Ad hoc network node search optimization method based on ARM platform

Abstract

The invention particularly relates to an ad hoc network node search optimization method based on an ARM platform. According to the ad hoc network node search optimization method based on the ARM platform, in a distributed network broadcast subframe time-frequency resource grid, six RBs are occupied on a frequency domain, one subframe is occupied on a time domain, each RB comprises 12 subcarriers, and each subframe comprises 14 symbols. Each subcarrier is 15Khz, and each subframe is 1ms; a coarse synchronization signal is designed in a first symbol of a subframe, an air interface signal is immediately copied to a DDR after coarse synchronization is completed, and node search is completed in a period in an offline processing mode. According to the ad hoc network node search optimization method based on the ARM platform, channel pre-compensation operation can be carried out on broadcast signals through special broadcast subframe design, so that channel interpolation operation of broadcast channels is optimized, channel interpolation time consumption is shortened, platform resources are saved, and the method is suitable for hardware with low cost and weak processing capacity. And the delay requirement of node search can also be met.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a self-organizing network node search optimization method based on an ARM platform. Background Art

[0002] Due to the uncertainty of wireless channels, channel estimation needs to be completed in advance before demodulating and decoding the physical broadcast channel, which is usually achieved using a pilot sequence. At the same time, since the pilot does not carry information, the pilot is required to occupy as few time domain and frequency domain resources as possible, so the pilot signal is sparsely arranged in the time and frequency domain. For example, the pilot density of 4G (LTE) is 2 / 7 in the time domain and 1 / 6 in the frequency domain, that is, 2 out of 7 symbols in the time domain have pilots, and one out of 6 subcarriers in the frequency domain is a pilot.

[0003] Due to the time-varying characteristics and frequency domain selectivity of wireless channels, in order to accurately demodulate data, it is necessary to derive the channel characteristics of the data subcarriers through interpolation. Common interpolation methods include Wiener filter interpolation and Bessel interpolation. These two types of interpolation are widely used in the field of wireless communications due to their good performance.

[0004] However, these interpolation methods have high computational complexity and require accurate prior parameter input to obtain appropriate interpolation coefficients, such as Doppler frequency shift, signal-to-noise ratio, noise variance, etc. In order to obtain these accurate parameters, additional calculations are required, further increasing the hardware load. For low-cost distributed network hardware with limited processing power, a large amount of calculations will lead to high processing delays, affecting user experience.

[0005] In order to optimize the time-frequency domain resource design, tap the processor capability, and optimize the broadcast channel processing delay in the distributed network node search process under the condition of limited processing capability, the present invention proposes an ad hoc network node search optimization method based on ARM platform. Summary of the invention

[0006] In order to make up for the defects of the prior art, the present invention provides a simple and efficient ad hoc network node search optimization method based on an ARM platform.

[0007] The present invention is achieved through the following technical solutions:

[0008] A node search optimization method for an ad hoc network based on an ARM platform, characterized in that: in a distributed network broadcast subframe time-frequency resource grid, 6 RBs are occupied in the frequency domain and 1 subframe is occupied in the time domain, each RB contains 12 subcarriers, and each subframe contains 14 symbols. Each subcarrier is 15Khz, and each subframe is 1ms;

[0009] The coarse synchronization signal is designed in the first symbol of the subframe. After the coarse synchronization is completed, the air interface signal is immediately copied to the DDR (double rate synchronous dynamic random access memory). Through offline processing, the node search is completed within one cycle.

[0010] By processing offline data, the processing delay of channel estimation is optimized, including the following steps:

[0011] Step S1: coarse synchronization signal processing, searching for the broadcast subframe position in the time domain, using signal correlation to complete coarse synchronization in the time domain, and adjusting the signal reception time;

[0012] Step S2, after completing the rough synchronization, copy the data from symbol 1 to symbol 12 to DDR for offline processing;

[0013] Step S3: fine synchronization signal processing;

[0014] Step S4: Compensate the time-frequency offset of the data copied to the DDR in step S2 to ensure that the result of step S5 is free from the influence of the time-frequency offset;

[0015] Step S5: completing channel estimation of the pilot signal;

[0016] Step S6: The broadcast channel completes signal processing by using the minimum Euclidean distance channel estimation result.

[0017] In step S1, since the coarse synchronization signal is designed in the first symbol, the position of the broadcast signal can be determined after the sliding correlation detection is completed in the time domain.

[0018] In step S3, the fine synchronization signal is designed as two separate columns of signals to further complete the calculation of timing synchronization and frequency deviation.

[0019] In step S6, the broadcast channel takes pilot numbers 0 to 5, and the broadcast resource uses numbers to indicate which pilot to use, with the closest Euclidean distance in the time-frequency domain being given priority. When the Euclidean distances are the same, the pilot with a lower frequency domain is used.

[0020] In step S6, by using adjacent pilots as channel estimation results, channel interpolation has no multiplication, addition and shift operations, and only designs memory read and write operations, and reuses the data prefetch function of the ARM-R5 platform. During memory operations, cache lines are used as units, and memory copies are performed through DMA to improve memory read and write efficiency.

[0021] An ARM platform-based ad hoc network node search and optimization device, characterized in that it includes a memory and a processor; the memory is used to store a computer program, and the processor is used to implement the above method steps when executing the computer program.

[0022] A readable storage medium, characterized in that: a computer program is stored on the readable storage medium, and the computer program implements the above method steps when executed by a processor.

[0023] The beneficial effects of the present invention are as follows: the self-organizing network node search optimization method based on the ARM platform can perform channel pre-compensation operations on broadcast signals through a special broadcast subframe design, thereby optimizing the channel interpolation operations of the broadcast channels and shortening the channel interpolation time. It not only saves platform resources, but also can meet the node search delay requirements for low-cost hardware with weak processing capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Attached Figure 1 It is a schematic diagram of the broadcast channel processing process of the present invention.

[0026] Attached Figure 2 It is a schematic diagram of the distributed network broadcast subframe time-frequency resource grid of the present invention.

[0027] Attached Figure 3 This is a schematic diagram of taking pilot signals for the broadcast channel of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] In the self-organizing network communication chip system, in order to reduce costs, low-cost hardware is usually preferred. However, the processing power of these hardware is weak, and the task priorities are different. Low-priority tasks will be interrupted by high-priority tasks. Therefore, the data part, such as signal processing, needs to be optimized to meet system requirements.

[0030] Since the node search process involves a lot of content, including coarse synchronization signal processing, fine synchronization signal processing, pilot signal processing, and broadcast signal, data processing cannot be completed within one subframe. It usually takes multiple broadcast cycles to complete the node search operation.

[0031] The node search optimization method for self-organizing network based on ARM platform, the distributed network broadcast subframe time-frequency resource grid is as shown in the attached Figure 2 As shown: 6 RBs are occupied in the frequency domain and 1 subframe is occupied in the time domain. Each RB contains 12 subcarriers and each subframe contains 14 symbols. Each subcarrier is 15Khz and each subframe is 1ms.

[0032] The coarse synchronization signal is designed in the first symbol of the subframe. After the coarse synchronization is completed, the air interface signal is immediately copied to the DDR (double rate synchronous dynamic random access memory). Through offline processing, the node search is completed within one cycle.

[0033] By processing offline data, the processing delay of channel estimation is optimized, including the following steps:

[0034] Step S1: coarse synchronization signal processing, searching for the broadcast subframe position in the time domain, using signal correlation to complete coarse synchronization in the time domain, and adjusting the signal reception time;

[0035] Step S2, after completing the rough synchronization, copy the data from symbol 1 to symbol 12 to DDR for offline processing;

[0036] Step S3: fine synchronization signal processing;

[0037] Step S4: Compensate the time-frequency offset of the data copied to the DDR in step S2 to ensure that the result of step S5 is free from the influence of the time-frequency offset;

[0038] Step S5: completing channel estimation of the pilot signal;

[0039] Step S6: The broadcast channel completes signal processing by using the minimum Euclidean distance channel estimation result. Figure 3 Schematic diagram of taking pilot signals from broadcast channels.

[0040] In step S1, since the coarse synchronization signal is designed in the first symbol, the position of the broadcast signal can be determined after the sliding correlation detection is completed in the time domain.

[0041] In step S3, the fine synchronization signal is designed as two separate columns of signals to further complete the calculation of timing synchronization and frequency deviation.

[0042] In step S6, the broadcast channel takes pilot numbers 0 to 5, and the broadcast resource uses numbers to indicate which pilot to use, with the closest Euclidean distance in the time-frequency domain being given priority. When the Euclidean distances are the same, the pilot with a lower frequency domain is used.

[0043] Without considering the prior parameters, the calculation amount and processing time of the two antenna data using the interpolation method are:

[0044] In the frequency domain, 4 symbols and 6 RBs and 3 pilots are interpolated into 4 symbols and 6 RBs and 12 subcarriers. Through 3136 multiplications, 2560 additions, and 576 saturation shift operations, plus memory read and write operations, the total time consumption is about 750us.

[0045] In the time domain, 4 symbols and 6 RBs and 12 subcarriers are interpolated into 9 symbols and 6 RBs and 12 subcarriers, which requires 20736 multiplications, 15552 additions, and 5184 saturation shift operations. Together with the memory read and write operations, the total time consumption is about 1063us.

[0046] The total time consumption of channel interpolation is 1813us.

[0047] In step S6, by using adjacent pilots as channel estimation results, channel interpolation has no multiplication, addition and shift operations, and only designs memory read and write operations, and reuses the data prefetch function of the ARM-R5 platform. During memory operations, cache lines are used as units, and memory copies are performed through DMA to improve memory read and write efficiency.

[0048] For example, symbols 3&4&5 use the same channel parameters, symbols 7&8&9 use the same channel parameters, and symbols 11&12 use the same channel parameters. In this case, memory copying can be performed through DMA. The overall time consumption of the optimized channel interpolation module is 112us.

[0049] The pseudo code is as follows:

[0050]

[0051] The ARM platform-based ad hoc network node search optimization device comprises a memory and a processor; the memory is used to store a computer program, and the processor is used to implement the above method steps when executing the computer program.

[0052] The readable storage medium stores a computer program, and when the computer program is executed by a processor, the above method steps are implemented.

[0053] Compared with the existing technology, the self-organizing network node search optimization method based on the ARM platform can perform channel pre-compensation operations on the broadcast signal through a special broadcast subframe design, thereby optimizing the channel interpolation operation of the broadcast channel and optimizing the channel interpolation time from the original 1813us to 112us, which can save platform resources and meet the node search latency requirements for low-cost hardware with weak processing capabilities.

[0054] The embodiment described above is only one specific implementation of the present invention. Common changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention should be included in the protection scope of the present invention.

Claims

1. A node search optimization method for an ad hoc network based on an ARM platform, characterized in that: In the distributed network broadcast subframe time-frequency resource grid, 6 RBs are occupied in the frequency domain and 1 subframe is occupied in the time domain. Each RB contains 12 subcarriers and each subframe contains 14 symbols. Each subcarrier is 15Khz and each subframe is 1ms. The coarse synchronization signal is designed in the first symbol of the subframe. After the coarse synchronization is completed, the air interface signal is immediately copied to the DDR. Through offline processing, the node search is completed within one cycle.

2. The method for optimizing node search in an ad hoc network based on an ARM platform according to claim 1, characterized in that: By processing offline data, the processing delay of channel estimation is optimized, including the following steps: Step S1: coarse synchronization signal processing, searching for the broadcast subframe position in the time domain, using signal correlation to complete coarse synchronization in the time domain, and adjusting the signal reception time; Step S2, after completing the rough synchronization, copy the data from symbol 1 to symbol 12 to DDR for offline processing; Step S3: fine synchronization signal processing; Step S4: Compensate the time-frequency offset of the data copied to the DDR in step S2 to ensure that the result of step S5 is free from the influence of the time-frequency offset; Step S5: completing channel estimation of the pilot signal; Step S6: The broadcast channel completes signal processing by using the minimum Euclidean distance channel estimation result.

3. The method for optimizing node search in an ad hoc network based on an ARM platform according to claim 2, characterized in that: In step S1, since the coarse synchronization signal is designed in the first symbol, the position of the broadcast signal can be determined after the sliding correlation detection is completed in the time domain.

4. The method for optimizing node search in an ad hoc network based on an ARM platform according to claim 2, characterized in that: In step S3, the fine synchronization signal is designed as two separate columns of signals to further complete the calculation of timing synchronization and frequency deviation.

5. The method for optimizing node search in a self-organizing network based on an ARM platform according to claim 2, characterized in that: In step S6, the broadcast channel takes pilot numbers 0 to 5, and the broadcast resource uses numbers to indicate which pilot to use, with the closest Euclidean distance in the time-frequency domain being given priority. When the Euclidean distances are the same, the pilot with a lower frequency domain is used.

6. The method for optimizing node search in a self-organizing network based on an ARM platform according to claim 5, characterized in that: In step S6, by using adjacent pilots as channel estimation results, channel interpolation has no multiplication, addition and shift operations, and only designs memory read and write operations, and reuses the data prefetch function of the ARM-R5 platform. During memory operations, cache lines are used as units, and memory copies are performed through DMA to improve memory read and write efficiency.

7. A node search and optimization device for a self-organizing network based on an ARM platform, characterized in that: The method comprises a memory and a processor; the memory is used to store a computer program, and the processor is used to implement the method steps described in any one of claims 1 to 6 when executing the computer program.

8. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps described in any one of claims 1 to 6 are implemented.

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