CN1339924A - Self adaptive lattice weighting channel evaluating method - Google Patents
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Abstract
The adaptive channel weighting estimation method is used for the estimation of the gain in radio transmission channel. It includes: forward equalization for the present time interval to obtain forward adaptive channel estimation value, reverse qualization of the same time interval to obtain reverse adaptive channel estimation value; lattice weighting treatment of the forward adaptive channel estimation value and the reverse adaptive channel estimation value to obtain ultimate channel gain estimation value. The method estimates pilot frequency channel through judging feedback process, tracks data business channel by using coherent detection and adaptive algorithm, and is one scheme combining judging feedback, adaptive linear predication and lattice weighting.
Description
The present invention relates to a kind of radio communication reception technique, relate to the channel estimation technique in a kind of public land mobile communication system receiver or rather.
In the receiver of third generation digit wireless communication system, the pilot frequency information of pilot channel and the data message of data channel are two available informations of channel estimating, thereby form three kinds of channel estimating modes based on the time-multiplexed pilot channel: utilize pilot frequency information to estimate channel purely; Utilize data message to estimate channel purely; Unite and utilize pilot frequency information and data message to estimate channel.
For first kind of mode of utilizing pilot frequency information to estimate channel purely, the method that has proposed at present comprises: MMSE (least mean-square error) algorithm, LMS (lowest mean square) algorithm, RLS (recurrence least square) algorithm, the Wiener filter method, the Kalman filter method, the first-order linear filter method, the first order nonlinear filter method, the Gauss interpolation method, Sigmoid interpolation method (a kind of nonlinear filtering method) and weighting multi-slot filter method (WMSA), these methods all are only to utilize pilot frequency information to carry out channel estimating, the fast advantage of computational speed is arranged, but the channel that serious decay is arranged is difficult to make correct estimation.
For second kind of mode of utilizing data message to estimate channel purely,, belong to blind estimation owing to do not utilize pilot frequency information, see to also have many defectives from present research situation, comprise that operand is big, postpone big, performance can not get assurance etc., and the current stage can't be applied fully at least.
Utilizing pilot frequency information and data message to unite the mode of estimating channel for the third, also is the main direction of studying at present, and can be divided into two big class methods again: a class is that direct estimation goes out data channel; Another kind of is also to recover a yard source (symbol) sequence when estimating channel, promptly realizes balanced in channel estimating.
Wherein, the method that first kind direct estimation goes out data channel includes: half-blind channel estimating method, MUSIC.ESPRIT subspace tracking channel method, PASTd algorithm, Kalman filter method and simple neural net method etc., these methods are still waiting to do further checking on arithmetic speed and performance, also do not reach degree of being practical.
Second class realizes balanced method in channel estimating, comprise the adaptive channel tracing that adopts decision-feedback and channel tracking, the outstanding shortcoming of this method is: owing to adopt the arest neighbors criterion to adjudicate, in case court verdict is incorrect, error will appear in ensuing channel estimating, when the next symbol of judgement, cause error accumulation easily like this.
In sum, in the channel estimation technique field, pure use pilot frequency information (symbol) estimates to lack instantaneity to the parameter of channel (Traffic Channel), and channel space-variantization at any time especially just can't accurately be estimated channel when the travelling carriage high-speed motion; Pure blind estimation can't be used.Generally speaking, traditional linear interpolation method, low order Gauss interpolation method, Wiener filter method (document that sees reference [1] J.K.Cavers. " An analysis of pilot symbol assisted modulation for Rayleigh fading channels. ＂ IEEE Trans.Veh.Technol.; vol.VT-42; pp.689-693, Nov.1991.; [2] F.Ling, " Coherent detection with reference-symbol based estimation for direct sequenceCDMA uplink communications; ＂ Proc.VTC ' 93 pp.400-403; New Jersey; USA; May1993.) and weighting multi-slot equilibrium (WMSA) interpolation method (document that sees reference [3] H.Andoh; M.Sawahashi, and F.Adachi, " Channel estimaion filter using time-multiplexed pilotchannel for coherent rake combining in DS-CDMA mobile radio; ＂ IEICE Trans.Commun.; vol.E81-B, NO.7 July 1998.; [4] Sadayuki ABETA, MamoruSAWAHASHI, and Fumiyuki ADACHI " Performance Comparison Between Time-Multiplesed Pilot Channel and Parallel Pilot Channel for Cohemt Rake Combiningin DS-CDMA Mobile Radio " IEICE TRANS.COMMUN., VOL.E81-B, NO.7, JULY1998.) etc., their common basic characteristics are to adopt simple linear processing methods, their common shortcomings are that the translational speed of travelling carriage in the requirement communication system can not be too fast, generally should be less than 100 kilometers/hour, because channel is space-variantization at any time, when the translational speed of travelling carriage too fast, as greater than 200 kilometers/hour the time, deep attenuation will appear in channel, nonlinear change perhaps occurs, just can't accurately estimate channel value, so said method is to have big defective.
As, Wiener filtering need be known the statistical property of fading channel, in fact is difficult to also can't obtain, and, fast power control is arranged in the cellular radio Communication system link, channel statistic property can't keep, so Wiener filtering can't practical application.And with regard to other three kinds of interpolation techniques, when the number of interpolation more for a long time, error is bigger; When signal to noise ratio is low, when the travelling carriage high-speed mobile causes bigger Doppler frequency shift, just can't estimate accurately that the error rate is higher.
The objective of the invention is to design a kind of self adaptive lattice weighting channel evaluating method, be to be under the jurisdiction of the third to utilize pilot frequency information and data message to unite the method for estimating channel, follow the tracks of and adaptive weighted technology by adopting, follow the tracks of the also variation of adaptive channel, reduce error as far as possible, so that estimate channel parameter more accurately, the business datum that receiver is demodulated is more accurate.
The object of the present invention is achieved like this: a kind of self adaptive lattice weighting channel evaluating method is that channel gain is estimated, it is characterized in that comprising:
A. current time slots is done the forward direction equilibrium, obtain the adaptive channel estimated value of forward;
B. same current time slots is done oppositely equilibrium, obtain reverse adaptive channel estimated value;
C. the adaptive channel estimated value and the reverse adaptive channel estimated value of forward are carried out the lattice weighting processing, obtain final channel gain estimated value.
Describedly current time slots is done the forward direction equilibrium be to use decision-feedback and self adaptation lowest mean square (LMS) algorithm, first forward is estimated the Traffic Channel value, obtains the adaptive channel estimated value of the forward of whole L bar propagation path current time slots.
Describedly current time slots is done the forward direction equilibrium further may further comprise the steps: A. is taken as the initial service channel yield value with the average of current time slots frequency pilot sign; B. predict the next channel yield value of initial service channel yield value, be the initial service channel predictive coefficient vector on duty that gains; C. with the channel yield value of prediction business datum is made relevant (Rake) and merge, obtain the data symbol of Traffic Channel according to a preliminary estimate; D. provide the Traffic Channel estimation of this propagation path again with detected data symbol; E. proofread and correct the predictive coefficient vector; F. channel estimation value is made low-pass filtering; G. execution in step B all estimates to finish until the Traffic Channel value of current time slots to step F continuously.
Described repeated execution of steps B total ND time to step F is the symbol numbers of Traffic Channel.
The data symbol of described estimation Traffic Channel comprises that elder generation carries out the high specific merging to the same data symbol of L bar propagation path, obtains the data symbol soft estimate of current received signal, re-uses arest neighbors decision rule and obtains detected symbol.
The detected symbol of described usefulness provides the channel estimating of each propagation path again, is that court verdict is taked the threshold values technology; Then revises during when court verdict, be modified to the ratio that current footpath received signal and relevant (Rake) merge the signal value after predicting less than the threshold values set; When court verdict is not then revised during more than or equal to the threshold values set.
Described correction predictive coefficient vector adopts self adaptation lowest mean square (LMS) algorithm to carry out.
Describedly be to use low pass filter that the estimated value of channel gain is carried out smoothing processing as low-pass filtering to channel estimation value.
Described use low pass filter carries out smoothing processing to the estimated value of channel gain, is the plurality of continuous value about estimated value is asked the estimated value of average back as current channel gain.
Described oppositely balanced to same current time slots work, be with the business datum receiving symbol of current time slots inverted arrangements in chronological order, and the pilot data symbol of next time slot of current time slots is placed on the initial estimate of the business datum symbol front of current time slots as current channel gain, and obtain reverse adaptive channel estimated value by the described method that current time slots is done the forward direction equilibrium.
Self adaptive lattice weighting channel evaluating method of the present invention is a kind of channel estimation methods (can be called for short the ALWA algorithm) of novelty of making at the frequency selective attenuation channel.The basic thought of this method is: to the time-multiplexed pilot sequence, utilize the decision-feedback method to estimate pilot channel; To the data Traffic Channel, utilize coherent detection and self adaptation lowest mean square (LMS) algorithm to follow the tracks of pilot channel.So method of the present invention is a kind of method that merges decision-feedback method, adaptive linear prediction method and lattice weighting method.
Self adaptive lattice weighting channel evaluating method of the present invention, it is a kind of self adaptive lattice weighting method of estimation at frequency-selective channel, with the essential distinction of traditional weighting multi-slot method of estimation (WMSA) be also to have related to the adaptive channel on the frequency-selective channel to estimate, and what adopt is that bidirectional self-adaptive is estimated, and the result is made weighted.Test shows, under mobile communication environment very condition of severe, adopts method of the present invention still can guarantee the lower error rate, and by emulation, weighting multi-slot method of estimation (WMSA) comparison with traditional has tangible technique effect.
Further specify method of the present invention below in conjunction with embodiment and accompanying drawing.
Fig. 1 is the time-division pilot channel structural representation of received signal in the wireless communication system.
Fig. 2 is the Rake receiver structure schematic diagram that comprises channel estimation module in the wireless communication system.
Fig. 3 is the execution schematic diagram of channel gain method of estimation of the present invention.
Fig. 4 be travelling carriage under various translational speeds, bit error code (error rate BER) performance of the inventive method and traditional weighting multi-slot method is schematic diagram relatively.
Fig. 5 is under various signal to noise ratio environment, and bit error code (error rate BER) performance of the inventive method and traditional weighting multi-slot method is schematic diagram relatively.
Referring to Fig. 1, illustrate a key technology in the land mobile communication system Rake receiver among the figure, be the time-division pilot channel structure of received signal.
Frame (Frame) structure is by communication protocol definition, the time time slot (Slot) long and every frame that comprises every frame is counted, each time slot includes frequency pilot sign (pilot Symbols) information and data symbol (DataSymbols), can represent with Np frequency pilot sign and Nd data symbol respectively, if the duration of each symbol is represented with T, the long T of time slot then
SlotCan be expressed as:
T
Slot=(Np+Nd) T ... formula (1)
Referring to Fig. 2, the Rake receiver receives is multipath signal (through multidiameter fading channel) from L bar propagation path, and behind receiving filter, by the received signal that multidiameter delay module 1 is aimed at current propagation path, this received signal r (t) can be expressed as:
L is the propagation path number in the formula, and Q (t) comprises that multipath disturbs the background noise of (MAI), and the one-sided power spectrum of noise is N
0, ζ
1(t) and τ
1Be respectively the complex value channel gain and the time delay in the 1st footpath, s (t) is the baseband signal that transmits.
Because different propagation paths should be delayed time to L footpath signal respectively by L delayer to different time-delays should be arranged.Received signal after this propagation path is aimed at is by despreader 2 despreading of being correlated with,
(l, m n) can be expressed as: (l, m n) are noise to the w in the formula to received signal r on the 1st footpath, n time slot, a m character position.
Because the time-division pilot channel has comprised frequency pilot sign and business datum symbol, need to separate by 3 pairs of signals of signal separation module, isolated pilot signal enters channel estimation module 4, and isolated service signal enters coherent demodulation module 5 and carries out phase compensation.
In channel estimation module 4, to the pilot signal of input with through the pilot signal of demodulation feedback, adopt two-way lattice weighting adaptive approach of the present invention to obtain channel estimation value, and offer coherent demodulation module 5 and carry out phase compensation.
In conjunction with referring to Fig. 3, describe method of the present invention in detail by three big steps, i.e. the channel gain estimation procedure of channel estimation module 4.
First step: at first use decision-feedback and self adaptation lowest mean square (LMS) algorithm, preceding (just) shown in " forward direction equilibrium " among Fig. 3, comprising to the Traffic Channel value is estimated:
The first step is taken as the mean value that current time slots (i) frequency pilot sign " is trained (i) " with the initial service channel gain;
Second step, predict next channel yield value, for the initial service channel yield value is multiplied by the predictive coefficient vector, be formulated as:
In the formula,
Be the predictive coefficient vector,
Be initial service channel yield value (average of current time slots frequency pilot sign);
The 3rd step, the data symbol of estimation Traffic Channel, the same data symbol to the L propagation path carries out high specific merging (MRC) earlier, obtains the data symbol soft estimate of current reception, is expressed as:
Y in the formula
kBe k received signal of current path, and then use arest neighbors decision rule, detect the symbol of k received signal, be expressed as:
In the formula, the value set when D is the emission of modulation complex value low-pass signal; In the 4th step, with detected symbol xk, the Traffic Channel that provides each propagation path is again estimated yk/ xk, and the result who adjudicates is taked the threshold values technology: if
, then
If
, then
In the 5th step, adopt conventional ADAPTIVE LMS ALGORITHM to proofread and correct the predictive coefficient vector
, be expressed as:
The 6th step, estimated value to channel gain is carried out low-pass filtering, because the correlation before and after the channel, and the necessity that suppresses noise, be that the low pass filter of 2K+1 (K is an integer, and 2K+1 is level and smooth symbol numbers) carries out signal smoothing also, promptly the plurality of continuous value about the channel gain estimated value asked average with rank, as current channel gain estimated value, smoothly the estimation of the channel gain after can be expressed as:
In the formula, h
iBe 2K+1 tap coefficient of low pass filter;
The 7th step, returned for second step and carry out, estimate to finish until the channel value (all symbols) of this current time slot services channel, obtain the adaptive channel estimated value of the forward of this this time slot of footpath, be designated as:
。
Second largest step: Traffic Channel receiving symbol that then will this current time slot (i) is inverted arrangements in chronological order, and the pilot channel symbols of next time slot (i+1) that will this current time slot " training (i+1) " is placed on business datum symbol front after inverted arrangements as the pilot tone (being current initial channel gain estimated value) of current time slots (i), repeat each step in the first step, shown in " oppositely balanced " among Fig. 3, obtain the oppositely balanced channel yield value that obtains of this current time slot (i), be designated as:
。
The third-largest step: last, the channel estimation gains value that the channel estimation gains value that the forward self adaptation is obtained and reverse self adaptation obtain lattice weighting method is routinely handled, and obtains final channel gain estimated value, is expressed as:
Continuation is referring to Fig. 2, the signal of channel estimation module 4 outputs is done phase compensation to data-signal in coherent demodulation module 5, offer RAKE multipath merging module 6 again and do multipath merging (being that the module 1 to 5 of L component safety pin to the L footpath arranged in the RAKE receiver) with other footpath signal, the signal indication after the merging is:
Multipath after 7 pairs of energy of judging module merge (L footpath) signal is adjudicated, court verdict offer reciprocal cross knit with channel decoding module 8 (by aforementioned formula 6, finish by deinterleaver, soft-decision Viterbi decoder), carry out that reciprocal cross is knitted and channel decoding, recover original transmitted signal.
What the present invention relates to is self adaptive lattice weighting method on the frequency-selective channel, with the essential distinction of conventional method is to have realized that the adaptive channel on the frequency-selective channel estimates, and what adopt is that bidirectional self-adaptive is estimated, and the result of correspondence made weighted, experiment shows that the effect of the inventive method is tangible.
Adopt the outstanding feature of the inventive method to be: under mobile communication environment very condition of severe, still can keep the lower error rate (BER).
Referring to Fig. 4, transverse axis represent travelling carriage translational speed (kilometer/hour), the longitudinal axis is represented the error rate (BER).At identical signal to noise ratio (SNR=6dB behind the spread spectrum, if spreading factor is 256, be equivalent to spread to-18dB) condition under, (more than 100 kilometers/hour) adopt the ber curve (dotting among the figure) that traditional weighting multi-slot equalization methods WMSA records when the travelling carriage high-speed mobile, compare with the ber curve (representing with solid line among the figure) that adopts the inventive method ALWA to record, the former error rate improves sharply with speed and rises, and the latter's the error rate then changes slower.
Referring to Fig. 5, transverse axis is represented signal to noise ratio (snr), and the longitudinal axis is represented the error rate (BER).Travelling carriage is under identical translational speed (300 kilometers/hour), when satisfying various signal to noise ratios (SNR is generally 1-8dB in the mobile environment), the ber curve (dotting among the figure) that adopts traditional weighting multi-slot equalization methods WMSA to record, compare with the ber curve (representing with solid line among the figure) that adopts the inventive method ALWA to record, the former error rate is much higher than the latter's the error rate.
Therefore, method of the present invention more is applicable in the more abominable mobile communication system of communication environment, under vehicle-mounted travelling carriage environment.If in 3-G (Generation Three mobile communication system), use, can help improving the performance of system's received signal, thereby improve communication quality.
Claims (10)
1. a self adaptive lattice weighting channel evaluating method is that channel gain is estimated, it is characterized in that comprising:
A. current time slots is done the forward direction equilibrium, obtain the adaptive channel estimated value of forward;
B. same current time slots is done oppositely equilibrium, obtain reverse adaptive channel estimated value;
C. the adaptive channel estimated value and the reverse adaptive channel estimated value of forward are carried out the lattice weighting processing, obtain final channel gain estimated value.
2. a kind of self adaptive lattice weighting channel evaluating method according to claim 1, it is characterized in that: describedly current time slots is done the forward direction equilibrium be to use decision-feedback and self adaptation lowest mean square (LMS) algorithm, elder generation's forward is estimated the Traffic Channel value, obtains the adaptive channel estimated value of the forward of whole L bar propagation path current time slots.
3. a kind of self adaptive lattice weighting channel evaluating method according to claim 1 and 2 is characterized in that: describedly current time slots is done the forward direction equilibrium further may further comprise the steps: A. is taken as the initial service channel yield value with the average of current time slots frequency pilot sign; B. predict the next channel yield value of initial service channel yield value, be the initial service channel predictive coefficient vector on duty that gains; C. with the channel yield value of prediction business datum is made relevant (Rake) and merge, obtain the data symbol of Traffic Channel according to a preliminary estimate; D. provide the Traffic Channel estimation of this propagation path again with detected data symbol; E. proofread and correct the predictive coefficient vector; F. channel estimation value is made low-pass filtering; G. execution in step B all estimates to finish until the Traffic Channel value of current time slots to step F continuously.
4. a kind of self adaptive lattice weighting channel evaluating method according to claim 3 is characterized in that: described repeated execution of steps B total ND time to step F is the symbol numbers of Traffic Channel.
5. a kind of self adaptive lattice weighting channel evaluating method according to claim 3 is characterized in that; The data symbol of described estimation Traffic Channel comprises that elder generation carries out the high specific merging to the same data symbol of L bar propagation path, obtains the data symbol soft estimate of current received signal, re-uses arest neighbors decision rule and obtains detected symbol.
6. a kind of self adaptive lattice weighting channel evaluating method according to claim 3 is characterized in that: the detected symbol of described usefulness provides the channel estimating of each propagation path again, is that court verdict is taked the threshold values technology; Then revises during when court verdict, be modified to the ratio that current footpath received signal and relevant (Rake) merge the signal value after predicting less than the threshold values set; When court verdict is not then revised during more than or equal to the threshold values set.
7. a kind of self adaptive lattice weighting channel evaluating method according to claim 3 is characterized in that: described correction predictive coefficient vector adopts self adaptation lowest mean square (LMS) algorithm to carry out.
8. a kind of self adaptive lattice weighting channel evaluating method according to claim 3 is characterized in that: describedly be to use low pass filter that the estimated value of channel gain is carried out smoothing processing to channel estimation value as low-pass filtering.
9. a kind of self adaptive lattice weighting channel evaluating method according to claim 8, it is characterized in that: described use low pass filter carries out smoothing processing to the estimated value of channel gain, is the plurality of continuous value about estimated value is asked the estimated value of average back as current channel gain.
10. a kind of self adaptive lattice weighting channel evaluating method according to claim 1, it is characterized in that: described oppositely balanced same current time slots work, be with the business datum receiving symbol of current time slots inverted arrangements in chronological order, and the pilot data symbol of next time slot of current time slots is placed on the initial estimate of the business datum symbol front of current time slots as current channel gain, and obtain reverse adaptive channel estimated value by the described method that current time slots is done the forward direction equilibrium.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1751485B (en) * | 2003-02-18 | 2010-12-29 | 高通股份有限公司 | Communication receiver with an adaptive equalizer |
| CN101316116B (en) * | 2007-05-31 | 2012-02-29 | 财团法人工业技术研究院 | Adaptive wireless passage estimation device and method |
| CN101729476B (en) * | 2008-10-23 | 2013-01-23 | 晨星软件研发(深圳)有限公司 | Channel estimator and channel estimating method |
| CN101652969B (en) * | 2007-04-10 | 2013-06-19 | 高通股份有限公司 | Adaptive pilot and data symbol estimation |
| CN106027117A (en) * | 2016-05-04 | 2016-10-12 | 大连理工大学 | Time delay and Doppler shift joint estimation method based on generalized Sigmoid conversion cyclic fuzzy function |
| CN109982342A (en) * | 2013-05-24 | 2019-07-05 | 日本电信电话株式会社 | Wireless communication device and wireless communications method |
-
2000
- 2000-08-21 CN CN 00123549 patent/CN1115888C/en not_active Expired - Fee Related
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1751485B (en) * | 2003-02-18 | 2010-12-29 | 高通股份有限公司 | Communication receiver with an adaptive equalizer |
| CN101652969B (en) * | 2007-04-10 | 2013-06-19 | 高通股份有限公司 | Adaptive pilot and data symbol estimation |
| CN101316116B (en) * | 2007-05-31 | 2012-02-29 | 财团法人工业技术研究院 | Adaptive wireless passage estimation device and method |
| CN101729476B (en) * | 2008-10-23 | 2013-01-23 | 晨星软件研发(深圳)有限公司 | Channel estimator and channel estimating method |
| CN109982342A (en) * | 2013-05-24 | 2019-07-05 | 日本电信电话株式会社 | Wireless communication device and wireless communications method |
| CN109982342B (en) * | 2013-05-24 | 2022-03-25 | 日本电信电话株式会社 | Wireless communication device and wireless communication method |
| CN106027117A (en) * | 2016-05-04 | 2016-10-12 | 大连理工大学 | Time delay and Doppler shift joint estimation method based on generalized Sigmoid conversion cyclic fuzzy function |
| CN106027117B (en) * | 2016-05-04 | 2018-04-10 | 大连理工大学 | A kind of time delay and Doppler frequency shift combined estimation method |
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