CN111555787B - Artificial noise weight iterative correction and low bit feedback method for multi-transmitting single-receiving system - Google Patents
Artificial noise weight iterative correction and low bit feedback method for multi-transmitting single-receiving system Download PDFInfo
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- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
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- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
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Abstract
The invention discloses an artificial noise weight iteration correction and low bit feedback method of a multi-transmitting-single-receiving system, under a TDD communication mode, an N-antenna sender Alice obtains an erroneous channel estimation value at an access time slotGenerating an initial main beam weight w0And the artificial noise weight q0,i. And the receiving end Bob calculates error data Er after receiving the signal containing the artificial noise, and feeds back the result after quantizing. After receiving the data, the Alice terminal carries out comparison on the main beam weight w and the artificial noise weight qi(i 1.., N-1) is updated and transmission and error feedback for the next slot is performed. After a certain number of iterations, the originally unmatched weights are corrected to the actual channel response. The invention can realize the function of weight correction by using a small number of return bits in each uplink time slot under the condition of not changing the existing TDD communication mode and not using additional equipment, has the advantage of low complexity and can meet the real-time requirement of communication.
Description
Technical Field
The invention belongs to the field of wireless communication, and particularly relates to an artificial noise weight iterative correction and low bit feedback method for a multi-transmitting and single-receiving system.
Background
With the development of wireless communication technology and the popularization of intelligent terminal equipment, people pay more attention to the information security problem in the wireless communication process. The wireless communication signals are easy to intercept and steal due to natural openness and boundless, and are one of the sources of information leakage problems. Therefore, how to ensure the effectiveness and reliability of communication without the help of an upper layer protocol encryption means becomes a first problem to solve the potential safety hazard. In view of this, it is critical to research the secure transmission of information in the physical layer, and a physical layer secure transmission technology that is a powerful supplement to the conventional encryption technology has also gained wide attention.
For a traditional Multiple Input Single Output (MISO) system, a widely accepted zero-space artificial noise scheme is an effective wireless physical layer secure transmission method. The null space artificial noise scheme requires the originator to transmit useful signals carrying secret information in the main channel direction, while uniformly transmitting artificial noise signals in the null space of the main channel. Artificially introducing a gap in transmission performance between legitimate and illegitimate channels at the cost of reducing the power utilization of the transmitting end.
However, in an actual TDD system, since the result of channel estimation is developed based on channel reciprocity, the uplink end estimates the uplink channel using the received signal, and at the same time, uses the estimated value of the uplink channel as the estimation result of the downlink channel. Due to the fact that estimation is inaccurate, uplink and downlink channels are not completely reciprocal, errors between channels exist in practical systems, and the like, the difference between a channel estimation result and real channel response exists. For the main lobe signal, such an error is not critical, and the signal gain in the main lobe direction is still guaranteed. However, for the artificial noise scheme, the transmission using the zero space weight generated by the channel estimation result with error introduces noise in the direction of the legitimate user. Due to the characteristics of artificial noise nulling, the additionally introduced noise can have a significant effect on the original characteristics.
The traditional engineering scheme is based on channel calibration expansion, and aims to correct errors among multiple antenna receiving and transmitting channels to meet the condition of channel reciprocity so as to enable a channel estimation result to be close to the real response of a channel. However, the traditional offline and online calibration, wired and wireless calibration, require additional equipment and a more cumbersome processing procedure in terms of implementation, and the calibration accuracy is limited by the accuracy of the existing equipment, which is difficult to reach a high level, and even impossible to process the estimation error and slow channel change influence except the inter-channel error, and it is difficult to ensure that the artificial noise does not affect the information transmission in the legal user direction.
The above facts indicate that in practical communication engineering, a method for correcting the artificial noise weight of the MISO system, which is really simple, effective and meets practical requirements, is still lacking at present.
Disclosure of Invention
The invention aims to solve the problems in the prior art, and provides a transmitting-end distributed beam weight iteration and low-bit feedback method, which can realize transmitting weight correction in a single-parameter feedback iteration mode on the premise of not using additional equipment and communication time slots, and provides a low-bit quantization feedback scheme to enhance the safe transmission performance of artificial noise.
In order to achieve the above purpose, the method for iteration of the transmit-side distributed beam weight and low-bit feedback of the invention comprises the following steps:
And 2, after the single-antenna receiving end Bob contains artificial noise signals at the receiving end, calculating the error between the received signal and the known signal according to the known pilot signal, and carrying out differential quantization on the error. And feeding back the quantized result to the Alice terminal.
And 3, using the received data to obtain a current error value by the Alice of the N antenna sender, correcting the weight of the main beam according to the error value, and updating the main beam and the artificial noise beam according to the corrected result. And using the updated weight value to continuously send the signal of the next time slot, and going to the step 2.
The communication system based on the weight correction method comprises an N-antenna sender Alice and a single-antenna expected receiver Bob, which form a communication pair through access. In TDD communication mode, the N-antenna sender Alice sends a signal containing artificial noise, and the signal received at the single-antenna receiver Bob can be represented asWhere s (t) represents the carrier of a known signal for training, yi(t) represents the standard Gaussian distribution of the artificial noise signal with mean value of zero and energy of 1, sigmaiIs ith artificial noise yi(t) complex amplitude, h is the true response of the channel, w is the main beam transmitting the desired signal, and initially the channel estimateNamely, it isqiIs the ith artificial noise weight, which is taken from the null space of the current main beam weightIt may be represented again as qi=U0(: i), n (t) is environmental noise. Under the line-of-sight environment, the channel true response h is considered to remain unchanged in the process of iterative convergence.
The step 1 is to use the channel estimation value in the access time slotGenerating an initial value w of the main beam0And accordingly generates a null space omega0To obtain the weight q of the artificial noiseiConsistent with conventional artificial noise generation schemes.
The step 2 is that the receiving end Bob generates the return error quantization bit according to the known signal when receiving the signal, and the specific operation steps are as follows:
step 2.1, the single-antenna receiver Bob receives a pilot signal containing artificial noise from the Alice terminal, and the received signal isThe useful signal s (t) is completely known to Bob, from which the error term e (t) in the received signal can be derivedk) X (t) -s (t). Is not difficult to obtain according to the expression of the received signalHere Λ0=diag(σ1,σ2,..,σN-1) And y (t) ═ y1(t),y2(t)...,yN-1(t))。
Suppose there is a known signal s (t) under a certain time slotk) And error term e (t)k) And calculating the cross-correlation value Er of the known signal and the error term at the momentk=E{s(tk)e(tk)*And applying a useful signal s (t) theretok) The energy of (a) is normalized.
Step 2.2, the normalized complex number ErkRespectively carrying out Q-format quantization on the real parts and the imaginary parts, and carrying out L-bit truncation on the quantized bit sequences. L represents the effective bit length of the real part or the imaginary part, without including the sign bit, and the specific value depends on the introduced noise and the environmental signal-to-noise ratio SNR. According to the rough calculation result of the quantization length and the equivalent quantization noise, when L is more than SNR/6, the introduced quantization noise is considered to be lower than the environment, and has no influence on the subsequent convergence performance.
The error bit sequence after the real part/imaginary part truncation is Ek[l]Bit sequence E from the previous instantk-1[l]And the bit sequence obtained by the difference is Dk[l]. Due to the convergent nature of the algorithm, the high-order number of the differential bit will quickly become 0 during the iteration and will not change during subsequent iterations. If the significant digit of the differential bit sequence is M bits in the lower order, the M bits are intercepted and transmitted. M selection rule according to error Er of initial weight0Determining the maximum representation d of the last M digitsmaxTo be reacted with Er0And (4) the equivalent. And for the direct sequence taking of the differential data with the expression range M after exceeding, the sequence is obtained when the differential data is transmitted back again. For the sequence of the differential data beyond the M-bit expression range, splitting is carried out according to the following rule, the feedback is carried out in sequence in a plurality of time slots, and no additional calculation and quantization are carried out in the process of multiple feedback:
when the real part or imaginary part data value of a certain returned difference sequence is larger than the maximum value d expressed by the M rear bitsmaxDividing the larger Q into Q ═ n × dmax+ q, wherein q is a number that can be expressed with the last M. In the process of returning later, n times of returning M-bit full 1 sequences and sequences corresponding to 1 time of transmission q occupy n +1 times of returning, so that the processing of the receiving end on the differential numerical value is always kept in addition operation. And the other side of the real part and the imaginary part is split in the same way, and 0 is supplemented for transmission.
It is noted that, since the all-1 sequence has a special meaning in degree, when the error data just corresponds to the all-1 sequence and does not exceed the expression range, the end bit of the corresponding differential sequence is modified to 0.
And 2.3, the single-antenna receiver Bob transmits the generated real-imaginary part differential bit sequence back through the uplink time slot.
And 3, after the N-antenna sender Alice receives the differential bit sequence of the Bob end, error data Er is obtainedkAnd calculating the main beam weight and the artificial noise beam weight of the next time slot according to the calculation result, wherein the specific operation steps are as follows:
step 3.1, the sender Alice of the N antenna calculates a difference result delta according to the received difference bits under the premise that the sender Alice of the N antenna intercepts M bits after the known L bit difference is quantizedkAnd accumulating error data Er, i.e. Erk=Erk-1+Δk。
At this time, different operations are taken according to different received differential bits: if the received bit sequence contains the all 1 sequence, turning to step 3.3, namely not updating the weight; if the received bit sequence does not contain all 1 bit, go to step 3.2, i.e. modify the weight.
Step 3.2, the receiving end obtains the error value Er at the moment according to the feedback bitkThen, the original beam forming weight value is updated and calculatedWherein wkAs a weight of the current beam forming, wk+1For the updated weight, μ is the iteration step, U0,kIs the null space of the current weight, i.e. the current artificial noise weight space, Λ0=diag(σ1,σ2,..,σN-1) For the energy allocation of artifacts, y (t) ═ y1(t),y2(t)...,yN-1(t)) are each artificial noise sequence. After updating the main beam weight wk+1Thereafter, a null space U of responses is also generated0,k+1And updating the artificial noise weights of all paths and turning to the step 3.3.
Step 3.3, according to the main beam weight w and the artificial noise weight U0And transmitting the signal of the next time slot. And (5) carrying out communication of the next time slot, and turning to the step (2) to carry out iterative correction on the weight.
Compared with the prior art, the invention has the following advantages: the calculation complexity is low, and the real-time requirement of communication can be met in actual use; the time slot design of the main stream communication is matched, and under the traditional TDD time slot communication structure, additional time frequency code domain resources are not occupied; the design starts from the background of artificial noise, fully utilizes the airspace resources of the multi-antenna, fully plays the role of multi-beam, can cover pilot frequency time slot by the artificial noise, and enhances the safety performance. The invention can overcome the influence of channel mismatching by using the minimum resources and optimize the performance of the artificial noise beam without changing the traditional TDD communication framework.
Drawings
FIG. 1 is a schematic diagram of an artificial noise weight iterative correction process under MISO time division communication
FIG. 2 is a flow chart of the differential quantization method of the present invention
FIG. 3 is a convergence curve of SINR output by the receiving end Bob with iteration number under given conditions
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
As shown in fig. 1, the communication system adopted by the present invention includes an N-antenna sender Alice and a single-antenna intended receiver Bob, the dual-transmission time-division uplink and downlink communication is performed according to the TDD communication method, and the pilot sequences of the Bob end and the Alice end at the front end of the dual-transmission time slot are completely known.
In TDD communication mode, the N-antenna sender Alice sends a signal containing artificial noise, and the signal received at the single-antenna receiver Bob can be represented asWhere s (t) represents the carrier of a known signal for training, yi(t) represents the standard Gaussian distribution of the artificial noise signal with mean value of zero and energy of 1, sigmaiIs ith artificial noise yi(t) complex amplitude, h is the true response of the channel, w is the main beam transmitting the desired signal, and initially the channel estimateqiIs the ith artificial noise weight, which is taken from the null space of the current main beam weightIt may be represented again as qi=U0(: i), n (t) is environmental noise.
And 3, completing the generation of the initial weight in the step 1, wherein the generation is consistent with the artificial noise weight generation method in the traditional method.
In the process of downlink communication, a single-antenna receiving end Bob receives the signalAfter the signal, the return error quantization bit is generated according to the known signal. A single-antenna receiver Bob receives a pilot signal containing artificial noise from an Alice terminal, and the received signal isNow, Bob is completely known about the useful signal s (t), and thus the error term e (t) in the received signal can be obtainedk) X (t) -s (t). The operation steps of calculating the error value and the differential quantization are as follows:
step 2.1, assume that there is a known signal s (t) in each communicationk) And error term e (t)k) And calculating the cross-correlation value Er of the known signal and the error term at the momentk=E{s(tk)e(tk)*And applying a useful signal s (t) theretok) The energy of (a) is normalized.
Step 2.2, the normalized complex number ErkRespectively carrying out Q-format quantization on the real parts and the imaginary parts, and carrying out L-bit truncation on the quantized bit sequences. L represents the effective bit length of the real part or the imaginary part, without including the sign bit, and the specific value depends on the introduced noise and the environmental signal-to-noise ratio SNR. According to the rough calculation result of the quantization length and the equivalent quantization noise, when L is more than SNR/6, the introduced quantization noise is considered to be lower than the environment, and has no influence on the subsequent convergence performance.
The error bit sequence after the real part or the imaginary part is truncated is Ek[l]Bit sequence E from the previous instantk-1[l]And the bit sequence obtained by the difference is Dk[l]. Due to the convergent nature of the algorithm, the high-order number of the differential bit will quickly become 0 during the iteration and will not change during subsequent iterations. If the significant digit of the differential bit sequence is M bits in the lower order, the M bits are intercepted and transmitted. M selection rule according to error Er of initial weight0Determining the maximum representation d of the last M digitsmaxTo be reacted with Er0And (4) the equivalent. And when the differential data is a direct sequence taking the expression range M after exceeding, returning. Wherein when the error data just corresponds to the full 1 sequence and does not exceed the expression range, the error data will beThe last bit of the corresponding differential sequence is modified to be 0. For the sequence of the differential data beyond the M-bit expression range, splitting is carried out according to the following rule, the feedback is carried out in sequence in a plurality of time slots, and no additional calculation and quantization are carried out in the process of multiple feedback:
when the real part or imaginary part data value of a certain returned difference sequence is larger than the maximum value d expressed by the M rear bitsmaxDividing the larger Q into Q ═ n × dmax+ q, wherein q is a number that can be expressed with the last M. In the process of returning later, n times of returning M-bit full 1 sequences and sequences corresponding to 1 time of transmission q occupy n +1 times of returning, so that the processing of the receiving end on the differential numerical value is always kept in addition operation. And the other side of the real part and the imaginary part is split in the same way, and 0 is supplemented for transmission.
And 2.3, the single-antenna receiver Bob transmits the generated differential bit sequence of the real part and the imaginary part back through the uplink time slot.
In the process of uplink communication, after receiving error differential bits fed back by the Bob end, the N-antenna sender Alice sends error data ErkAnd accumulating and calculating the main beam weight and the artificial noise beam weight of the next time slot according to the accumulated values. The specific operation steps of accumulating error data and updating weight are as follows:
step 3.1, the sender Alice of the N antenna calculates a difference result delta according to the received difference bits under the premise that the sender Alice of the N antenna intercepts M bits after the known L bit difference is quantizedkAnd accumulating error data Er, i.e. Erk=Erk-1+Δk。
At this time, different operations are taken according to different received differential bits: if the received bit sequence contains the all 1 sequence, turning to step 3.3, namely not updating the weight; if the received bit sequence does not contain all 1 bit, go to step 3.2, i.e. modify the weight.
Step 3.2, the receiving end obtains the error value Er at the moment according to the feedback bitkThen, the original beam forming weight value is updated and calculatedWherein wkAs a weight of the current beam forming, wk+1For the updated weight, μ is the iteration step, U0,kIs the null space of the current weight, i.e. the current artificial noise weight space, Λ0=diag(σ1,σ2,..,σN-1) For the energy allocation of artifacts, y (t) ═ y1(t),y2(t)...,yN-1(t)) are each artificial noise sequence. After updating the main beam weight wk+1Thereafter, a null space U of responses is also generated0,k+1And updating the artificial noise weights of all paths and turning to the step 3.3.
Step 3.3, according to the main beam weight w and the artificial noise weight U0And transmitting the signal of the next time slot.
It can be seen that the iterative process of the algorithm is consistent with the uplink and downlink transmission mode, no convergence condition needs to be additionally set, and the method has a tracking effect on slowly-varying channels in the continuous correction process. Channel estimation value by simulation methodAnd a gain error of 10 percent and a phase error of 5 degrees exist between the signal and the real response h of the channel, and the optimization performance is realized under the condition that the environmental signal-to-noise ratio is 30 dB. Wherein, the length of each frame pilot frequency is 127bit, the length of the truncation is 6bit, the length of the difference is 3bit, so the length of each feedback data is 8 bit. The original artificial noise performance can only be about 20dB of signal-to-interference-and-noise ratio at the output end.
As can be seen from fig. 3, under the above conditions, the method of the present invention is used to modify the artificial noise weight, so that the signal-to-interference-and-noise ratio output by the Bob end is within the signal-to-noise ratio of the convergence value environment after a finite number of iterations, i.e., the transmission artificial noise does not affect the communication performance of the legal receiving end, and the cost is that each time slot occupies 8 backhaul bits.
In summary, the effective role of the method in correcting the artificial noise weight value and optimizing the transmission performance can be verified from the theoretical analysis and simulation results of the technical scheme.
The foregoing is only a preferred embodiment of the invention and is not intended to be limiting in any way, as it will be appreciated by those skilled in the art that changes may be made in this invention without departing from the principles and spirit of the invention, which is defined in the appended claims.
Claims (5)
1. An artificial noise weight iteration correction and low bit feedback method of a multi-transmitter-receiver system is characterized by comprising the following steps:
step 1, an N-antenna sender Alice establishes a communication link with a single-antenna receiver Bob according to access information and obtains an initial channel estimation result by receiving an uplink pilot signalUnder the MISO line-of-sight model, the channel is considered to be slowly changed, and the channel estimation valueGenerating a main beam weight w and N-1 groups of artificial noise weights q for an Nx1 dimensional column vector according to the existing informationi(i 1.., N-1), and when transmitting a signal, simultaneously sending artificial noise to protect a useful signal;
step 2, after receiving the signal containing the artificial noise, the single-antenna receiving end Bob calculates the error between the received signal and the known signal according to the known pilot signal, performs differential quantization on the error, and feeds back the quantized result to the Alice end;
and 3, using the received data to obtain a current error value by the Alice of the N-antenna sender, correcting the weight of the main beam according to the error value, updating the main beam and the artificial noise beam according to the corrected result, and using the updated weight to continuously send a signal of the next time slot.
2. The artificial noise weight iterative correction and low bit feedback method for multi-transmission single-reception system according to claim 1, wherein: the communication system comprises an N-antenna sender Alice and a single-antenna receiver Bob;
in TDD communication mode, the N-antenna sender Alice sends a signal containing artificial noise, and the signal received at the single-antenna receiver Bob can be represented asWhere t denotes the signal time, s (t) denotes the time at which the known signal is carried for training, yi(t) represents an artificial noise signal and obeys a standard Gaussian distribution with mean zero and energy of 1, σiIs ith artificial noise yi(t) complex amplitude, h is the true channel response, w is the primary beam weight, and initially is the channel estimateNamely, it isqiThe beam weight of ith artificial noise is taken from the null space of the current main beam weightWherein U is0Is a matrix of orthogonal weights, then the beam weight can be represented as qi=U0And (i), n (t) is environmental noise, and in a line-of-sight environment, the real response h of the channel is considered to be kept unchanged in the iterative convergence process.
3. The artificial noise weight iterative correction and low bit feedback method for multi-transmission single-reception system according to claim 1, wherein: in step 2 and step 3, the Alice end corrects the weight value by feeding back the error, and the Bob end can sufficiently feed back the error information by using a small number of bits.
4. The iterative artificial noise weight correction and low bit feedback method according to claim 3, wherein the method for correcting the weight by feeding back the error data comprises the following steps:
step 2.1, the single-antenna receiving end Bob receives a pilot signal containing artificial noise from the Alice end, and the received signal isWhere t denotes the signal time, s (t) denotes the time at which the known signal is carried for training, yi(t) represents an artificial noise signal and obeys a standard Gaussian distribution with mean zero and energy of 1, σiIs ith artificial noise yi(t) complex amplitude, h is the channel true response, w is the main beam weight, qiFor the ith artificial noise weight, n (t) is the ambient noise, and for Bob, the useful signal s (t) is completely known, and in the kth pilot frequency transceiving process, t is usedkIndicating the signal moment in the transmission using wkThe signal weight used by the Alice terminal in the process is shown, so that the signal error e (t) in the k pilot frequency receiving process can be obtainedk)=x(tk)-s(tk) The received signal isWherein n isq(tk) Representing equivalent quantization noise introduced by quantization, n0(tk) Representing ambient noise, here Λ0=diag(σ1,σ2,..,σN-1) And y (t) ═ y1(t),y2(t)...,yN-1(t));
Suppose there is a known signal s (t) under a certain time slotk) And error term e (t)k) And calculating the cross-correlation value Er of the known signal and the error term at the momentk=E{s(tk)e(tk)*And applying a useful signal s (t) theretok) Normalizing the energy, and feeding the error data back to an Alice end;
step 3.2, the Alice end obtains the error value Er at the moment according to the feedback bitkThen, the original beam forming weight value is updated and calculatedWherein wkAs a weight of the current beam forming, wk+1For the updated weight, μ is the iteration step, U0,kIs the null space of the current weight, i.e. the current artificial noise weight space, Λ0=diag(σ1,σ2,..,σN-1) For the energy allocation of artifacts, y (t) ═ y1(t),y2(t)...,yN-1(t)) is the artificial noise sequence of each path, and the main beam weight w is updated after the updatingk+1Thereafter, a null space U of responses is also generated0,k+1。
5. The method for iterative modification of artificial noise weight and low bit feedback in a multi-transmission single-reception system according to claim 3, wherein the error information is transmitted through a small number of bits, comprising the steps of:
step 2.2, cross-correlation value Er of the known signal and the error signalkDivided by the useful signal s (t)k) Normalizing the energy, respectively carrying out Q-format quantization on real parts and imaginary parts of the result, carrying out L-bit truncation on a quantized bit sequence, wherein L represents the real part or the imaginary part and is under the condition of not including a sign bit, the obtained effective bit length specifically takes a value depending on introduced noise and an environment signal-to-noise ratio (SNR), and when L is the rough calculation result of the quantization length and equivalent quantization noise, when L is the rough calculation result of the quantization length and the equivalent quantization noise>At SNR/6, the introduced quantization noise is considered to be lower than the environment and has no influence on the subsequent convergence performance;
real/imaginary truncated error bit sequence Ek[l]Bit sequence E with previous time instantk-1[l]The bit sequence obtained by the difference is Dk[l]After interception, M bits are transmitted, and the selection rule of M is according to the error Er of the initial weight0Determining the maximum representation d of the last M digitsmaxTo be greater than or equal to Er0If the differential data is not greater than d during transmissionmaxThen directly converting into a bit sequence, and only needing to transmit back once; if the difference data is larger than dmaxSplitting is carried out according to the following rules, feedback is carried out in sequence in a plurality of time slots, and no additional calculation and quantification are carried out in the process of multiple feedback:
when the real part or imaginary part data value of a certain returned difference sequence is larger than the maximum value d expressed by the M rear bitsmaxDividing the larger Q into Q ═ n × dmax+ q, wherein q is a numerical value capable of being expressed by the rear M bit, in the process of returning, n times of returning M bit full 1 sequence and 1 time of transmitting q corresponding sequence occupy n +1 times of returning, so that the Alice end always keeps addition operation for processing difference value, and the other side of real and imaginary parts is split in the same way and is transmitted by complementing 0;
it is worth noting that because the all-1 sequence has a special meaning in the times, when the error data just corresponds to the all-1 sequence and does not exceed the expression range, the tail bit of the corresponding differential sequence is modified to be 0;
step 3.1, the sender Alice of the N antenna calculates a difference result delta according to the received difference bits under the premise that the sender Alice of the N antenna intercepts M bits after the known L bit difference is quantizedkAnd accumulating error data Er, i.e. Erk=Erk-1+Δk;
At this time, different operations are taken according to different received differential bits: if the received bit sequence contains the all-1 sequence, the weight is not updated, and the current transmission weight is maintained for the next pilot frequency transmission; if the received bit sequence does not contain all 1 bit, an error value is obtained according to the receiving result, the weight value is corrected by using the weight value correction method in claim 4, and the next pilot frequency transmission is performed according to the corrected weight value.
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105915472A (en) * | 2016-05-20 | 2016-08-31 | 电子科技大学 | Artificial noise-based cooperative network power allocation method for main channel and cooperative channel under non ideal channel estimation condition |
CN106817158A (en) * | 2017-01-09 | 2017-06-09 | 南京理工大学 | A kind of sane error burst integration direction modulation synthetic method of self adaptation |
CN108337029A (en) * | 2017-12-29 | 2018-07-27 | 南京理工大学 | Adaptive steady kernel projected beam shaping method in secure wireless transmission |
CN110650479A (en) * | 2019-09-12 | 2020-01-03 | 中国人民解放军战略支援部队信息工程大学 | Robust physical layer secure transmission method and device in heterogeneous energy-carrying communication network |
CN110798282A (en) * | 2019-10-28 | 2020-02-14 | 哈尔滨工业大学 | Software radio-based artificial noise assisted MISO system verification platform implementation method |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
AU2002359956A1 (en) * | 2002-12-31 | 2004-07-22 | Zte Corporation | Smart antenna, method and device for forming |
CN107437963B (en) * | 2017-07-05 | 2020-10-20 | 深圳大学 | Distributed safe beam forming method and device based on feedback control |
CN109194378B (en) * | 2018-08-06 | 2021-07-13 | 重庆邮电大学 | Physical layer safety wave beam shaping method based on linear neural network |
-
2020
- 2020-04-24 CN CN202010333794.9A patent/CN111555787B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105915472A (en) * | 2016-05-20 | 2016-08-31 | 电子科技大学 | Artificial noise-based cooperative network power allocation method for main channel and cooperative channel under non ideal channel estimation condition |
CN106817158A (en) * | 2017-01-09 | 2017-06-09 | 南京理工大学 | A kind of sane error burst integration direction modulation synthetic method of self adaptation |
CN108337029A (en) * | 2017-12-29 | 2018-07-27 | 南京理工大学 | Adaptive steady kernel projected beam shaping method in secure wireless transmission |
CN110650479A (en) * | 2019-09-12 | 2020-01-03 | 中国人民解放军战略支援部队信息工程大学 | Robust physical layer secure transmission method and device in heterogeneous energy-carrying communication network |
CN110798282A (en) * | 2019-10-28 | 2020-02-14 | 哈尔滨工业大学 | Software radio-based artificial noise assisted MISO system verification platform implementation method |
Non-Patent Citations (4)
Title |
---|
Artificial-Noise-Aided Zero-Forcing Synthesis Approach for Secure Multi-Beam Directional Modulation;Tao Xie et al.;《IEEE Communications Letters》;20171110;第22卷(第2期);第1-4页 * |
Secure MISO Wiretap Channels With Multiantenna Passive Eavesdropper: Artificial Noise vs. Artificial Fast Fading;Hui-Ming Wang et al.;《IEEE Transactions on Wireless Communications》;20140620;第14卷(第1期);第1-13页 * |
人工噪声辅助安全传输中的反馈比特数研究;王啸;《信号处理》;20161025;第32卷(第10期);第1-8页 * |
无线携能通信***中基于人工噪声的波束成形算法研究;许魁丽;《计算机应用研究》;20171130;第34卷(第11期);第1-4页 * |
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