CN107070451B - Equipment ADC precision configuration method in large-scale MIMO system - Google Patents

Equipment ADC precision configuration method in large-scale MIMO system Download PDF

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CN107070451B
CN107070451B CN201710030997.9A CN201710030997A CN107070451B CN 107070451 B CN107070451 B CN 107070451B CN 201710030997 A CN201710030997 A CN 201710030997A CN 107070451 B CN107070451 B CN 107070451B
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dac
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许威
徐锦丹
张华�
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Southeast University
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    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M1/00—Analogue/digital conversion; Digital/analogue conversion
    • H03M1/002—Provisions or arrangements for saving power, e.g. by allowing a sleep mode, using lower supply voltage for downstream stages, using multiple clock domains or by selectively turning on stages when needed
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M1/00—Analogue/digital conversion; Digital/analogue conversion
    • H03M1/12—Analogue/digital converters
    • H03M1/1205—Multiplexed conversion systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention discloses a method for configuring the precision of an ADC (analog to digital converter) of equipment in a large-scale MIMO (multiple input multiple output) system. In a large-scale MIMO system, due to the large number of antennas, configuring a DAC and an ADC with low accuracy for each antenna unit can effectively control the overall power consumption of the transmission system. The invention considers the down link, the large-scale antenna base station as the transmitting terminal configures a low-power consumption 1-bit quantification DAC for each antenna, and the invention can calculate and determine the optimal precision of the receiving terminal ADC meeting the target speed requirement according to the fixed system parameters such as the number of the base station antennas and the terminal equipment. The method is simple in calculation, can realize the target performance of the system with the minimum power consumption cost, and has guiding significance on large-scale MIMO system configuration and hardware design.

Description

Equipment ADC precision configuration method in large-scale MIMO system
Technical Field
The invention relates to a precision configuration method of equipment ADC (analog-to-digital conversion unit) in a large-scale MIMO (multiple input multiple output) system, belonging to the wireless communication technology.
Background
In recent years, in order to meet the rapidly increasing mobile data transmission needs, wireless communication systems are urgently required to improve spectrum transmission efficiency. MIMO, that is, a plurality of transmitting antennas and receiving antennas are used at the transmitting end and the receiving end, respectively, can make full use of spatial resources to suppress channel fading, and significantly improve the channel capacity of the system without increasing spectrum resources and overall transmitting power, and has obvious advantages. The massive MIMO technology proposed on this basis has become a key component of the next generation wireless communication system (5G). The technology greatly improves the spatial freedom of wireless signal transmission by configuring hundreds or even thousands of antennas for a base station, thereby improving the frequency spectrum efficiency and the channel capacity of a system through space division multiplexing. In a multi-user MIMO scheme, one base station serves multiple single-antenna users simultaneously, and multiple data streams may be transmitted simultaneously between the base station and the users. Each user can still obtain considerable spatial freedom as long as the number of base station antennas is greater than the number of users.
However, the increase in the number of antennas also increases the complexity of hardware implementation. In the downlink, each base station transmitting antenna needs to be configured with a DAC (digital-to-analog conversion unit), and each terminal receiving antenna needs to be configured with an ADC. Therefore, hardware cost and power consumption cost rapidly increase as the number of antennas increases. This greatly limits the application of massive MIMO. There are currently two main solutions to this problem. Firstly, the number of the DACs and the ADCs is reduced, and the radio frequency link is reduced by adopting the hybrid transceiver, for example, digital precoding is performed at a transmitting end, then digital-to-analog conversion is performed, and then analog precoding is performed. The digital precoding still adopts the traditional zero-breaking (ZF), Maximum Ratio Transmission (MRT) precoding and other methods, while the analog precoding needs to be designed additionally. When beamforming is performed, the lower limit of the number of radio frequency links is the number of actually transmitted data streams, and the upper limit of the beamforming gain is determined by the number of antennas; and secondly, the precision of the DAC and the ADC is reduced, and even only the DAC and the ADC with 1 bit are adopted in an extreme case, because the power consumption of the DAC and the ADC is increased exponentially along with the increase of the number of quantization precision bits. Most of the current schemes consider low precision DACs or ADCs separately. Therefore, the problem of the precision configuration of the two is jointly considered, and especially the trade-off of the precision of the two is of great significance to the design of a practical system. If the two schemes are combined, the power consumption of the massive MIMO system can be reduced from two aspects at the same time.
When the transmitting end is configured with 1-bit DAC, it is not necessary for the receiving end to be configured with infinite-precision ADC. Because the low-precision ADC can also obtain the approximate maximum data transmission rate, the power consumption is reduced by a lot compared with the infinite-precision ADC. In other words, the accuracy of the ADC requires a trade-off between system transmission performance and hardware and power consumption costs. The precision of the ADC at the receiving end is designed according to the specific data rate requirement, and the method has very important guiding significance for system implementation.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects in the prior art, the invention provides a method for calculating the precision configuration of an equipment ADC in a large-scale MIMO system.
The technical scheme is as follows: in order to achieve the purpose, the invention adopts the technical scheme that: the method comprises the following steps:
(1)according to the Bussang theory, when a base station transmitting antenna is configured with a 1-bit DAC and a terminal receiving antenna is configured with an ideal infinite precision ADC, the receiving signal-to-noise ratio gamma of each user in a downlinkidealComprises the following steps:
Figure BDA0001211412660000021
where ρ isDAC0.3634, representing the influence parameters of 1-bit quantization DAC on the receiving signal-to-noise ratio; the number of base station antennas is N, the number of terminal single antenna users is M, the transmitting power is P, and the thermal noise power of the receiving end is N0；
(2) According to the Bussang theory and the step (1), a base station transmitting antenna is configured with a 1-bit DAC, and a terminal receiving antenna is configured with a quantization bit number of kADCFor the low-precision ADC of (1), the received signal-to-noise ratio γ of each user in the downlink is:
Figure BDA0001211412660000022
wherein k isADCRho represents the attenuation factor of the low-precision ADC to the receiving noise ratio; ρ and kADCThe relationship of (1) is:
Figure BDA0001211412660000023
(3) when the target data rate is η times the ideal rate, according to the shannon formula, there is
log(1+γ)＝ηlog(1+γideal)
Substituting equation (2) can solve the attenuation factor ρ:
Figure BDA0001211412660000031
(4) after rho is obtained according to the step (3), calculating a configuration value k required by the ADC precision of the receiving antenna of the terminal according to a formula (3)ADC：
Figure BDA0001211412660000032
Wherein,
Figure BDA0001211412660000033
indicating rounding up.
Has the advantages that: compared with the prior art, the precision configuration method of the equipment ADC in the large-scale MIMO system has the following advantages that: 1. the invention starts from the overall situation of a large-scale MIMO system, balances the data transmission rate and the system hardware and power consumption cost on the premise of configuring a 1-bit DAC at a transmitting end, determines the precision of an ADC at a receiving end and can obtain the overall optimal performance; 2. the invention approximates the nonlinear influence of DAC and ADC quantization precision on the user data rate to linearity, simplifies the solving process and reduces the calculation complexity; 3. the number N of base station antennas, the number M of users, the transmission power P and the noise power N in the invention0The value is flexible; therefore, the scheme is suitable for a multi-user large-scale MIMO system under any signal-to-noise ratio; 4. the method has important value for the design of an actual system; the present invention can quickly determine the accuracy of the ADC to achieve the required performance at the lowest power consumption cost for a given data rate requirement.
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FIG. 1 is a block diagram of a transmitting end and a receiving end of a massive MIMO system according to the present invention;
FIG. 2 is a schematic diagram of a low-precision ADC processing signals at a receiving end according to the present invention;
FIG. 3 is a graphical representation of the calculated ADC accuracy as a function of target data rate for a given condition in accordance with the present invention;
fig. 4 is a schematic diagram of ADC accuracy as a function of signal-to-noise ratio calculated according to the present invention under given conditions.
Detailed Description
The present invention will be further described with reference to the accompanying drawings.
Fig. 1 shows a block diagram of a transmitting end and a receiving end of a massive MIMO system in the present invention. At a transmitting end, original data are modulated to generate M symbols, N complex signals are generated through precoding, real parts and imaginary parts of the complex signals respectively generate analog signals through a DAC, and finally the analog signals are transmitted by N antennas after passing through a radio frequency link (RF). At a receiving end, M single-antenna users respectively receive signals, the signals are processed by a radio frequency link and then processed by an ADC module to obtain digital signals, and finally, original data are recovered through demodulation.
FIG. 2 shows the operation of a low-precision ADC on a received signal, the precision k of the ADCADCIs 1 bit, the number of transmit antennas N is 32, and the number of users M is 8. In the figure, a signal y is a received signal processed by a radio frequency link, and the y is continuously distributed between-5 and 10; signal yqFor the output signal after ADC processing, y can be seen from the figureqThere are only 2 values. Obviously, the received signal is distorted by the low-precision ADC, and k isADCThe smaller the distortion. Therefore, the use of a low-precision ADC for reducing the power consumption of the system has an influence on the transmission performance of the system. Specifically, the transmission rate may be reduced.
FIG. 3 shows the P/N ratio0And when the target data rate is 0-100% of the ideal rate respectively under the conditions of 0dB, N128 and M8, the ADC precision is calculated according to the algorithm of the invention. As can be seen from the figure, if the data rate is to reach 0-39% of the ideal rate, the ADC precision is at least 1 bit; if 40% -76% is to be reached, at least 2 bits are needed; if 77% -93% is to be reached, at least 3 bits are to be reached; if 94% -98% is to be reached, at least 4 bits are to be reached. Calculating kADCThe method comprises the following specific steps:
(1) by N128, M8, signal-to-noise ratio P/N00dB, the received signal-to-noise ratio γ for each user in the downlink is calculated with a 1-bit DAC and an ideal infinite precision ADC deployedidealThe formula is as follows:
Figure BDA0001211412660000041
where ρ isDAC0.3634, the influence of 1-bit quantization DAC on the received signal-to-noise ratioAnd (4) counting.
(2) According to the Bussang theory and the step (1), a base station transmitting antenna is configured with a 1-bit DAC, and a terminal receiving antenna is configured with a quantization bit number of kADCFor the low-precision ADC of (1), the received signal-to-noise ratio γ of each user in the downlink is:
Figure BDA0001211412660000042
wherein k isADCRho represents the attenuation factor of the low-precision ADC to the receiving noise ratio; ρ and kADCThe relationship of (1) is:
Figure BDA0001211412660000043
(3) when the target data rate is η times the ideal rate, there is log (1+ γ) η log (1+ γ) according to shannon's formulaideal) Substituting the target data rate η and equation (2) into the equation to calculate the attenuation factor ρ, the equation is:
Figure BDA0001211412660000051
(4) calculating ADC precision k of the receiving antenna of the terminal according to the rho obtained in the step (2) and a formula (3)ADCThe formula is as follows:
Figure BDA0001211412660000052
wherein,
Figure BDA0001211412660000053
indicating rounding up.
Fig. 4 shows the ADC accuracy k calculated by the present invention when the target data rate η is 50%, 70%, and 90% respectively under the conditions of N being 128 and M being 8ADCAssociated signal-to-noise ratio P/N0Schematic representation of the variations. P/N0Is in the range of-15 dB to 15dB it can be seen from the figure that the higher the signal to noise ratio, k, for the same target data rate ηADCThe larger the value. Is illustrated in the followingIn actual systems, the higher the signal-to-noise ratio, the higher the requirements on hardware such as ADCs.
Starting from the overall situation of a large-scale MIMO system, the invention obtains the ADC precision k according to the steps (1) to (4) on the premise that a transmitting end is configured with a 1-bit DACADCIs to ensure that the data rate reaches η gammaidealWith minimal precision. The smaller the precision, the smaller the hardware and power consumption costs. The present invention thus balances data transfer rates against system hardware and power consumption costs to achieve the target rate at minimal cost.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.

Claims (1)

1. A method for configuring the precision of an equipment ADC in a large-scale MIMO system is characterized by comprising the following steps: the method comprises the following steps:
(1) according to the Bussang theory, when a base station transmitting antenna is configured with a 1-bit DAC and a terminal receiving antenna is configured with an ideal infinite precision ADC, the receiving signal-to-noise ratio gamma of each user in a downlinkidealComprises the following steps:
Figure FDA0002497692540000011
where ρ isDAC0.3634, representing the influence parameters of 1-bit quantization DAC on the receiving signal-to-noise ratio; the number of base station antennas is N, the number of terminal single antenna users is M, the transmitting power is P, and the thermal noise power of the receiving end is N0；
(2) According to the Bussang theory and the step (1), a base station transmitting antenna is configured with a 1-bit DAC, and a terminal receiving antenna is configured with a quantization bit number of kADCFor the low-precision ADC of (1), the received signal-to-noise ratio γ of each user in the downlink is:
Figure FDA0002497692540000012
wherein k isADCRho represents the attenuation factor of the low-precision ADC to the receiving noise ratio; ρ and kADCThe relationship of (1) is:
Figure FDA0002497692540000013
(3) when the target data rate is η times of the ideal rate, according to the Shannon formula, the target data rate is obtained
log(1+γ)＝ηlog(1+γideal)
Substituting equation (2) to solve the attenuation factor ρ:
Figure FDA0002497692540000014
(4) after rho is obtained according to the step (3), calculating a configuration value k required by the ADC precision of the receiving antenna of the terminal according to a formula (3)ADC：
Figure FDA0002497692540000015
Wherein,
Figure FDA0002497692540000016
indicating rounding up.
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CN108365873B (en) * 2018-01-12 2021-03-23 东南大学 Large-scale MIMO self-adaptive transmission method adopting low-precision ADC millimeter waves
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CN1770672A (en) * 2005-10-21 2006-05-10 北京交通大学 Space-time block code MT-CDMA system uplink transmitting and receiving method
WO2006112030A1 (en) * 2005-04-14 2006-10-26 Matsushita Electric Industrial Co., Ltd. Wireless reception apparatus and wireless reception method
CN101547066A (en) * 2008-03-25 2009-09-30 中兴通讯股份有限公司 MU-MIMO mode-based method for indicating downlink precoding information
CN101621321A (en) * 2008-06-30 2010-01-06 三星电子株式会社 Closed loop constant modulus multi-user MIMO system and a control signaling processing method thereof

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2006112030A1 (en) * 2005-04-14 2006-10-26 Matsushita Electric Industrial Co., Ltd. Wireless reception apparatus and wireless reception method
CN1770672A (en) * 2005-10-21 2006-05-10 北京交通大学 Space-time block code MT-CDMA system uplink transmitting and receiving method
CN101547066A (en) * 2008-03-25 2009-09-30 中兴通讯股份有限公司 MU-MIMO mode-based method for indicating downlink precoding information
CN101621321A (en) * 2008-06-30 2010-01-06 三星电子株式会社 Closed loop constant modulus multi-user MIMO system and a control signaling processing method thereof

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