equalization parameter for equalizing the signal to be demodulated according to the scene interference degree parameter of each RB in the current interference detection period.
The implementation manner of the step 106 is many, and one implementation manner is given here, specifically: the equalization parameters for equalizing the signal to be demodulated are calculated according to the following expression.
The expression is:
，
。
in the expression, the expression is given,
in order to equalize the matrix, the matrix is,
setting a scene interference degree parameter of each RB in the current interference detection period, wherein the scene interference degree parameter of each RB in the current interference detection period is the scene interference degree parameter of each RB in the current interference detection period, and if the RB corresponds to an interference-free scene
Is composed of
. If the RB corresponds to a weak interference scene, the scene interference degree parameter of the RB
Is composed of
. If the RB corresponds to a strong interference scene, the scene interference degree parameter of the RB
Is composed of
，
In order to balance the factors, the method comprises the following steps of,
and taking the real part function.
And 108, calculating an equalization parameter for equalizing the signal to be demodulated according to the scene interference degree parameter of each RB in the last interference detection period.
Therefore, the technical scheme provided by the embodiment can improve the IRC mode stability and time-varying property. The switching of IRC and MRC depends on the current slot, and the last interference detection period, namely N is also referredslotThe judgment result of each slot not only considers different interference scenes of the current channel, but also avoids frequent switching of mode micro-disturbance.
Thus, the description of the method provided in the present application is completed.
The following describes the apparatus provided in the present application:
referring to fig. 3, fig. 3 is a schematic structural diagram of an interference suppression apparatus 300 according to the present application. The device is applied to an interference suppression device, and comprises:
an interference and noise value determining unit 301, configured to obtain an interference and noise value N on a first slot in a current interference detection period1；
An interference scenario reference parameter determining unit 302, configured to determine the interference and noise value N according to the interference and noise value N1Determining an interference scene reference parameter corresponding to each RB on the first slot; what is needed isThe interference scene reference parameter is used for determining the current scene type;
a scene type determining unit 303, configured to determine a current target scene type of each RB according to the interference scene reference parameter corresponding to each RB; and when the determined target scene type is an interference-free scene, the adopted load balancing mode is an MRC mode, and when the determined target scene type is a strong interference scene or a weak interference scene, the adopted load balancing mode is an IRC mode.
In an embodiment of the present application, the interference scenario reference parameter determining unit 302 includes:
an RB covariance ratio average determining subunit, configured to determine, for each RB in the first slot, an RB covariance ratio average of the RB in the first slot according to the interference and noise value N1;
and the interference scene reference parameter determining subunit is configured to determine the RB covariance ratio average of each RB in the first slot as the interference scene reference parameter corresponding to the RB.
In an embodiment of the present application, the RB covariance ratio average determination subunit is specifically configured to:
calculating an interference degree parameter between noise parameters corresponding to RB according to the interference and noise value N1
；
Interference degree parameter
And substituting the RB covariance ratio average value into an RB covariance ratio average value formula to obtain the RB covariance ratio average value.
In an embodiment of the application, the mode determining unit includes:
a scene type determining subunit, configured to determine, for each RB in the first slot, a target RB covariance ratio average range that matches the RB covariance ratio average of the RB from the set RB covariance ratio average ranges; when the target RB covariance ratio average range is the RB covariance ratio average range corresponding to the non-interference scene, determining that the candidate scene type corresponding to the RB is the non-interference scene; when the target RB covariance ratio average range is the RB covariance ratio average range corresponding to the strong interference scene, determining that the candidate scene type corresponding to the RB is the strong interference scene; when the target RB covariance ratio average range is the RB covariance ratio average range corresponding to the weak interference scene, determining that the candidate scene type corresponding to the RB is the weak interference scene;
and the target scene type determining subunit is used for determining the current target scene type of each RB according to the determined candidate scene type corresponding to each RB.
In an embodiment of the application, the target scene type determining subunit is specifically configured to:
determining a first RB coverage range when the candidate scene type is an interference-free scene, and determining an intersection P1 of the first RB coverage range and an RB coverage range occupied by the interference-free scene in the last interference detection period;
determining a second RB coverage range when the candidate scene type is a strong interference scene, and determining an intersection P2 of the second RB coverage range and the RB coverage range occupied by the strong interference scene in the last interference detection period;
determining a third RB coverage range when the candidate scene type is a weak interference scene, and determining an intersection P3 of the third RB coverage range and the RB coverage range occupied by the weak interference scene in the last interference detection period;
when the interference state in the last interference detection period is determined to be updated according to the intersection P1, the intersection P2 and the intersection P3, determining candidate scene types corresponding to RBs on the first slot in the current interference detection period as target scene types, and when the interference state in the last interference detection period is determined to be maintained according to the intersection P1, the intersection P2 and the intersection P3, determining the target scene types corresponding to the RBs on the first slot in the current interference detection period according to the interference state in the last interference detection period; and the interference state in the last interference detection period at least comprises the scene type corresponding to each RB in the first slot in the last interference detection period.
In an embodiment of the present application, when it is determined to update the interference status in the last interference detection period according to the intersection P1, the intersection P2, and the intersection P3, the apparatus further includes:
a first scene interference degree parameter determining unit, configured to determine, for each RB in each slot in a current interference detection period, a scene interference degree parameter corresponding to an average particle value matched with a target scene type according to the interference and noise value N1 in the slot and the average particle value matched with the target scene type;
and the first equalization parameter determination unit is used for calculating the equalization parameters for equalizing the signal to be demodulated according to the scene interference degree parameters of each RB in the current interference detection period.
When it is determined from the intersection P1, the intersection P2, and the intersection P3 that the interference state in the last interference detection period is maintained, the apparatus further includes:
a second scene interference degree parameter determining unit, configured to determine, for each RB in each slot in a previous interference detection period, a scene interference degree parameter corresponding to an average particle value matched with a target scene type according to the interference and noise value N1 in the slot and the average particle value matched with the target scene type;
and the second equalization parameter determination unit is used for calculating the equalization parameters for equalizing the signal to be demodulated according to the scene interference degree parameters of each RB in the last interference detection period.
Therefore, with the structure shown in fig. 3, instead of performing a self-adaptive judgment calculation on each RB in each slot in the interference detection period, the interference scene reference parameter corresponding to each RB in the first slot is determined only according to the interference and noise values in the first slot in the current interference detection period, so as to determine the current target scene type of each RB according to the interference scene reference parameter corresponding to each RB, and then the load balancing mode corresponding to the target scene type is adopted. Therefore, the technical scheme provided by the embodiment of the application introduces the interference detection period, and only each RB on the first slot in the interference detection period is calculated, so that the calculation process of the interference scene reference parameter for determining the current scene type is simplified, and the consumption of hardware DSP resources can be reduced.
Thus, the description of the structure of the device shown in fig. 3 is completed.
The implementation process of the functions and actions of each unit in the above device is specifically described in the implementation process of the corresponding step in the above method, and is not described herein again.
In the electronic device provided in the embodiment of the present application, from a hardware level, a schematic diagram of a hardware architecture can be seen as shown in fig. 4. The method comprises the following steps: a machine-readable storage medium and a processor, wherein: the machine-readable storage medium stores machine-executable instructions executable by the processor; the processor is configured to execute machine-executable instructions to implement the interference mitigation operations disclosed in the above examples.
Machine-readable storage media are provided by embodiments of the present application that store machine-executable instructions that, when invoked and executed by a processor, cause the processor to implement the interference mitigation operations disclosed by the above examples.
Here, a machine-readable storage medium may be any electronic, magnetic, optical, or other physical storage device that can contain or store information such as executable instructions, data, and so forth. For example, the machine-readable storage medium may be: a RAM (random Access Memory), a volatile Memory, a non-volatile Memory, a flash Memory, a storage drive (e.g., a hard drive), a solid state drive, any type of storage disk (e.g., an optical disk, a dvd, etc.), or similar storage medium, or a combination thereof.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. A typical implementation device is a computer, which may take the form of a personal computer, laptop computer, cellular telephone, camera phone, smart phone, personal digital assistant, media player, navigation device, email messaging device, game console, tablet computer, wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Furthermore, these computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the application. One of ordinary skill in the art can understand and implement it without inventive effort.
So far, the description of the apparatus shown in fig. 4 is completed.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the scope of protection of the present application.
Claims (10)
1. An interference suppression method, comprising:
obtaining the interference and noise value N on the first time slot in the current interference detection period1；
According to the interference and noise value N1Determining an interference scene reference parameter corresponding to each resource block on the first time slot; the interference scene reference parameter is used for determining the current scene type;
determining a target scene type of each resource block currently located on each time slot in a current interference detection period according to an interference scene reference parameter corresponding to each resource block; and when the determined target scene type is an interference-free scene, the adopted load balancing mode is an MRC mode, and when the determined target scene type is a strong interference scene or a weak interference scene, the adopted load balancing mode is an IRC mode.
2. The method of claim 1, wherein determining the interference scenario reference parameter corresponding to each resource block in the first slot according to the interference and noise value N1 comprises:
for each resource block in the first time slot, determining a resource block covariance ratio average value of the resource block in the first time slot according to the interference and noise value N1;
and determining the mean value of the covariance ratio of the resource blocks on the first time slot as the reference parameter of the interference scene corresponding to the resource block.
3. The method of claim 2, wherein the determining the mean value of the covariance ratio of the resource block in the first slot according to the interference and noise value N1 comprises:
calculating interference degree parameters among noise parameters corresponding to the resource block according to the interference and noise value N1
；
Interference degree parameter
And substituting the average value into a resource block covariance ratio average value formula to obtain a resource block covariance ratio average value.
4. The method of claim 2, wherein the determining a current target scene type of each resource block in each slot in a current interference detection period according to the interference scene reference parameter corresponding to each resource block comprises:
for each resource block on the first time slot, determining a target resource block covariance ratio average value range matched with the resource block covariance ratio average value of the resource block from the set covariance ratio average value range of each resource block; when the target resource block covariance ratio average range is the resource block covariance ratio average range corresponding to the non-interference scene, determining that the candidate scene type corresponding to the resource block is the non-interference scene; when the target resource block covariance ratio average range is the resource block covariance ratio average range corresponding to the strong interference scene, determining that the candidate scene type corresponding to the resource block is the strong interference scene; when the target resource block covariance ratio average range is the resource block covariance ratio average range corresponding to the weak interference scene, determining that the candidate scene type corresponding to the resource block is the weak interference scene;
and determining the current target scene type of each resource block according to the determined candidate scene type corresponding to each resource block.
5. The method of claim 4, wherein the determining the current target scene type of each resource block according to the determined candidate scene types corresponding to the resource blocks comprises:
determining a first resource block coverage range when the candidate scene type is an interference-free scene, and determining an intersection P of the first resource block coverage range and a resource block coverage range occupied by the interference-free scene in the last interference detection period1；
Determining a second resource block coverage range when the candidate scene type is a strong interference scene, and determining an intersection P of the second resource block coverage range and a resource block coverage range occupied by the strong interference scene in the last interference detection period2；
Determining a third resource block coverage range when the candidate scene type is a weak interference scene, and determining an intersection P of the third resource block coverage range and a resource block coverage range occupied by the weak interference scene in the last interference detection period3；
When the basis is intersected with P1Intersect P2Intersect P3When the interference state in the last interference detection period is determined to be updated, determining the candidate scene type corresponding to each resource block on the first time slot in the current interference detection period as the target scene type, and determining the candidate scene type according to the intersection P1Intersect P2Intersect P3When the interference state in the last interference detection period is determined to be kept, determining the target scene type corresponding to each resource block on the first time slot in the current interference detection period according to the interference state in the last interference detection period; and the interference state in the last interference detection period at least comprises the scene type corresponding to each resource block on the first time slot in the last interference detection period.
6. The method of claim 5, wherein the method is based on the intersection P1Intersect P2Intersect P3When determining to update the interference state in the last interference detection period, the method further includes:
determining a scene interference degree parameter corresponding to an average particle value matched with a target scene type according to an interference and noise value N1 on the time slot and the average particle value matched with the target scene type aiming at each resource block on each time slot in a current interference detection period;
according to the scene interference degree parameter of each resource block in the current interference detection period, calculating an equalization parameter for equalizing the signal to be demodulated;
when the basis is intersected with P1Intersect P2Intersect P3When the interference state in the last interference detection period is determined to be maintained, the method further comprises the following steps:
determining a scene interference degree parameter corresponding to an average particle value matched with a target scene type according to the interference and noise value N1 on the time slot and the average particle value matched with the target scene type aiming at each resource block on each time slot in the last interference detection period;
and calculating an equalization parameter for equalizing the signal to be demodulated according to the scene interference degree parameter of each resource block in the last interference detection period.
7. An interference suppression apparatus, comprising:
an interference and noise value determining unit for obtaining an interference and noise value N on a first time slot in a current interference detection period1；
An interference scene reference parameter determining unit for determining an interference scene reference parameter according to the interference and noise value N1Determining an interference scene reference parameter corresponding to each resource block on the first time slot; the interference scene reference parameter is used for determining a target scene type;
the scene type determining unit is used for determining the scene type of the frequency band where the pilot signal belongs according to the mean value result and the threshold range corresponding to the first time slot of the pilot signal in each period aiming at each pilot signal;
the mode determining unit is used for determining the current target scene type of each resource block on each time slot in the current interference detection period according to the interference scene reference parameter corresponding to each resource block; and when the determined target scene type is an interference-free scene, the adopted load balancing mode is an MRC mode, and when the determined target scene type is a strong interference scene or a weak interference scene, the adopted load balancing mode is an IRC mode.
8. The apparatus of claim 7, wherein the interference scenario reference parameter determination unit comprises:
a resource block covariance ratio average determining subunit, configured to determine, for each resource block in the first slot, a resource block covariance ratio average of the resource block in the first slot according to the interference and noise value N1;
and the interference scene reference parameter determining subunit is configured to determine the average value of the covariance ratio of the resource blocks in the first time slot as the interference scene reference parameter corresponding to the resource block.
9. The apparatus of claim 8, wherein the resource block covariance ratio mean determination subunit is specifically configured to:
calculating interference degree parameters among noise parameters corresponding to the resource block according to the interference and noise value N1
；
Interference degree parameter
And substituting the average value into a resource block covariance ratio average value formula to obtain a resource block covariance ratio average value.
10. An electronic device comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor; the processor is configured to execute machine executable instructions to perform the method steps of any of claims 1-6.
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