CN106533590B - Uplink channel quality measurement method based on receiving end EVM - Google Patents
Uplink channel quality measurement method based on receiving end EVM Download PDFInfo
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Abstract
The invention proposes a kind of uplink channel quality measurement methods based on receiving end EVM, refer to the low technical problem of throughput of system existing for mass measuring method for solving existing channel, realize step are as follows: construction uplink Adaptable System model, and establish the mathematical relationship of frequency-region signal between the model transmitting terminal and receiving end；According to the pilot frequency configuration form of 3GPP standard, pilot signal is extracted from the frequency-region signal of receiving end；Estimating system domain channel response；Estimate the measuring signal based on receiving end EVM channel quality measurement algorithm；Turbo code decoding is carried out to transmitting terminal time-domain signal estimated value, the bit data after being decoded, and re-encoding and re-modulation are carried out to the bit data, obtain ideal reference signal；Receiving end EVM is calculated according to measuring signal and ideal reference signal using Error Vector Magnitude calculation formula；Select modulation coding scheme MCS.Channel quality measurement accuracy of the present invention is high, computation complexity is low, robustness is high, is suitable for wireless communication system.
Description
Technical field
The invention belongs to wireless communication fields, are related to a kind of signal channel quality measuring method, and in particular to one kind is based on reception
Hold error vector magnitude adaptive uplink system signal channel quality measuring method, be suitable for ground based cellular communication system,
The wireless communication systems such as satellite communication system, Massive-MIMO system and point-to-point link Transmission system.
Background technique
In a wireless communication system, channel is the time varying channel there are multipath effect, transmitting terminal if it is known that channel elder generation
Testing information may be selected by the modulation system for being more suitable for transmission and code rate to emit data, to reduce transmission process
Influence of the middle various factors to signal is received improves system performance preferably to adapt to changeable transmission condition.Thus may be used
See, in order to promote the performance of communication system, the research of link circuit self-adapting is very necessary.Uplink adaptively includes power
Control technology and rate control techniques.Wherein power control techniques are to adjust transmission power by dynamic, maintain receiving end certain
Signal-to-noise ratio, to guarantee the transmission quality of link.And rate control techniques are then the technologies that link circuit self-adapting mainly uses,
Namely what is often called adaptive modulation and coding technology (AMC), the information that eNodeB changes according to the channel circumstance that user terminal provides,
It is dynamically selected the mode (MCS) of modulation and coding, while meeting system BLER limitation, maximizes the property of lifting system
It can, it is ensured that the transmission quality of link.Specifically, be exactly it is closer from base station, the preferable user of channel condition can be assigned high-order
Modulation system and higher code rate；And farther out from base station, the bad user of channel condition, receiving end in order to guarantee correctly
Demodulation, needs more redundancies, but more redundancy can reduce code rate, thus distribute be low order modulation
Method and lower code rate.
In adaptive uplink system, receiving end is needed to transmitting terminal feeding back channel state information, this just need into
Row channel quality measurement, existing method use Signal to Interference plus Noise Ratio (SINR) generally to characterize the transmission quality of channel, that is, will
A module of the SINR as channel quality measurement, receiving end carry out the selection of MCS according to the SINR that estimation obtains, so
After feed back to transmitting terminal, transmitting terminal carries out the allocation optimum of configured transmission next time according to the channel quality information of feedback.For
In terms of the research of this respect mostly concentrates on the measurement of effective SINR, basic thought is to estimate each subcarrier first
The SINR value mapping of these subcarriers is become one and is able to reflect entire link by SINR then by certain mapping method
Effective SINR of average behavior, and carry out according to this effective SINR the selection of MCS.Common method has the effective SINR of index to reflect
It penetrates effective SINR mapping (MIESM) algorithm of (EESM) algorithm, mutual information, every bit Average Mutual (MMIB) algorithm, averagely have
Imitate SINR mapping (AESM) algorithm and harmonic average algorithm (Harm-mean).Wherein both algorithms of EESM and MIESM have
Similarity, all from effective SINR mapping (ESM), difference is that the mapping function that they are used is different, respectively index
Mapping function and related mutual information mapping function.But in both algorithms, mapping function all include one tuning because
Son needs off-line simulation to obtain, and its parameter value size depends on MCS, channel status and antenna configuration, so being extremely difficult to
It is optimal, poor robustness, to cause the loss of throughput of system performance.MMIB refers to coded-bit and its log-likelihood ratio (LLR)
Between Average Mutual, MMIB channel quality measurement refers to for wireless channel being equivalent to multiple parallel bit LLR channels,
By the mutual information between the corresponding receiving end LLR value of calculation code bit by effective SINR and bit-level Average Mutual
Set up one-to-one relationship, but due to the calculating of mutual information be it is sufficiently complex, hardly result in its accurate mapping equation,
So the accuracy of MMIB algorithm is lower, in addition to this, the performance of the algorithm largely depends on order of modulation, that is,
Say this algorithm be for the variation of order of modulation it is very sensitive, be not suitable for time-varying characteristics wireless channel in.Harm-
Mean algorithm is using the harmonic-mean of the SINR of multiple subcarriers as equivalent SINR, and AESM algorithm is thought in SC-
In FDMA system, the SINR of all subcarriers is approximately equal, it is possible to be simplified with the operation being averaging and be calculated.But this two
Kind method has certain limitation, is only applicable to frequency and selects not serious scene, although the complexity of both algorithms is smaller, its
Counting accuracy is accordingly poor.
As seen from the above analysis, above-mentioned each method is the equal of a many-to-one mapping, the different sons of two such
Effective SINR of channel may be it is identical, have ignored the difference between different subchannels, selected identical MCS, and this MCS pairs
It may not all be optimal for these subchannels, so measuring accuracy is lower, robustness is poor, to influence systematicness
Can, cause the decline of handling capacity.Therefore, using SINR as the Measure Indexes of channel quality, then the accuracy of its measured value for
The promotion of throughput of system performance is very crucial.But in wireless communications, influence SINR value variation because being known as very
It is more, as fading channel, interference and noise etc., thus want to guarantee its accuracy be it is very difficult, there is certain challenge
Property.
In the uplink, signal will lead to signal and become by channel due to being influenced by noise or interference
Change.If channel condition is preferable, signal is smaller by the variation of channel, conversely, signal can be sent out by channel if channel condition is poor
Raw biggish variation.Therefore in addition to traditional channel quality measurement based on SINR, channel can also be passed through by measuring signal
The variation degree of generation, to judge channel quality, and error vector magnitude EVM (Error Vector Magnitude)
Exactly measure an index of this variation because influence to signal of interference and noise can with signal on planisphere with standard star
The deviation of seat point intuitively shows.Receiving end EVM is defined as the square root of receiving end error vector average power signal
Ratio between the square root of receiving end reference signal average power.It can be seen that the size of receiving end EVM can reflect
Channel quality, when channel condition is preferable, signal is small by channel effect, and receiving end EVM is smaller；When channel condition is poor, signal by
Channel effect is big, and receiving end EVM is larger.And relative to the SINR for estimating each subcarrier, easier it can obtain system
Receiving end EVM.
Summary of the invention
It is an object of the invention to overcome above-mentioned the deficiencies in the prior art, a kind of uplink based on receiving end EVM is proposed
Link Channel Quality measurement method, receiving end according to the instantaneous EVM of system, using off-line simulation obtain receiving end EVM and MCS it
Between mapping table to select suitable MCS, and feed back to transmitting terminal, for being configured to the optimized parameter transmitted next time,
It is meant to ensure that solution existing channel mass measuring method is existing because of channel while meeting uplink adaptive link BLER limitation
Mass measurement accuracy it is low it is high with computation complexity caused by the low technical problem of throughput of system.
To achieve the above object, the technical solution that the present invention takes includes the following steps:
(1) uplink Adaptable System model is constructed, and establishes frequency-region signal between the model transmitting terminal and receiving end
Mathematical relationship, realize step are as follows:
(1a) uses multiple access technology, constructs ground based cellular communication system or satellite communication system or Massive-MIMO system
The adaptive uplink system model of system or point-to-point link Transmission system: including Turbo coding, modulation, layer mapping, DFT
The transmitting terminal of transformation and symbol generation module, including FFT transform, channel estimation, frequency domain equalization, IDFT transformation, demodulation decoding
Receiving end, mimo channel includes that channel quality measurement based on receiving end error vector magnitude EVM and Adaptive Modulation are compiled
The adaptive feedback module of code；
(1b) establishes the mathematical relationship of frequency-region signal between adaptive uplink system model transmitting terminal and receiving end
Obtain the frequency-region signal y of receiving endf:
Wherein Y is receiving end frequency-region signal, and H is system domain channel response, FMThe normalization DFT transform for being M for size,K, l=1,2 ..., M, NTFor transmitting antenna number, INTIt is N for dimensionTUnit vector, x
For transmitting terminal modulated signal, V is that mean value is 0, and variance isWhite Gaussian noise；
(2) it is received according to the pilot frequency configuration form in 3GPP standard from adaptive uplink system model in receiving end
It holds and extracts pilot signal Y in frequency-region signal Yp:
Yp=HpSp+Vp
Wherein, Sp、HpAnd VpRespectively refer to transmitting terminal pilot signal, pilot channel response and white Gaussian noise；
(3) in receiving end, system domain channel response H is estimated:
(3a) uses channel estimation method, according to pilot signal YpTo pilot channel response HpEstimated, obtains pilot tone letter
Road response estimation value
(3b) uses time domain interpolation algorithm, according to pilot channel responseComputing system domain channel response estimated value
(4) estimate the measurement signal Z based on receiving end error vector magnitude EVM channel quality measurement algorithm:
(4a) uses frequency domain equalization algorithm, according to the receiving end frequency-region signal matrix y in step (1b)fIn step (3)
The system domain channel response of acquisitionCalculate the estimated value of transmitting terminal frequency-region signal
The estimated value of (4b) to transmitting terminal frequency-region signalIFFT transformation is carried out, transmitting terminal time-domain signal estimated value is obtained
Measurement signal Z i.e. based on receiving end error vector magnitude EVM channel quality measurement algorithm；
(5) in receiving end, to transmitting terminal time-domain signal estimated valueCarry out Turbo code decoding, the bit number after being decoded
According to, and re-encoding and re-modulation are carried out to the bit data, obtain ideal reference signal R；
(6) Error Vector Magnitude calculation formula is used, what the measurement signal Z and step (5) obtained according to step (4) obtained
Ideal reference signal R calculates receiving end EVM；
(7) in receiving end, modulation coding scheme MCS is selected:
(7a) carries out off-line simulation to adaptive uplink system model, obtains the mapping between receiving end EVM and MCS
Table；
(7b) carries out Multi simulation running to adaptive uplink system model, according to the instantaneous reception in each simulation cycles
EVM value is held, chooses its corresponding MCS in the mapping table between receiving end EVM and MCS, and feed back to transmitting terminal, under
The optimized parameter once transmitted is configured.
Compared with the prior art, the invention has the following advantages:
(1) present invention obtains the mapping table between receiving end EVM and MCS by off-line simulation, and is instantaneously connect according to system
Receiving end EVM chooses its corresponding MCS in the mapping table between receiving end EVM and MCS, is an one-to-one mapping relations, institute
It is higher with its channel quality measurement accuracy, under conditions of meeting system BLER limitation, handling up for system is effectively promoted
Measure performance；
(2) present invention is based on receiving end due to using when measuring to adaptive uplink system channel quality
The signal channel quality measuring method of EVM, computation complexity is small, and robustness is high, can preferably be suitable for adaptive uplink
System, the further throughput performance for improving system.
Detailed description of the invention
Fig. 1 is implementation process block diagram of the invention；
Fig. 2 is adaptive uplink system model schematic diagram of the invention；
Fig. 3 is the schematic diagram for the channel quality measurement index EVM that the present invention uses；
Fig. 4 is the acquisition flow chart of mapping table between receiving end EVM and MCS in the present invention；
Fig. 5 is receiving end EVM and BLER simulation curve figure of the invention；
Fig. 6 is system BLER and handling capacity analogous diagram of the invention.
Specific embodiment
Below in conjunction with the drawings and specific embodiments, present invention is further described in detail.
Referring to Fig.1, realization step of the invention are as follows:
Step 1, using SC-FDMA multiple access technology, construct ground based cellular communication system or satellite communication system or
The adaptive uplink system model of Massive-MIMO system or point-to-point link Transmission system, the present embodiment construction are
LTE system in ground based cellular communication, as shown in Fig. 2, including Turbo coding, modulation, layer mapping, DFT transform and SC-FDMA
The transmitting terminal of symbol generation module, the reception decoded including FFT transform, channel estimation, frequency domain equalization, IDFT transformation, demodulation
End, mimo channel includes channel quality measurement and Adaptive Modulation and Coding based on receiving end error vector magnitude EVM
(AMC) adaptive feedback module.
Step 2, frequency-region signal between constructed adaptive uplink system model transmitting terminal and receiving end is established
Mathematical relationshipObtain the frequency-region signal y of receiving endf:
WhereinIt is that the IDFT that size is M is converted, hr,n=diag { [h1]r,n,[h2]r,n,...,[hM]r,n, [hm]r,n
Refer to n-th of transmitting antenna, the domain channel response of m-th of subcarrier, v under r-th of receiving antennarIt is that mean value is under frequency domain
0, variance isNoise vector, xn=[xn,1,xn,2,...,xn,M]TIt is transmitting terminal after M-QAM is modulated
Time-domain signal, NTFor transmitting antenna number, NRFor receiving antenna number, h is system time domain channel response.
Receiving end frequency-region signal is expressed as matrix form yf:
Wherein Y is receiving end frequency-region signal, and H is system domain channel response, and V is that mean value is 0, and variance isWhite Gaussian
Noise.
Step 3, in receiving end, according to the pilot frequency configuration form of 3GPPLTE standard, from adaptive uplink system model
Pilot signal Y is extracted in the frequency-region signal Y of receiving endp:
In a time slot, different SC-FDMA symbols may have different CP (cyclic prefix) length, and signal is by letter
After road, processing is received in receiving end.Receiving end is receiving after the uplink signal of channel, carries out to signal is received
Time and Frequency Synchronization, and pilot signal Y is extracted from the receiving end frequency-region signal Y Jing Guo Time and Frequency Synchronizationp:
Yp=HpSp+Vp
Wherein, Sp、HpAnd VpRespectively refer to the pilot signal, pilot channel response and white Gaussian noise of transmitting terminal.Transmitting terminal
Pilot signal SpIt is known.
Step 4, in receiving end, system domain channel response H is estimated:
Step 4a, based on the pilot signal Y extracted in step 3p, calculated using LS channel estimation method or MMSE channel estimation
Method is to pilot channel response HpEstimated, obtains pilot channel response estimated value
According to LS channel estimation, then its channel response estimation coefficient are as follows:
According to MMSE channel estimation, then its channel response estimation coefficient are as follows:
Wherein,It is the covariance matrix of pilot channel response and reception signal,It is to receive signal auto-covariance
Matrix.
LS channel estimation method is used widely due to simple and easy and not needing the statistical property of channel, but LS is calculated
The estimated result of method is easy affected by noise, and especially when noise is relatively low, the accuracy of estimation be will be greatly reduced.And
MMSE algorithm has good inhibiting effect for inter-sub-carrier interference and white Gaussian noise.In the present embodiment, believed using MMSE
Channel estimation algorithm.
Step 4b, with time domain interpolation algorithm, according to pilot channel responseComputing system domain channel response estimated valueIt carries out as follows:
Step 4b1, using FFT/IFFT method, to the pilot channel response estimated value obtained in step 4aCarry out IFFT
Transformation, obtains time domain pilot channel response estimated value
Wherein,It is N for sizepIDFT transformation, NpFor the number of pilot channel response,N=0,1 ..., Np- 1, T are matrix transposition.
Step 4b2, clock synchronization field pilot channel response estimation valueInterpolation is carried out, system time domain channel response estimated value is obtained
Wherein N is the number of system channel response.
Step 4b3, to system time domain channel response estimated valueFFT operation is carried out, system domain channel response is obtained
Wherein FNThe DFT transform for being N for size,K=0,1 ..., N-1.
Step 5, estimate the measurement signal Z based on receiving end error vector magnitude EVM channel quality measurement algorithm:
Step 5a is believed using ZF frequency domain equalization algorithm or MMSE frequency domain equalization algorithm according to the receiving end frequency domain in step 2
Number matrix yfWith the system domain channel response obtained in step 4Calculate the estimated value of transmitting terminal frequency-region signal
According to ZF frequency domain equalization algorithm, then its equalizing coefficient isTransmitting terminal frequency-region signal
Estimated value are as follows:
According to MMSE equalization algorithm, then its equalizing coefficient isTransmitting terminal frequency domain letter
Number estimated value are as follows:
In the present embodiment, using ZF frequency domain equalization algorithm.
Step 5b, to the estimated value of transmitting terminal frequency-region signalIFFT transformation is carried out, the estimation of transmitting terminal time-domain signal is obtained
ValueMeasurement signal Z i.e. based on receiving end error vector magnitude EVM channel quality measurement algorithm:
Step 6, to transmitting terminal time-domain signal estimated valueProgress Turbo code decoding, the bit data after being decoded, and
Re-encoding and re-modulation are carried out to the bit data, obtain ideal reference signal R:
Step 6a, first to transmitting terminal time-domain signal estimated valueTurbo code logarithm MAP decoding is carried out, when obtaining transmitting terminal
Domain signal estimated valueBit data Soft Inform ation
Again to this Soft Inform ationHard decision is carried out, transmitting terminal time-domain signal estimated value is obtainedBit dataIts
Adjudicate formula are as follows:
Step 6b, to bit dataRe-encoding and re-modulation are carried out, ideal reference signal R is obtained.
Step 7, using Error Vector Magnitude calculation formula, what the measurement signal Z and step 6 obtained according to step 5 obtained
Ideal reference signal R calculates receiving end EVM:
Receiving end EVM is defined as the square root and reference signal average power of receiving end error vector average power signal
Square root between ratio, that is, root-mean-square value (the RMS:Root Mean of error vector signal and reference signal
Square the ratio between), as shown in Figure 3.
Step 7a calculates the every subframe in receiving end in uplink shared data channel using Error Vector Magnitude calculation formula
EVMi:
Step 7b calculates all subframe receiving end EVM under a frameiAverage value, obtain receiving end EVM, realize formula are as follows:
Wherein, i is sub-frame number, and L is subframe sum.
Step 8, modulation coding scheme MCS is selected:
Step 8a carries out off-line simulation to adaptive uplink system model, obtains between receiving end EVM and MCS
Mapping table, obtained by carrying out off-line simulation to the adaptive uplink system model using SISO awgn channel,
Specific implementation flow as shown in figure 4, the MCS that uses of the present embodiment for 1~15:
Step 8a1, enables MCS=1.
Step 8a2 carries out offline circulation emulation to the adaptive uplink system model using SISO awgn channel,
And from finding out the value range that can make BLER equally distributed SNR between 0 to 1 in simulation result.
Under step 8a3, each SNR in SNR value range, to adaptive using the uplink of SISO awgn channel
It answers system model to carry out offline circulation emulation, is recycled corresponding receiving end EVM and BLER every time, and to these receiving ends
EVM and BLER are attached, and obtain the simulation curve between receiving end EVM and BLER, as shown in Figure 5.
Step 8a4 on the simulation curve between receiving end EVM and BLER, finds out the corresponding receiving end BLER=0.1
EVM is simultaneously stored, while storing current MCS.
Step 8a5, enables MCS=MCS+1, repeats step 8a2~8a4, until MCS=15, and from the multiple of storage
The mapping table between receiving end EVM and corresponding MCS is extracted in receiving end EVM and MCS, as shown in table 1:
Table 1
Step 8b carries out Multi simulation running to adaptive uplink system model, according to instantaneous in each simulation cycles
Receiving end EVM value chooses its corresponding MCS from table 1, and feeds back to transmitting terminal, for the optimized parameter transmitted next time
It is configured.
Effect of the invention can pass through following emulation further instruction:
1. simulated conditions
Simulation software: Matlab is used；
Simulating scenes: the parameter setting for transmitting aspect is based on 3GPP LTE standard, 1.4MHz system bandwidth, transmitting antenna number
Be 1, reception world number be 2, VehA channel, it is assumed that there is no Time and Frequency Synchronization, I/Q is uneven the problems such as.Specific simulation parameter
It is as shown in table 2:
Table 2: simulation parameter table
| Parameter | Numerical value |
| Cell | 7 cells |
| Radius of society | 500m |
| Carrier frequency/system bandwidth | 2GHz/1.4MHz |
| Channel model | VehA |
| SNR(dB) | 5:5:40 |
| Target BLER | Less than or equal to 10% |
| Antenna configuration | 1 hair 2 receives (1 × 2) |
| BS receiver type | ZF receiver |
| Channel estimation | MMSE |
2. emulation content and interpretation of result
Using the above simulated conditions, the present invention is emulated with existing channel quality measurement algorithm, as EESM algorithm,
MIESM algorithm, AESM algorithm and Harm-mean algorithm obtain the present invention and existing channel quality measurement algorithms at different SNR
BLER and throughput performance compare figure, as shown in Fig. 6.
Abscissa in Fig. 6 (a) and Fig. 6 (b) indicates SNR, unit dB in current scene.The ordinate table of Fig. 6 (a)
Show that system BLER, the ordinate of Fig. 6 (b) indicate throughput of system, unit bit/s., in Fig. 6, the curve that is indicated with small vertical bar
For the BLER and handling capacity simulation result curve of EESM algorithm；Curve with square mark is the BLER of MIESM algorithm and gulps down
The amount of spitting simulation result curve；Curve with five-pointed star mark is the BLER and handling capacity simulation result curve of AESM algorithm；With water chestnut
The curve of shape mark is the BLER and handling capacity simulation result curve of Hram-mean algorithm；Curve with circle mark is application
When of the invention, the BLER and handling capacity simulation result curve of system.
From Fig. 6 (a) as can be seen that for all channel quality measurement algorithms, with the increase of SNR, system BLER
It is all promoted with throughput performance.EESM, MIESM, AESM and Harm-mean algorithm are arrived when SNR is more than 25dB
The BLER of target has been reached, and for algorithm proposed by the present invention, when SNR is more than 13dB, so that it may reach target BLER, thus
As can be seen that the present invention has more preferably BLER performance, the limitation of system BLER can be better met.It can be with from Fig. 6 (b)
Find out, with the increase of SNR, compared with existing channel quality measurement algorithm, measuring accuracy of the invention is higher, handling capacity
Performance is obviously improved.Therefore, the existing channels mass measurement such as the present invention and EESM, MIESM, AESM and Harm-mean is calculated
Method is compared, under conditions of meeting system BLER requirement, the throughput performance of energy more effectively lifting system.
Claims (9)
1. a kind of uplink channel quality measurement method based on receiving end error vector magnitude EVM, includes the following steps:
(1) uplink Adaptable System model is constructed, and establishes the number of frequency-region signal between the model transmitting terminal and receiving end
Relationship realizes step are as follows:
(1a) uses multiple access technology, construct ground based cellular communication system or satellite communication system or Massive-MIMO system or
The adaptive uplink system model of point-to-point link Transmission system: including Turbo coding, modulation, layer mapping, DFT transform
With the transmitting terminal of symbol generation module, connect including what FFT transform, channel estimation, frequency domain equalization, IDFT transformation, demodulation decoded
Receiving end, mimo channel include channel quality measurement and Adaptive Modulation and Coding based on receiving end error vector magnitude EVM
Adaptive feedback module；
(1b) establishes the mathematical relationship y of frequency-region signal between adaptive uplink system model transmitting terminal and receiving endi f, obtain
The frequency-region signal y of receiving endf:
Wherein Y is receiving end frequency-region signal, and H is system domain channel response, FMThe normalization DFT transform for being M for size,K, l=1,2 ..., M, NTFor transmitting antenna number,It is N for dimensionTUnit vector, x
For transmitting terminal modulated signal, V is that mean value is 0, and variance isWhite Gaussian noise；
(2) in receiving end, according to the pilot frequency configuration form in 3GPP standard, from adaptive uplink system model receiving end frequency
Pilot signal Y is extracted in the signal Y of domainp:
Yp=HpSp+Vp
Wherein, Sp、HpAnd VpRespectively refer to transmitting terminal pilot signal, pilot channel response and white Gaussian noise；
(3) in receiving end, system domain channel response H is estimated:
(3a) uses channel estimation method, according to pilot signal YpTo pilot channel response HpEstimated, obtains pilot channel and ring
Answer estimated value
(3b) uses time domain interpolation algorithm, according to pilot channel response estimated valueComputing system domain channel response estimated value
(4) estimate the measurement signal Z based on receiving end error vector magnitude EVM channel quality measurement algorithm:
(4a) uses frequency domain equalization algorithm, according to the frequency-region signal y of the receiving end in step (1b)fIt is with what is obtained in step (3)
System domain channel response estimated valueCalculate the estimated value of transmitting terminal frequency-region signal(4b) estimates transmitting terminal frequency-region signal
EvaluationIFFT transformation is carried out, transmitting terminal time-domain signal estimated value is obtainedIt is based on receiving end error vector magnitude EVM channel
The measurement signal Z of quality measurement algorithms；
(5) in receiving end, to transmitting terminal time-domain signal estimated valueProgress Turbo code decoding, the bit data after being decoded,
And re-encoding and re-modulation are carried out to the bit data, obtain ideal reference signal R；
(6) Error Vector Magnitude calculation formula is used, the ideal that the measurement signal Z and step (5) obtained according to step (4) obtains
Reference signal R calculates receiving end EVM；
(7) in receiving end, modulation coding scheme MCS is selected:
(7a) carries out off-line simulation to adaptive uplink system model, obtains the mapping table between receiving end EVM and MCS；
(7b) carries out Multi simulation running to adaptive uplink system model, according to the instantaneous receiving end in each simulation cycles
EVM value chooses its corresponding MCS in the mapping table between receiving end EVM and MCS, and feeds back to transmitting terminal, for next
The optimized parameter of secondary transmission is configured.
2. the uplink channel quality measurement method according to claim 1 based on receiving end error vector magnitude EVM,
It is characterized in that, frequency-region signal between adaptive uplink system model transmitting terminal and receiving end described in step (1)
Mathematical relationshipIts expression formula are as follows:
WhereinIt is that the IDFT that size is M is converted, hr,n=diag { [h1]r,n,[h2]r,n,...,[hM]r,n, [hm]r,nIt refers to
N-th of transmitting antenna, the domain channel response of m-th of subcarrier, v under r-th of receiving antennarIt is that mean value is 0, variance under frequency domain
ForNoise vector, xn=[xn,1,xn,2,...,xn,M]TIt is transmitting terminal by the modulated time domain of M-QAM
Signal, NTFor transmitting antenna number, HMFor hr,nFourier transformation form, vnFor interchannel noise.
3. the uplink channel quality measurement side according to claim 1 based on receiving end error vector magnitude EVM
Method, which is characterized in that channel estimation method described in step (3a) is calculated using LS channel estimation method or MMSE channel estimation
Method: according to LS channel estimation method, then its channel response estimation coefficient isBelieve according to MMSE
Channel estimation algorithm, then its channel response estimation coefficient beWherein,Be pilot channel response and
The covariance matrix of signal is received,It is to receive signal auto-covariance matrix.
4. the uplink channel quality measurement method according to claim 1 based on receiving end error vector magnitude EVM,
It is characterized in that, system domain channel response estimated value described in step (3b)Its obtaining step are as follows:
(3b1) utilizes FFT/IFFT method, the pilot channel response estimated value obtained to step (3a)IFFT transformation is carried out, is obtained
Time domain pilot channel response estimated value
Wherein,It is N for sizepIDFT transformation, NpFor the number of pilot channel response,N=0,1 ..., Np- 1, T are matrix transposition；
(3b2) clock synchronization field pilot channel response estimation valueInterpolation is carried out, system time domain channel response estimated value is obtained
Wherein N is the number of system channel response；
(3b3) is to system time domain channel response estimated valueFFT operation is carried out, system domain channel response estimated value is obtained
Wherein FNThe DFT transform for being N for size,K=0,1 ..., N-1.
5. the uplink channel quality measurement method according to claim 1 based on receiving end error vector magnitude EVM,
It is characterized in that, frequency domain equalization algorithm described in step (4a), using ZF frequency domain equalization algorithm or MMSE frequency domain equalization algorithm:
According to ZF frequency domain equalization algorithm, then its equalizing coefficient isThe estimated value of transmitting terminal frequency-region signal
ForAccording to MMSE equalization algorithm, then its equalizing coefficient isThe estimated value of transmitting terminal frequency-region signal is
6. the uplink channel quality measurement method according to claim 1 based on receiving end error vector magnitude EVM,
It is characterized in that, the measurement described in step (4b) based on receiving end error vector magnitude EVM channel quality measurement algorithm is believed
Number Z realizes formula are as follows:
WhereinFor M point Fourier transformation inverse matrix.
7. the uplink channel quality measurement method according to claim 1 based on receiving end error vector magnitude EVM,
It is characterized in that, ideal reference signal R described in step (5), obtaining step are as follows:
(5a) is first to transmitting terminal time-domain signal estimated valueTurbo code logarithm MAP decoding is carried out, transmitting terminal time-domain signal is obtained
Estimated valueBit data Soft Inform ation
Again to this Soft Inform ationHard decision is carried out, transmitting terminal time-domain signal estimated value is obtainedBit dataIt adjudicates public
Formula are as follows:
(5b) is to bit dataRe-encoding and re-modulation are carried out, ideal reference signal R is obtained.
8. the uplink channel quality measurement method according to claim 1 based on receiving end error vector magnitude EVM,
It is characterized in that, calculating receiving end EVM described in step (6), realizes step are as follows:
(6a) uses Error Vector Magnitude calculation formula, calculates the every subframe EVM in receiving end in uplink shared data channeli:
(6b) calculates all subframe receiving end EVM under a frameiAverage value, obtain receiving end EVM, realize formula are as follows:
Wherein, i is sub-frame number, and L is subframe sum.
9. the uplink channel quality measurement method according to claim 1 based on receiving end error vector magnitude EVM,
It is characterized in that, the mapping table between receiving end EVM and MCS described in step (7a), obtaining step are as follows:
(7a1) initialization, enables MCS=1；
(7a2) carries out offline circulation emulation to the adaptive uplink system model using SISO awgn channel, and from emulation
As a result the value range that can make BLER equally distributed SNR between 0 to 1 is found out in；
Under each SNR of (7a3) in SNR value range, to the adaptive uplink system mould using SISO awgn channel
Type carries out offline circulation emulation, is recycled corresponding receiving end EVM and BLER every time, and to these receiving ends EVM and BLER
It is attached, obtains the simulation curve between receiving end EVM and BLER；
On the simulation curve of (7a4) between receiving end EVM and BLER, finds out the corresponding receiving end EVM of BLER=0.1 and deposit
Storage, while storing current MCS；
(7a5) enables MCS=MCS+1, repeats step (7a2)~(7a4), until MCS=28, and from multiple receptions of storage
The mapping table between receiving end EVM and corresponding MCS is extracted in the EVM and MCS of end.
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