TWI420838B - Cooperative communications system and training sequence designing method thereof - Google Patents

Description

Cooperative communication system and training sequence design method thereof

The invention relates to a cooperative communication system and a training sequence design method thereof, in particular to a cooperative communication system capable of improving system strength and toughness and a training sequence design method thereof.

With the development and popularization of multimedia communication technologies, the demand for information volume and information service types is increasing, and any single network or single technology may not be able to meet all the needs. Therefore, it is possible to generate their own independent operations by combining different terminals, mechanisms, technologies or systems. At present, this "cooperation" mechanism has gradually been valued and used in the radio communication environment, such as cooperative communication systems.

Cooperative communication systems are often used to improve signal transmission for better communication quality. Among them, the relay terminal of the cooperative communication system assists in three modes of transmission. One way is to amplify the received signal and send it directly (amplify-and-forward (AF)); the other way is to decode the received signal and then re-encode and then send it (decode-and-forward (DF); another way Then, the received signal is compressed and then sent (compress-and-forward, CF). However, it is necessary to have complete channel state information (CSI) before using the spatial diversity brought about by cooperative communication, so channel estimation is required first. Therefore, channel estimation is typically performed using known training sequences and an optimal training sequence is designed in a particular situation.

However, most of the cooperative communication systems can only design the optimal training sequence under independent channels, but in real life, there may be channel-related and noise-related, and even the relay may be maliciously interfered with the behavior. And greatly affect the quality of communication.

Therefore, it is necessary to provide a cooperative communication system and a training sequence design method thereof to solve the problems existing in the prior art.

The main object of the present invention is to provide a cooperative communication system and a training sequence design method thereof, which can improve the toughness of the cooperative communication system.

According to an embodiment of the present invention, the present invention provides a cooperative communication system, including: at least one transmitting end for transmitting a signal; and at least one receiving end for receiving the signal, wherein the receiving end is provided with a linear least square error An estimator for estimating the signal; a plurality of relay terminals disposed between the transmitting end and the receiving end for receiving the signal transmitted by the transmitting end and transmitting the signal to the receiving end; And a training sequence setting unit configured to set a maximum of the signal according to an estimated result estimated by the linear least square error estimator, a channel correlation coefficient, a correlated noise coefficient, and a virtual abnormal signal. Good training sequence.

In an embodiment of the present invention, the relays amplify the received signal and directly transmit the signal to the receiving end.

In an embodiment of the invention, the relays decode the received signal and re-encode the signal to the receiving end.

In an embodiment of the invention, the relays compress the received signal and transmit the received signal to the receiving end.

Moreover, in accordance with an embodiment of the present invention, a training sequence design method for a cooperative communication system of the present invention, wherein the cooperative communication system includes at least one transmitting end, at least one receiving end, and a plurality of repeating ends, the method comprising the following steps : using a linear least square error estimator to estimate the signal transmitted by the transmitting end; obtaining a channel correlation coefficient and a correlated noise coefficient; setting a virtual abnormal signal; and according to the linear least square error estimator The estimated estimated result, the channel correlation coefficient, the correlated noise coefficient, and the virtual abnormal signal are used to set an optimal training sequence of the signal.

In an embodiment of the invention, the step of setting the optimal training sequence includes minimizing an average squared error of the cooperative communication system.

Therefore, the cooperative communication system and the training sequence design method thereof of the present invention can design an optimal training sequence according to the situation of channel correlation, noise correlation and abnormal relay, which can perform corresponding changes according to different malicious signals. To reduce the system error rate and enhance the toughness of the cooperative communication system.

The above and other objects, features, advantages and embodiments of the present invention will become more apparent and understood. It is to be understood that the embodiments are merely illustrative of the embodiments of the invention and are not intended to limit the invention.

Please refer to FIG. 1, which shows a system block diagram of a cooperative communication system in accordance with an embodiment of the present invention. The cooperative communication system of this embodiment includes at least one transmitting end 110, at least one receiving end 120, a plurality of repeating ends 130, and a training sequence setting unit 140. The transmitting end 110 can be, for example, a radio base station for transmitting signals. The receiving end 120 is configured to receive the signal transmitted by the transmitting end 110, and the receiving end 120 is, for example, an electronic device capable of using wireless communication, such as a desktop computer, a notebook computer, a palmtop computer, a mobile phone, and a personal digital assistant (Personal). Digital Assistant, PDA), portable navigation map device or multimedia player. The receiving end 120 can be provided with a linear minimum mean square estimator (LMMSE) 121 for estimating the signal received by the receiving end 120. The relay terminal 130 is disposed, for example, between the transmitting end 110 and the receiving end 120 for receiving the signal transmitted by the transmitting end 110 and transmitting the signal to the receiving end 120. The training sequence setting unit 140 is configured to set an optimal training sequence for transmitting signals according to the estimation result estimated by the linear least square error estimator 121, the channel correlation coefficient, the correlation noise coefficient, and the virtual abnormal signal.

As shown in FIG. 1, the relay terminal 130 of this embodiment can be used to improve signal transmission between the transmitting end 110 and the receiving end 120. For example, the relay end 130 can amplify the received signal and directly transmit it to the receiving end 120 ( Amplify-and-forward (AF); or the relay 130 can decode the received signal and re-encode it and transmit it to the receiver-and-forward (DF); for example, the relay 130 can receive the received signal The signal is compressed and then transmitted to the receiving end 120 (compress-and-forward, CF).

As shown in FIG. 1, the training sequence setting unit 140 of this embodiment is, for example, a central processing unit (CPU), a programmable controller (PLC), a single-chip microprocessor (MCU), or other processing unit, which can be built in The receiving end 1200 or the receiving end 120 or the system is used to set an optimal training sequence for transmitting signals, thereby ensuring system performance and detection robustness (Robust).

Referring to FIG. 2, a system architecture diagram of a cooperative communication system in accordance with an embodiment of the present invention is shown. In this embodiment, the cooperative communication system includes two-stage signal transmission, the first stage is the transmitting end 110 to the relay end 130, and the second stage is the relay end 130 to the receiving end 120, and the direct receiving path is not considered. (Direct path). As shown in Figure 2, the phase relationship between the first phase and the second phase is symbolized by with To represent. In the first phase, the noise received by the relay 130 is related to To represent:

Where g and h are respectively additive white Gaussian noises, n _r =[n _r1 ... n _{r M} ] ^H is additive white Gaussian noise. Σ _g = R ^{M × M} and Σ _h = R ^{M × M} is the channel correlation coefficient, Σ _n = R ^{M × M} is the noise correlation coefficient.

The signal received by each relay 130 at each time point is:

The signal received by the receiving end 120 is represented by the following formula:

Here, it is assumed that the training sequence S has a length of N and is known at the receiving end 120.

Then, the signal received at the receiving end 120 is subjected to signal estimation, which is performed by the linear least squares error estimator 121:

Then the estimated result can be expressed as:

Next, consider the two scenarios and use the minimum mean square error rule (Mean Square Error) for training sequence design. First, consider the existence of channel-related and noise-related situations in cooperative communication systems:

Since R _h and R _n respectively contain the total of the product of the channel correlation coefficients and the sum of the correlation channels and the relevant noise coefficients. In this case, there is a large interference effect compared to the independent channel. It can be seen that the training sequence in channel-related and noise-related situations needs to have more transmission energy to resist interference and reduce the mean square error method compared to independent channels and independent noise.

In another case, an additional situation in which the relay terminal 130 suddenly violates a behavior or a malicious attack is added. In this case, the received signal can be expressed by the following formula:

After the estimated results of the estimator:

Finally, the mean square error rule can be used:

Where F is the average signal sent by the abnormal relay terminal 130:

In addition, with The sum of the average squared difference of the noise and the correlation coefficient of the correct channel:

In addition, the sum of the correlation coefficients for all channels and the correct channel:

Here, two training sequences are proposed, which can be used to design the best and second best training sequences.

First, it can be found from equation (9) that to minimize the mean squared error, it is equivalent to minimizing (s ^H ( +F) s), and s ^H s must be a certain value. Therefore, it can be expressed as the following optimal expression:

Then, use the standard Lagrange function to represent:

And differentiate this function:

Therefore, the optimal training sequence S is the feature vector to which the minimum eigenvalue of the matrix A corresponds.

The second method is a suboptimal solution, which can be further derived according to formula (13):

It can be seen from the above equation that the minimum average square error is obtained as the sum of the minimum brackets.

Referring to FIG. 3, an experimental simulation diagram of a cooperative communication system in accordance with an embodiment of the present invention is shown. Assume that the training sequence length N is 5, and two of the three relay points 130 are malicious relays, which send a 'zero' malicious attack signal (virtual abnormal signal) f ^H =[0,0,0 , 0,0].

As shown in FIG. 3, the optimal training sequence design of this embodiment can be superior to the sub-optimal training sequence.

Referring to FIG. 4, a flow chart of a method for designing a training sequence of a cooperative communication system according to an embodiment of the present invention is shown. When the training sequence design method of the cooperative communication system of the present embodiment is performed, first, the linear least squares error estimator 121 is used to estimate the signal transmitted by the transmitting terminal 110 (step 201). Next, the channel correlation coefficient of the system and the associated noise coefficients are obtained (step 202). Next, a virtual abnormality signal is set (step 203). Then, the training sequence setting unit 140 can set the optimal training sequence for transmitting the signal according to the estimation result estimated by the linear least square error estimator 121, the channel correlation coefficient, the correlation noise coefficient, and the virtual abnormal signal (steps). 204).

As described above, the cooperative communication system and the training sequence design method of the present invention can provide an optimal training sequence design, which can effectively resist the influence of interference when the interference affects the detection result, and reduce the system error rate to improve The strength of the cooperative communication system and the average squared error of the channel estimation can be minimized.

The present invention has been disclosed in its preferred embodiments, and is not intended to limit the invention, and the present invention may be modified and modified without departing from the spirit and scope of the invention. The scope of protection is subject to the definition of the scope of the patent application.

110. . . Transmitter

120. . . Receiving end

121. . . Linear least squares error estimator

130. . . Relay side

140. . . Training sequence setting unit

S201. . . Estimate the signal transmitted by the transmitter

S202. . . Obtain channel correlation coefficient and related noise coefficient

S203. . . Set virtual abnormal signal

S204. . . Set the optimal training sequence based on the estimated results, channel correlation coefficients, associated noise coefficients, and virtual anomalies

1 shows a system block diagram of a cooperative communication system in accordance with an embodiment of the present invention.

2 shows a system architecture diagram of a cooperative communication system in accordance with an embodiment of the present invention.

3 shows an experimental simulation diagram of a cooperative communication system in accordance with an embodiment of the present invention.

4 is a flow chart showing a method of designing a training sequence of a cooperative communication system in accordance with an embodiment of the present invention.

110. . . Transmitter

120. . . Receiving end

121. . . Linear least squares error estimator

130. . . Relay side

140. . . Training sequence setting unit

Claims (6)

A cooperative communication system includes: at least one transmitting end for transmitting a signal; and at least one receiving end for receiving the signal, wherein the receiving end is provided with a linear minimum mean square estimator (LMMSE) For estimating the signal; a plurality of relay terminals are disposed between the transmitting end and the receiving end for receiving the signal transmitted by the transmitting end and transmitting the signal to the receiving end; and a training sequence setting unit configured to set an optimal training of the signal according to an estimated result estimated by the linear least square error estimator, a channel correlation coefficient, a correlated noise coefficient, and a virtual abnormal signal sequence. The cooperative communication system according to claim 1, wherein the relays amplify the received signal and directly transmit the signal to the receiving end. The cooperative communication system according to claim 1, wherein the relays decode the received signal and re-encode the signal to the receiving end. The cooperative communication system according to claim 1, wherein the relays compress the received signals and transmit the signals to the receiving end. A training sequence design method for a cooperative communication system, wherein the cooperative communication system includes at least one transmitting end, at least one receiving end, and a plurality of repeating ends, the method comprising the steps of: using a linear least square error estimator Estimating the signal transmitted by the transmitting end; obtaining a channel correlation coefficient and a correlated noise coefficient; setting a virtual abnormal signal; and estimating the estimated result according to the linear least square error estimator The correlation coefficient, the correlation noise coefficient and the virtual abnormal signal are used to set an optimal training sequence of the signal. The method of claim 5, wherein the step of setting the optimal training sequence comprises: minimizing an average squared error of the cooperative communication system.