CN105978666B - Transmitting terminal and processing method of space-time channel optimization MIMO wireless transmission system - Google Patents
Transmitting terminal and processing method of space-time channel optimization MIMO wireless transmission system Download PDFInfo
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Abstract
The present invention relates to communication technology. The invention provides a space-time channel optimization MIMO wireless transmission system transmitting end and a processing method, which aim to remarkably improve the data transmission rate, the system capacity and the frequency spectrum efficiency of an MIMO system, and the technical scheme can be summarized as follows: the space-time channel optimization MIMO wireless transmission system transmitting end comprises a plurality of signal transmitting ends, a plurality of virtual channel vector modules, feedback information receiving ends and space-time optimization modules, wherein each virtual channel vector module corresponds to at least one signal input end, each signal input end corresponds to only one virtual channel vector module, the output end of each virtual channel vector module is only connected with one path of signal transmitting end in a one-to-one correspondence manner, the feedback information receiving ends are connected with the space-time optimization modules, the space-time optimization modules are connected with each virtual channel vector module, and the space-time optimization modules are connected with each signal input end. The invention has the beneficial effects of improving the data transmission rate and being suitable for the MIMO system.
Description
Technical Field
The present invention relates to communication technology, and in particular, to MIMO wireless transmission technology.
Background
The MIMO (multiple input multiple output) technology uses the wireless channels formed by different spatial positions of multiple antennas of the transmitting end and the receiving end to transmit multiple data streams in parallel, can obviously improve the data transmission rate and the system capacity of the wireless communication system, is an important development direction of the modern wireless communication technology, and has a wide application prospect.
Referring to fig. 1 for a system block diagram of an existing MIMO system, a transmitting end thereof has N T Path input baseband data stream x 1 (t)，x 2 (t)，...，
N T Root transmitting antenna (N) T ＝1，2，…),x m (t)∈{±1}(m＝1,2,...,N T ) The method comprises the steps of carrying out a first treatment on the surface of the Each data stream x m (t) is modulated by radio frequency to become a high frequency signal, which is amplified and transmitted by the corresponding antenna ant.m (m=1, 2, …, N) T ) Emitting out; receiving end configuration L R Root receiving antenna (L) R =1, 2, …), the radio frequency signal of each antenna is amplified and demodulated to obtain a baseband signal; the signal detection and processing module is used for detecting L from different antennas R The path baseband signals are optimized, combined, detected, judged and the like, and finally N is obtained T Way output data stream y 1 (t)，y 2 (t)，...，/>
y m (t)∈{±1}(m＝1,2,...,N T )，y m (t) is the transmitting end input data stream x m Estimate of (t)>
I.e. < ->
In general, L R ≥N T 。
Let h be lm Representing the spatial radio channel between the first receiving antenna and the mth transmitting antenna, the signals on the first receiving antenna are:
wherein ,nl And (t) is Gaussian white noise of the first receiving antenna. To detect a certain data stream x i (t) a maximum signal-to-noise ratio combining method can be adopted at the receiving end, and the calculation formula is as follows:
channel h can be estimated at the receiving end lm The signals of the receiving antennas are then combined accordingly to obtain decision variables, namely:
set Q D (-) is a decision function, Q D (-) E {. + -.1 }. Then there are:
here, re () represents a real number taking operation.
Representing a useful signal component;
In the existing MIMO system, the transmitting end adopts multiple antennas to simultaneously transmit multiple paths of signals or data streams in the same frequency band, so that the data transmission rate can be improved, or the system capacity can be increased. An n×n (N transmit antennas and N receive antennas) MIMO system can increase the data transmission rate by at most N times, or increase the system capacity by at most N times. And the more the data transmission rate increases or the more the system capacity increases, the more the number of antennas increases. However, in practical applications, the increase of the number of antennas is often limited by factors such as cost and space dimension, so that the improvement degree of the system performance is limited, that is, the obtained data transmission rate, the system capacity or the performance is very limited compared with the increase of the number of additional antennas and the investment of components and cost, which is not ideal, and is a disadvantage in the prior art. In addition, there is often a correlation between wireless channels, and the correlation of channels may significantly impair performance of the MIMO system, making it difficult to take advantage of its potential advantages, which is another disadvantage of the prior art scheme.
Disclosure of Invention
The invention aims to remarkably improve the data transmission rate, the system capacity and the frequency spectrum efficiency of a MIMO system, optimize a transmission channel and improve the system performance, and provides a space-time channel-optimized MIMO wireless transmission system transmitting end and a processing method.
The invention solves the technical problems, and adopts the technical proposal that the transmitting end of the space-time channel optimization MIMO wireless transmission system comprises a plurality of signal transmitting ends, each signal transmitting end comprises a modulation filtering amplifying module and a transmitting antenna, and is characterized by also comprising a plurality of virtual channel vector modules, feedback information receiving ends and space-time optimization modules, wherein each virtual channel vector module corresponds to at least one signal input end, each signal input end corresponds to only one virtual channel vector module, the output end of each virtual channel vector module is only connected with one signal transmitting end in a one-to-one correspondence manner, the feedback information receiving end is connected with the space-time optimization module, the space-time optimization module is connected with each virtual channel vector module, and the space-time optimization module is connected with each signal input end;
the virtual channel vector module is used for carrying out complex weighting operation on the baseband signals input by each signal input end connected with the virtual channel vector module according to the set complex weighting value, combining all the complex weighted baseband signals and transmitting the combined baseband signals to the corresponding signal transmitting end;
The feedback information receiving end is used for receiving feedback information sent by the system receiving end and transmitting the feedback information to the space-time optimization module;
and the space-time optimization module is used for calculating each complex weight value in each virtual channel vector module by adopting a space-time optimization algorithm according to the received feedback information, and setting the complex weight values.
Specifically, the virtual channel vector module includes complex weighting modules corresponding to the number of the signal input ends and an adder, the input end of each complex weighting module is connected with one signal input end in a one-to-one correspondence manner, the output end of each complex weighting module is connected with one input end of the adder in a one-to-one correspondence manner, the output end of each adder is used as the output end of the virtual channel vector module to be connected with one signal transmitting end in a one-to-one correspondence manner, and the space-time optimization module is connected with each complex weighting module.
Further, the baseband signals input by the signal input ends are different; or some of the signal inputs input baseband signals are the same, and others of the signal inputs input baseband signals are different.
Specifically, the number of signal input ends corresponding to each virtual channel vector module may be the same or different.
Still further, the feedback information includes channel identification and system status information.
Specifically, the channel identification and system state information includes a signal-to-noise ratio, an error rate, an error value and a channel estimation value.
The processing method of the space-time channel optimization MIMO wireless transmission system transmitting end is applied to the space-time channel optimization MIMO wireless transmission system transmitting end and is characterized by comprising the following steps:
A. the signal input end receives the input baseband signal and transmits the baseband signal to the corresponding virtual channel vector module;
B. each virtual channel vector module carries out complex weighting operation on the baseband signals input by each signal input end connected with the virtual channel vector module according to the set complex weighting value, and all the complex weighted baseband signals are combined and then transmitted to the corresponding signal transmitting end for transmission;
C. and B, the feedback information receiving end receives feedback information sent by the system receiving end in real time and transmits the feedback information to the space-time optimizing module, and the space-time optimizing module calculates each complex weight value in each virtual channel vector module by adopting a space-time optimizing algorithm according to the received feedback information and sets the complex weight value, and the step B is returned to.
Specifically, in step B, the signal output by the mth virtual channel vector module is
Wherein the vector w m Representing an mth virtual channel vector comprising N m Virtual channels w mn Expressed as:
w mn representing each baseband input signal x mn The virtual channel corresponding to (t) is specifically: />
x mn (t) is a complex signal, N T For the number of transmit antennas, also for the number of input signal vectors, N m Refers to the number of signal input ends corresponding to the mth virtual channel vector module, n=1, 2, … …, N m ，x mn (t) the baseband input signal input from the nth signal input end in the mth virtual channel vector module, and the vector x m (t) refers to the input signal vector of the mth virtual channel vector module, expressed as: />
In step C, the method for calculating each complex weight value in each virtual channel vector module by the space-time optimization module according to the received feedback information by using a space-time optimization algorithm includes:
the space-time optimization module calculates each complex weight value in each virtual channel vector module by adopting a space-time optimization algorithm according to the received feedback information, and the calculation formula is as follows:
wherein ,wopt I.e. the complex weight vector to be obtainedThe optimal value of w, and the complex weight vector w, also called the system virtual channel vector, is expressed as: 
Here, vector w m Representing an mth virtual channel vector comprising N m Virtual channels w mn Expressed as: />
w mn Representing each baseband input signal x mn The virtual channel corresponding to (t) is specifically: />
N T For the number of transmit antennas, also for the number of input signal vectors, N m Refers to the number of signal input ends corresponding to the mth virtual channel vector module, n=1, 2, … …, N m ，x mn (t) means a baseband input signal input from an n-th signal input terminal in the m-th virtual channel vector module;
R is one
The signal transmission matrix refers to:
wherein ,Rij ＝E[x i (t)x j (t) H ]Is N i ×N j Input correlation matrix, i=1, 2, …, N T ，j＝1,2,…,N T ；
Vector x m (t) is an input signal vector of an mth virtual channel vector module, which includes N m The baseband input signals x mn (t)(n＝0,1,…,N m )，x mn (t) is a complex signal, expressed as:
all input signal vectors constitute the system transmit signal vector +.>
λ ij ＝E[h i H h j ]Is a scalar and the spatial radio channel matrix of the system is expressed as
H can be simply expressed as
wherein />
h lm Representing the spatial radio channel between the first receive antenna and the mth transmit antenna, l=1, 2, …, L R ，L R For the number of receive antennas.
Specifically, in step C, the method of calculating each complex weight value in each virtual channel vector module by the space-time optimization module according to the received feedback information using the space-time optimization algorithm may search for a global optimal system virtual channel vector by using the particle swarm algorithm, where,
Let the number of transmitting antennas be N T Also, the number of input signal vectors, the number of receiving antennas is L R W is a system virtual channel vector, expressed as:
here, vector w m Representing an mth virtual channel vector comprising N m Virtual channels w mn Expressed as: />
w mn Representing each baseband input signal x mn The virtual channel corresponding to (t) is specifically: />
N m Refers to the number of signal input ends corresponding to the mth virtual channel vector module, n=1, 2, … …, N m ，x mn (t) the baseband input signal input from the nth signal input end in the mth virtual channel vector module, and the vector x m (t) is an input signal vector of an mth virtual channel vector module, which includes N m The baseband input signals x mn (t)(n＝0,1,…,N m )，x mn (t) is a complex signal, expressed as +.>
Let the number of particles be S E Taking each system virtual channel vector of a space-time channel optimization MIMO wireless transmission system transmitting end as a position of one particle;
at the kth iteration time, the s-th particle position, i.e., the s-th system virtual channel vector, is expressed as
wherein ,/>
Is the mth virtual channel vector in the s-th particle position;
at the kth iteration time, the movement speed of the s-th particle is expressed as:
order the
Representing the individual optimum position searched so far for by the s-th particle at the kth iteration instant, wherein +.>
Is the mth virtual channel vector in the optimal position of the s-th particle individual;
order the
Representing the global optimum position searched so far for the entire population at the kth iteration, wherein +.>
Is the mth virtual channel vector in the global optimum position;
the reference signal occupies one time slot in each data frame, using
Representing a reference signal vector, where x Rm (t) is the vector x corresponding to the input signal m The mth parameter of (t)The signal vector is examined, and the reference signal vector is represented by w (s) (k) The estimated value under the action condition is expressed as +.>
The corresponding error is expressed as +.>
Similarly, at w (s) (k) The bit error rate BER under the action condition is expressed as +.>
Therefore, the specific steps of searching the global optimal system virtual channel vector by adopting the particle swarm algorithm are as follows:
Step 3, detecting the reference signal at the system receiving end to obtain S E Vector estimation of individual reference signals, i.e
Then using different position vectors w (s) (0) Calculating an error:
Transmitting each as a feedback signal
Or->
Optimizing a transmitting end of the MIMO wireless transmission system by a space-time channel;
step 4, setting the optimal individual position at the transmitting end of the space-time channel optimization MIMO wireless transmission system: p is p (s) (0)＝w (s) (0)(s＝1,2,…,S E ) Finding the minimum feedback signal value among all feedback signals, setting the particle position corresponding to the minimum feedback signal value as w (g) (0) Then the best global position is b (0) =w (g) (0)；
Step 5, updating inertia weight at the transmitting end of the space-time channel optimization MIMO wireless transmission system: α=b (k+1) +a, and for each particle, the velocity and position vectors are calculated as follows:
v (s) (k+1)＝αv (s) (k)+c 1 r 1 [p (s) (k)-w (s) (k)]+c 2 r 2 [b(k)-w (s) (k)]
w (s) (k+1)＝w (s) (k)+v (s) (k+1)
wherein s=1, 2, …, S E Vector v (s) The value of each element in (k+1) ranges from [ v ] min ,v max ]In addition, the transmit power is limited:
then, transmitting reference signals to the system receiving end in different time slots, and S is the total E A plurality of time slots, each time slot adopting a different position vector w (s) (k+1)(s＝1,2,…,S E )；
Step 6, detecting the reference signal at the system receiving end to obtain S E Vector estimation of individual reference signals, i.e
Then, using different position vectors w (s) (k+1) calculation error:
And then sends each as a feedback signal
Or->
Space-time channel optimized MIMO noneA transmission end of the line transmission system;
step 7, the transmitting end of the space-time channel optimized MIMO wireless transmission system updates the optimal individual position according to the feedback signal, if
Or->
Then p is (s) (k+1)＝w (s) (k+1); otherwise, P (s) (k+1)＝P (s) (k)；
step 9, if e R,b(k+1) <ε 1 or BERb(k+1) <ε 2 Stopping the operation and starting formally transmitting data; otherwise, k→k+1, go back to step 5.
The method has the beneficial effects that in the scheme of the invention, the transmitting end and the processing method of the MIMO wireless transmission system are optimized through the space-time channel, so that the number of transmission channels of each transmitting antenna in the MIMO wireless communication system can be greatly increased, and the number of signal or data flow paths transmitted by each antenna is increased, and the data transmission rate, the system capacity and the frequency spectrum efficiency of the MIMO system can be obviously improved under the condition that the number of the antennas is not increased. When the same data stream is transmitted, compared with the existing MIMO system, the MIMO system has fewer antennas, thereby reducing the number of transmitting antennas, reducing the complexity of the system and the cost of the system, and according to feedback information, the dynamic virtual channel adjustment is carried out, the receiving error rate is obviously reduced, and the reliability of signal transmission is improved.
Drawings
Fig. 1 is a system block diagram of an existing MIMO wireless communication system.
Fig. 2 is a system block diagram of a transmitting end of the space-time channel-optimized MIMO wireless transmission system of the present invention.
Fig. 3 is a system block diagram of a space-time channel-optimized MIMO wireless transmission system in accordance with an embodiment of the present invention.
Detailed Description
The technical scheme of the invention is described in detail below with reference to the embodiment and the attached drawings.
The system block diagram of the transmitting end of the space-time channel optimization MIMO wireless transmission system is shown in figure 2. The invention discloses a space-time channel optimization MIMO wireless transmission system transmitting end, which comprises a plurality of signal transmitting ends, wherein each signal transmitting end comprises a modulation filtering amplifying module and a transmitting antenna, and further comprises a plurality of virtual channel vector modules, feedback information receiving ends and space-time optimization modules, wherein each virtual channel vector module corresponds to at least one signal input end, each signal input end corresponds to only one virtual channel vector module, the output end of each virtual channel vector module is only connected with one signal transmitting end in a one-to-one correspondence manner, the feedback information receiving ends are connected with the space-time optimization modules, the space-time optimization modules are connected with each virtual channel vector module, the space-time optimization modules are connected with each signal input end, and the virtual channel vector modules are used for carrying out complex weighting operation on baseband signals input by each signal input end connected with the virtual channel vector modules according to set complex weighting values, and combining all the complex weighted baseband signals and transmitting the baseband signals to the corresponding signal transmitting ends; the feedback information receiving end is used for receiving feedback information sent by the system receiving end and transmitting the feedback information to the space-time optimization module; and the space-time optimization module is used for calculating each complex weight value in each virtual channel vector module by adopting a space-time optimization algorithm according to the received feedback information, and setting the complex weight values.
The invention relates to a processing method of a transmitting end of a space-time channel optimization MIMO wireless transmission system, which is applied to the transmitting end of the space-time channel optimization MIMO wireless transmission system, and is characterized in that firstly, a signal input end receives an input baseband signal and transmits the baseband signal to a corresponding virtual channel vector module, each virtual channel vector module carries out complex weighting operation on the baseband signal input by each signal input end connected with the virtual channel vector module according to a set complex weighting value, all the complex weighted baseband signals are combined and then transmitted to the corresponding signal transmitting end for transmission, a feedback information receiving end receives feedback information transmitted by a system receiving end in real time and transmits the feedback information to a space-time optimization module, and the space-time optimization module calculates each complex weighting value in each virtual channel vector module according to the received feedback information by adopting a space-time optimization algorithm and sets the complex weighting value.
Examples
The system block diagram of the transmitting end of the space-time channel optimization MIMO wireless transmission system in the embodiment of the invention is shown in figure 2, and comprises a plurality of signal transmitting ends, each signal transmitting end comprises a modulation filtering amplifying module and a transmitting antenna, and further comprises a plurality of virtual channel vector modules, feedback information receiving ends and space-time optimization modules, wherein each virtual channel vector module corresponds to at least one signal input end, each signal input end corresponds to only one virtual channel vector module, the output end of each virtual channel vector module is only connected with one signal transmitting end in a one-to-one correspondence manner, the feedback information receiving end is connected with the space-time optimization module, the space-time optimization module is connected with each virtual channel vector module, the space-time optimization module is connected with each signal input end, and the virtual channel vector modules are used for carrying out complex weighting operation on baseband signals input by each signal input end connected with the virtual channel vector module according to set complex weighting values, and combining all the baseband signals subjected to complex weighting and transmitting the baseband signals to the corresponding signal transmitting ends; the feedback information receiving end is used for receiving feedback information sent by the system receiving end and transmitting the feedback information to the space-time optimization module; and the space-time optimization module is used for calculating each complex weight value in each virtual channel vector module by adopting a space-time optimization algorithm according to the received feedback information, and setting the complex weight values.
In this example, the virtual channel vector module includes complex weighting modules corresponding to the number of signal input ends and an adder, the input end of each complex weighting module is connected with one signal input end in a one-to-one correspondence manner, the output end of each complex weighting module is connected with one input end of the adder in a one-to-one correspondence manner, the output end of each adder is connected with one signal transmitting end in a one-to-one correspondence manner as the output end of the virtual channel vector module, and the space-time optimization module is connected with each complex weighting module.
The baseband signals input by each signal input end can be different or some of the baseband signals can be the same and some of the baseband signals can be different, of course, the baseband signals can also be the same, the number of the signal input ends corresponding to each virtual channel vector module can also be different or the same, and the feedback information comprises channel identification and system state information such as signal-to-noise ratio, error rate, error value, channel estimation value and the like.
In this example, a system block diagram of the space-time channel optimization MIMO wireless transmission system composed of the space-time channel optimization MIMO wireless transmission system transmitting end is shown in fig. 3, and includes a corresponding system receiving end, where the system receiving end includes multiple receiving antennas, a corresponding demodulation filtering amplifying module, a corresponding signal detecting and processing module, a channel identification and system state information collecting module, and a feedback information transmitting end, and the channel identification and system state information collecting module and the feedback information transmitting end are parts of some existing receiving ends, which are not described in detail herein.
When in use, the treatment method comprises the following steps:
A. the signal input end receives the input baseband signal and transmits the baseband signal to the corresponding virtual channel vector module;
B. each virtual channel vector module carries out complex weighting operation on the baseband signals input by each signal input end connected with the virtual channel vector module according to the set complex weighting value, and all the complex weighted baseband signals are combined and then transmitted to the corresponding signal transmitting end for transmission;
C. and B, the feedback information receiving end receives feedback information sent by the system receiving end in real time and transmits the feedback information to the space-time optimizing module, and the space-time optimizing module calculates each complex weight value in each virtual channel vector module by adopting a space-time optimizing algorithm according to the received feedback information and sets the complex weight value, and the step B is returned to.
In this step, the space-time optimization module calculates each complex weight value in each virtual channel vector module by using a space-time optimization algorithm according to the received feedback information, and the specific method and principle thereof are as follows:
a transmitting end (hereinafter referred to as a transmitting end) of the space-time channel optimized MIMO wireless transmission system is provided with N T A root transmitting antenna with a corresponding receiving end having L R Root receiving antenna, in general, L R ≥N T The transmitting end has N T A plurality of input signal vectors each including a plurality of baseband input signals, the mth input signal vector being
I.e. vector x m (t) includes N m The baseband input signals x mn (t)(n＝0,1,…,N m )，x mn And (t) is a complex signal.
All N of system transmitting terminal T The input signal vectors form the system transmitting signal vector
Each baseband input signal x mn (t) passing through a corresponding virtual channel
By w m Representing the mth virtual channel vector, < ->
Vector w m Comprising N m Virtual channels w mn . At the transmitting end, N T Virtual channel vectors w m And N T Input signal vector x m (t) one-to-one correspondence, which can be represented by a systematic virtual channel vector, i.e. +.>
At the receiving end, the first receiving antenna receives signals from all N T The signal of the root transmit antenna. Let h lm Representing the spatial radio channel between the first receive antenna to the mth transmit antenna. Signal x mn (t) two transmission paths from the mth transmitting antenna to the first receiving antenna, i.e. virtual channel w mn And spatial radio channel h lm These two channels are concatenated to form an overall transmission channel w mn * h lm The cooperative space division channels are referred to. Thus, the signal transmitted by the mth transmitting antenna is
The signal received by the first receiving antenna is
in the formula ,ql And (t) is Gaussian white noise of the first receiving antenna. The spatial radio channel matrix of the system is expressed as
H can be simply expressed as
wherein />
Is provided with
For the received signal vector at the receiving end
in the formula ,
is the noise vector at the receiving end.
In the system, the system cooperative space division channel matrix is expressed as
in the formula ,gm ＝h m w m H Is an L R ×N m And the matrix represents the cooperative space division channel corresponding to the mth transmitting antenna. Thus, the received signal vector may be further represented as
By adjusting and optimizing virtual channel w mn The coordinated space division channel w can be adjusted and optimized mn * h lm (m＝1,2,…,N T ；n＝1,2,…,N m ；l＝1,2,…,L R ) The system has reasonable overall transmission channel layout, and is most favorable for signal detection of a receiving end and optimization of system transmission performance.
At the system receiving end, the signal-to-noise ratio is
Here, P R ＝E[(gx(t)) H (gx(t))]Is the received signal power of the receiving end, sigma 2 ＝E[q(t) H q(t)]Is the noise power of the receiving end. Will beP R ＝E[(gx(t)) H (gx(t))]Spread out to obtain
in the formula ,λij ＝E[h i H h j ]Is a scalar, R ij ＝E[x i (t)x j (t) H ]Is N i ×N j Input correlation matrix, (i=1, 2, …, N T ；j＝1,2,…,N T ) R is one
The signal transmission matrix is a matrix of the signal transmission,
at the system receiving end, we want to maximize the signal-to-noise ratio η R But due to the noise power sigma at the receiving end 2 Considered as a constant, so that the received signal power P is maximized R Equivalent to maximizing the signal-to-noise ratio eta R Therefore, the optimization criteria for this example are as follows:
here, G is a constant. Under the condition that the power of the transmitted signal is constant, the optimization mechanism maximizes the power of the signal transmitted to the receiving end by adjusting the virtual channel. The optimization solution is as follows:
in the formula ,
is the eigenvector corresponding to the largest eigenvalue of matrix R, and +.>
w opt I.e. the optimal value of the complex weight vector w to be obtained.
For QPSK signals, if the received signal-to-noise ratio is known
The reception Bit Error Rate (BER) is +.>
Where Q (-) is a function defined as
Thus, for QPSK signals, an optimal solution is used>
The time receiving error rate (BER) is
in the formula ,PRmax Is the maximum value of the received signal power.
Although it is
An optimized closing solution is provided, but in some cases its effect is not necessarily ideal. Another solution is to search for a globally optimal solution using a particle swarm algorithm.
Here, let the particle population size be S E I.e. the number of particles is S E And takes each potential system virtual channel vector of the transmitting end as the position of one particle. At the kth iteration time, the s-th particle position, i.e., the s-th system virtual channel vector, is expressed as
in the formula ,
is the mth virtual channel vector in the s-th particle position. At the kth iteration time, the movement speed of the kth particle is expressed as
in the formula ,
is a virtual channel vector->
Is provided for the respective movement speed of the vehicle. Let->
Representing the individual optimal position searched so far for by the s-th particle at the kth iteration moment, wherein, 
Is the mth virtual channel vector in the individual optimal position of the s-th particle. Let->
Representing the global optimum position searched so far for the entire population at the kth iteration time, where,
is the mth virtual channel vector in the globally optimal location. In this approach, the use of reference signals will facilitate searching. The reference signal occupies one slot in each data frame, with +.>
Representing a reference signal vector, where x Rm (t) is the vector x corresponding to the input signal m The mth reference signal vector of (t). In the optimization process, the reference signal is detected or estimated first, then the detection or estimation result is compared with the actual reference signal to generate an error, and the error is used as feedback information to be sent to the transmitting end. In detecting the reference signal vector x R At (t), the signal vector estimate is subjected to the virtual channel vector w (s) (k) Thus, the reference signal vector is set at w (s) (k) The estimated value under the condition is expressed as +.>
The corresponding error is expressed as +.>
Similarly, at w (s) (k) The bit error rate BER under the condition is expressed as +.>
Therefore, the specific steps of searching the global optimal system virtual channel vector by adopting the particle swarm algorithm are as follows:
Step 3, detecting the reference signal at the system receiving end to obtain S E Estimates of individual reference signal vectors, i.e.
Then, using different position vectors w (s) (0) Calculating an error:
or calculate
Then, each +.>
Or->
To the system transmitting end (s=1, 2, …, S E )。
Step 4, atThe system transmitting end sets the optimal individual position: p is p (s) (0)＝w (s) (0)(s＝1,2,…,S E ) Finding the minimum feedback signal value among all feedback signals, setting the particle position corresponding to the minimum feedback signal value as w (g) (0) Then the best global position is b (0) =w (g) (0)。
Step 5, updating inertia weight at a system transmitting end: α=b (k+1) +a. For each particle, its velocity and position vector is calculated as follows:
v (s) (k+1)＝αv (s) (k)+c 1 r 1 [p (s) (k)-w (s) (k)]+c 2 r 2 [b(k)-w (s) (k)]
w (s) (k+1)＝w (s) (k)+v (s) (k+1)
wherein s=1, 2, …, S E . Vector v (s) The value of each element in (k+1) ranges from [ v ] min ,v max ]. In addition, the transmit power is limited:
then, transmitting reference signals to the system receiving end in different time slots, and S is the total E A plurality of time slots, each time slot adopting a different position vector w (s) (k+1)(s＝1,2,…,S E )。
Step 6, detecting the reference signal at the system receiving end to obtain S E Vector estimation of individual reference signals, i.e
Then, using different position vectors w (s) (k+1) calculation error: />
And 7, updating the optimal individual position at the system transmitting end according to the feedback signal. If it is
Or->
Then p is (s) (k+1)＝w (s) (k+1); if it is
Or->
Then P (s) (k+1)＝P (s) (k)。
And 8, carrying out optimal global position updating at a system transmitting end according to the feedback signal. Finding the minimum feedback signal value among all feedback signals, setting the particle position corresponding to the minimum feedback signal value to be w (g) (k+1) if
Or->
The best global position is b (k+1) =w (g) (k+1); if it is
Or->
The best global position is b (k+1) =b (k).
Step 9, if e R,b(k+1) <ε 1 or BERb(k+1) <ε 2 Stopping the operation and starting formally transmitting data; if e R,b(k+1) ≥ε 1 or BERb(k+1) ≥ε 2 K→k+1, and the process returns to step 5.
In the above steps 3, 6, when the QPSK signal is used, if the received signal-to-noise ratio is already obtained, it is available that
BER is calculated directly. />
Claims (8)
1. The space-time channel optimization MIMO wireless transmission system transmitting end comprises a plurality of signal transmitting ends, each signal transmitting end comprises a modulation filtering amplifying module and a transmitting antenna, and is characterized by further comprising a plurality of virtual channel vector modules, feedback information receiving ends and space-time optimization modules, wherein each virtual channel vector module corresponds to at least one signal input end, each signal input end corresponds to only one virtual channel vector module, the output end of each virtual channel vector module is only connected with one signal transmitting end in a one-to-one correspondence manner, the feedback information receiving ends are connected with the space-time optimization modules, the space-time optimization modules are connected with each virtual channel vector module, and the space-time optimization modules are connected with each signal input end;
The virtual channel vector module is used for carrying out complex weighting operation on the baseband signals input by each signal input end connected with the virtual channel vector module according to the set complex weighting value, combining all the complex weighted baseband signals and transmitting the combined baseband signals to the corresponding signal transmitting end;
the feedback information receiving end is used for receiving feedback information sent by the system receiving end and transmitting the feedback information to the space-time optimization module;
the space-time optimization module is used for calculating each complex weight value in each virtual channel vector module by adopting a space-time optimization algorithm according to the received feedback information and setting the complex weight values;
the space-time optimization module calculates each complex weight value in each virtual channel vector module by adopting a space-time optimization algorithm according to the received feedback information, and the method specifically comprises the following steps:
the space-time optimization module calculates each complex weight value in each virtual channel vector module by adopting a space-time optimization algorithm according to the received feedback information, and the calculation formula is as follows:
wherein ,wopt The optimal value of the complex weight vector w to be obtained is also called the system virtual channel vector, and is expressed as:
here, vector w m Representing an mth virtual channel vector comprising N m Virtual channels w mn Expressed as: / >
w mn Representing each baseband input signal x mn The virtual channel corresponding to (t) is specifically: />
N T For the number of transmit antennas, also for the number of input signal vectors, N m Refers to the number of signal input ends corresponding to the mth virtual channel vector module, n=1, 2, … …, N m ，x mn (t) means a baseband input signal input from an n-th signal input terminal in the m-th virtual channel vector module;
R is one
The signal transmission matrix refers to:
wherein ,Rij ＝E[x i (t)x j (t) H ]Is N i ×N j Input correlation matrix, i=1, 2, …, N T ，j＝1,2,…,N T ；
Vector x m (t) is an input signal vector of an mth virtual channel vector module, which includes N m The baseband input signals x mn (t)(n＝0,1,…,N m )，x mn (t) is a complex signal, expressed as:
/>
all input signal vectors constitute the system transmit signal vector +.>
λ ij ＝E[h i H h j ]Is a scalar and the spatial radio channel matrix of the system is expressed as
H can be simply expressed as
wherein />
h lm Representing the spatial radio channel between the first receive antenna and the mth transmit antenna, l=1, 2, …, L R ，L R For the number of receive antennas;
the method for calculating each complex weight value in each virtual channel vector module by adopting a space-time optimization algorithm is to search a global optimal system virtual channel vector by adopting a particle swarm algorithm, wherein,
Let the number of transmitting antennas be N T Also, the number of input signal vectors, the number of receiving antennas is L R W is a system virtual channel vector, expressed as:
here, vector w m Representing an mth virtual channel vector comprising N m Virtual channels w mn Expressed as: />
w mn Representing each baseband input signal x mn The virtual channel corresponding to (t) is specifically: />
N m Refers to the number of signal input ends corresponding to the mth virtual channel vector module, n=1, 2, … …, N m ，x mn (t) the baseband input signal input from the nth signal input end in the mth virtual channel vector module, and the vector x m (t) is an input signal vector of an mth virtual channel vector module, which includes N m The baseband input signals x mn (t)(n＝0,1,…,N m )，x mn (t) is a complex signal, expressed as
Let the number of particles be S E And optimizing space-time channel to MIMO wireless transmission systemEach system virtual channel vector of the transmitting end is used as a position of a particle;
at the kth iteration time, the s-th particle position, i.e., the s-th system virtual channel vector, is expressed as
wherein ,
is the mth virtual channel vector in the s-th particle position;
at the kth iteration time, the movement speed of the s-th particle is expressed as:
wherein ,/>
Is a virtual channel vector- >
Corresponding movement speed of (a);
order the
Representing the individual optimum position searched so far for by the s-th particle at the kth iteration instant, wherein +.>
Is the individual optimal position of the s-th particleAn mth virtual channel vector of (a);
order the
Representing the global optimum position searched so far for the entire population at the kth iteration, wherein +.>
Is the mth virtual channel vector in the global optimum position;
the reference signal occupies one time slot in each data frame, using
Representing a reference signal vector, where x Rm (t) is the vector x corresponding to the input signal m The mth reference signal vector of (t), the reference signal vector is set at w (s) (k) The estimated value under the action condition is expressed as +.>
The corresponding error is expressed as +.>
Similarly, at w (s) (k) The bit error rate BER under the action condition is expressed as +.>
Therefore, the specific steps of searching the global optimal system virtual channel vector by adopting the particle swarm algorithm are as follows:
step 1, optimizing a transmitting end of the MIMO wireless transmission system at a space-time channel, and setting a constant according to an actual communication environment: c 1 ,c 2 ,r 1 ，r 2 ，ε 1 ,ε 2 ，A,B，G T ,v min ，v max, wherein ,c1 and c2 Is a learning factor that gives particles self-summary and excellent individual in the populationThe learning ability, thereby approaching to the own history optimum and the history optimum within the group; r is (r) 1 and r2 Is [0,1 ]]Random numbers in between; epsilon 1 And epsilon 2 Is a small constant set according to an actual communication environment; a is an initial inertial weight; b is an update coefficient of the inertia weight; g T Is a virtual channel gain constraint constant; v min and vmax Respectively, the minimum speed and the maximum speed of the movement of the particles, and limiting the speed range of the particles;
step 2, optimizing a transmitting end of the MIMO wireless transmission system at a space-time channel, setting k=0, and randomly initializing the position and the moving speed of each particle to obtain the position and the moving speed of each particle respectively
And
using each of the obtained w (s) (0) Slotted transmission of a reference signal sequence x R (t), a total of S E A different time slot, each time slot using a different position vector w (s) (0)(s＝1,2,…,S E )；
Step 3, detecting the reference signal at the system receiving end to obtain S E Vector estimation of individual reference signals, i.e
Then using different position vectors w (s) (0) Calculating an error:
Transmitting each as a feedback signal
Or->
Optimizing a transmitting end of the MIMO wireless transmission system by a space-time channel;
step 4, setting the optimal individual position at the transmitting end of the space-time channel optimization MIMO wireless transmission system: p is p (s) (0)＝w (s) (0)(s＝1,2,…,S E ) Finding the minimum feedback signal value among all feedback signals, setting the particle position corresponding to the minimum feedback signal value as w (g) (0) Then the best global position is b (0) =w (g) (0)；
Step 5, updating inertia weight at the transmitting end of the space-time channel optimization MIMO wireless transmission system: α=b (k+1) +a, and for each particle, the velocity and position vectors are calculated as follows:
v (s) (k+1)＝αv (s) (k)+c 1 r 1 [p (s) (k)-w (s) (k)]+c 2 r 2 [b(k)-w (s) (k)]
w (s) (k+1)＝w (s) (k)+v (s) (k+1)
wherein s=1, 2, …, S E Vector v (s) The value of each element in (k+1) ranges from [ v ] min ,v max ]In addition, the transmit power is limited:
then, transmitting reference signals to the system receiving end in different time slots, and S is the total E A plurality of time slots, each time slot adopting a different position vector w (s) (k+1)(s＝1,2,…,S E )；
Step 6, detecting the reference signal at the system receiving end to obtain S E Vector estimation of individual reference signals, i.e
Then, using different position vectors w (s) (k+1) calculation error:
And then sends each as a feedback signal
Or->
Optimizing a transmitting end of the MIMO wireless transmission system by a space-time channel;
step 7, the transmitting end of the space-time channel optimized MIMO wireless transmission system updates the optimal individual position according to the feedback signal, if
Or->
Then p is (s) (k+1)＝w (s) (k+1); otherwise, P (s) (k+1)＝P (s) (k)；
Step 8, the transmitting end of the space-time channel optimized MIMO wireless transmission system updates the optimal global position according to the feedback signals, finds out the minimum feedback signal value in all the feedback signals, and sets the particle position corresponding to the minimum feedback signal value as w (g) (k+1) if
Or->
The best global position is b (k+1) =w (g) (k+1); otherwise, the optimal global position is b (k+1) =b (k), +.>
For the reference signal vector at W (g) Corresponding error under the action of (k+1),. About.>
Is W (g) BER representation of bit error rate under (k+1) action conditions, e R,b(k) BER for corresponding error of reference signal vector under b (k) action condition b(k) A BER representation of bit error rate under b (k) acting conditions;
step 9, if e R,b(k+1) ＜ε 1 or BERb(k+1) ＜ε 2 Stopping the operation and starting formally transmitting data; otherwise, k→k+1, go back to step 5,e R,b(k+1) BER for corresponding error of reference signal vector under b (k+1) action condition b(k+1) A BER representation of the bit error rate under the conditions of b (k+1) action.
2. The transmission end of the space-time channel optimization MIMO wireless transmission system of claim 1, wherein the virtual channel vector module includes complex weighting modules corresponding to the number of signal input ends and an adder, the input end of each complex weighting module is connected with one signal input end in one-to-one correspondence, the output end of each complex weighting module is connected with one input end of the adder in one-to-one correspondence, the output end of each adder is connected with one signal transmission end in one-to-one correspondence as the output end of the virtual channel vector module, and the space-time optimization module is connected with each complex weighting module.
3. The transmission terminal of the space-time channel-optimized MIMO wireless transmission system of claim 1, wherein the baseband signal input from each signal input terminal is different.
4. The transmitting terminal of the space-time channel-optimized MIMO wireless transmission system of claim 1, wherein the number of signal input terminals corresponding to each virtual channel vector module is different.
5. The transmitting end of the space-time channel-optimized MIMO wireless transmission system of claim 1, wherein the feedback information comprises channel identification and system status information.
6. The transmitter of the space-time channel-optimized MIMO wireless transmission system of claim 5, wherein the channel identification and system status information comprises signal-to-noise ratio, bit error rate, error value, and channel estimation value.
7. The processing method of the space-time channel optimization MIMO wireless transmission system transmitting end is applied to the space-time channel optimization MIMO wireless transmission system transmitting end as set forth in claim 1 or 2 or 3 or 4 or 5 or 6, and is characterized by comprising the following steps:
A. the signal input end receives the input baseband signal and transmits the baseband signal to the corresponding virtual channel vector module;
B. Each virtual channel vector module carries out complex weighting operation on the baseband signals input by each signal input end connected with the virtual channel vector module according to the set complex weighting value, and all the complex weighted baseband signals are combined and then transmitted to the corresponding signal transmitting end for transmission;
C. the feedback information receiving end receives feedback information sent by the system receiving end in real time and transmits the feedback information to the space-time optimizing module, and the space-time optimizing module calculates each complex weight value in each virtual channel vector module by adopting a space-time optimizing algorithm according to the received feedback information and sets the complex weight value, and the step B is returned to;
in the step C, the method for calculating each complex weight value in each virtual channel vector module by the space-time optimization module according to the received feedback information by using a space-time optimization algorithm includes:
the space-time optimization module calculates each complex weight value in each virtual channel vector module by adopting a space-time optimization algorithm according to the received feedback information, and the calculation formula is as follows:
wherein ,wopt The optimal value of the complex weight vector w to be obtained is also called the system virtual channel vector, and is expressed as:
here, vector w m Representing an mth virtual channel vector comprising N m Virtual channels w mn Expressed as: />
w mn Representing each baseband input signal x mn The virtual channel corresponding to (t) is specifically: />
N T For the number of transmit antennas, also for the number of input signal vectors, N m Refers to the number of signal input ends corresponding to the mth virtual channel vector module, n=1, 2, … …, N m ，x mn (t) means a baseband input signal input from an n-th signal input terminal in the m-th virtual channel vector module;
R is one
The signal transmission matrix refers to:
wherein ,Rij ＝E[x i (t)x j (t) H ]Is N i ×N j Input correlation matrix, i=1, 2, …, N T ，j＝1,2,…,N T ；
Vector x m (t) is an input signal vector of an mth virtual channel vector module, which includes N m The baseband input signals x mn (t)(n＝0,1,…,N m )，x mn (t) is a complex signal, expressed as:
all input signal vectors constitute the system transmit signal vector +.>
λ ij ＝E[h i H h j ]Is a scalar and the spatial radio channel matrix of the system is expressed as
H can be simply expressed as
wherein />
h lm Representing the spatial radio channel between the first receive antenna and the mth transmit antenna, l=1, 2, …, L R ，L R For the number of receive antennas;
the method for calculating each complex weight value in each virtual channel vector module by adopting a space-time optimization algorithm is to search a global optimal system virtual channel vector by adopting a particle swarm algorithm, wherein,
Let the number of transmitting antennas be N T Also, the number of input signal vectors, the number of receiving antennas is L R W is a system virtual channel vector, expressed as:
here, vector w m Representing an mth virtual channel vector comprising N m Virtual channels w mn Expressed as: />
w mn Representing each baseband input signal x mn The virtual channel corresponding to (t) is specifically: />
N m Refers to the number of signal input ends corresponding to the mth virtual channel vector module, n=1, 2, … …, N m ，x mn (t) the baseband input signal input from the nth signal input end in the mth virtual channel vector module, and the vector x m (t) is an input signal vector of an mth virtual channel vector module, which includes N m The baseband input signals x mn (t)(n＝0,1,…,N m )，x mn (t) is a complex signal, expressed as
Let the number of particles be S E Taking each system virtual channel vector of a space-time channel optimization MIMO wireless transmission system transmitting end as a position of one particle;
at the kth iteration time, the s-th particle position, i.e., the s-th system virtual channel vector, is expressed as
wherein ,/>
Is the mth virtual channel vector in the s-th particle position;
at the kth iteration time, the movement speed of the s-th particle is expressed as:
order the
Representing the individual optimal position searched so far for by the s-th particle at the kth iteration moment, wherein,
is the mth virtual channel vector in the optimal position of the s-th particle individual;
order the
Representing the global optimum position searched so far for the entire population at the kth iteration, wherein +.>
Is the mth virtual channel vector in the global optimum position; />
The reference signal occupies one time slot in each data frame, using
Representing a reference signal vector, where x Rm (t) is the vector x corresponding to the input signal m The mth reference signal vector of (t), the reference signal vector is set at w (s) (k) The estimated value under the action condition is expressed as +.>
The corresponding error is expressed as +.>
Similarly, at w (s) (k) The bit error rate BER under the action condition is expressed as +.>
Therefore, the specific steps of searching the global optimal system virtual channel vector by adopting the particle swarm algorithm are as follows:
step 1, optimizing a transmitting end of the MIMO wireless transmission system at a space-time channel, and setting a constant according to an actual communication environment: c 1 ,c 2 ,r 1 ，r 2 ，ε 1 ,ε 2 ，A,B，G T ,v min ，v max, wherein ,c1 and c2 Is a learning factor that gives particles the ability to self-summarize and learn to excellent individuals in a population, thereby optimizing to their own history The historic optimal points in the group are close; r is (r) 1 and r2 Is [0,1 ]]Random numbers in between; epsilon 1 And epsilon 2 Is a small constant set according to an actual communication environment; a is an initial inertial weight; b is an update coefficient of the inertia weight; g T Is a virtual channel gain constraint constant; v min and vmax Respectively, the minimum speed and the maximum speed of the movement of the particles, and limiting the speed range of the particles;
step 2, optimizing a transmitting end of the MIMO wireless transmission system at a space-time channel, setting k=0, and randomly initializing the position and the moving speed of each particle to obtain the position and the moving speed of each particle respectively
And
using each of the obtained w (s) (0) Slotted transmission of a reference signal sequence x R (t), a total of S E A different time slot, each time slot using a different position vector w (s) (0)(s＝1,2,…,S E )；
Step 3, detecting the reference signal at the system receiving end to obtain S E Vector estimation of individual reference signals, i.e
Then using different position vectors w (s) (0) Calculating an error:
Transmitting each as a feedback signal
Or->
Optimizing a transmitting end of the MIMO wireless transmission system by a space-time channel;
step 4, setting the optimal individual position at the transmitting end of the space-time channel optimization MIMO wireless transmission system: p is p (s) (0)＝w (s) (0)(s＝1,2,…,S E ) Finding the minimum feedback signal value among all feedback signals, setting the particle position corresponding to the minimum feedback signal value as w (g) (0) Then the best global position is b (0) =w (g) (0)；
Step 5, updating inertia weight at the transmitting end of the space-time channel optimization MIMO wireless transmission system: α=b (k+1) +a, and for each particle, the velocity and position vectors are calculated as follows:
v (s) (k+1)＝αv (s) (k)+c 1 r 1 [p (s) (k)-w (s) (k)]+c 2 r 2 [b(k)-w (s) (k)]
w (s) (k+1)＝w (s) (k)+v (s) (k+1)
wherein s=1, 2, …, S E Vector v (s) The value of each element in (k+1) ranges from [ v ] min ,v max ]In addition, the transmit power is limited:
then, transmitting reference signals to the system receiving end in different time slots, and S is the total E A plurality of time slots, each time slot adopting a different position vector w (s) (k+1)(s＝1,2,…,S E )；
Step 6, detecting the reference signal at the system receiving end to obtain S E Vector estimation of individual reference signals, i.e
Then, using different position vectors w (s) (k+1) calculation error:
And then sends each as a feedback signal
Or->
Optimizing a transmitting end of the MIMO wireless transmission system by a space-time channel;
step 7, the transmitting end of the space-time channel optimized MIMO wireless transmission system updates the optimal individual position according to the feedback signal, if
Or->
Then p is (s) (k+1)＝w (s) (k+1); otherwise, P (s) (k+1)＝P (s) (k)；
Step 8, the transmitting end of the space-time channel optimized MIMO wireless transmission system updates the optimal global position according to the feedback signals, finds out the minimum feedback signal value in all the feedback signals, and sets the particle position corresponding to the minimum feedback signal value as w (g) (k+1) if
Or->
The best global position is b (k+1) =w (g) (k+1); otherwise, the optimal global position is b (k+1) =b (k), +.>
For the reference signal vector at W (g) Corresponding error under the action of (k+1),. About.>
Is W (g) BER representation of bit error rate under (k+1) action conditions, e R,b(k) BER for corresponding error of reference signal vector under b (k) action condition b(k) A BER representation of bit error rate under b (k) acting conditions;
step 9, if e R,b(k+1) ＜ε 1 or BERb(k+1) ＜ε 2 Stopping the operation and starting formally transmitting data; otherwise, k→k+1, go back to step 5,e R,b(k+1) BER for corresponding error of reference signal vector under b (k+1) action condition b(k+1) A BER representation of the bit error rate under the conditions of b (k+1) action.
8. The method for processing transmitting end of space-time channel optimized MIMO wireless transmission system as claimed in claim 7, wherein in step B, the signal outputted by the mth virtual channel vector module is
Wherein the vector w m Representing an mth virtual channel vector comprising N m Virtual channels w mn Expressed as:
w mn representing each baseband input signalx mn The virtual channel corresponding to (t) is specifically: />
x mn (t) is a complex signal, N T For the number of transmit antennas, also for the number of input signal vectors, N m Refers to the number of signal input ends corresponding to the mth virtual channel vector module, n=1, 2, … …, N m ，x mn (t) the baseband input signal input from the nth signal input end in the mth virtual channel vector module, and the vector x m (t) refers to the input signal vector of the mth virtual channel vector module, expressed as: />
/>
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