CN105577591B - Cross-layer serial interference delet method based on full-duplex communication in a kind of heterogeneous network - Google Patents

Abstract

The invention discloses a full-duplex communication-based cross-layer serial interference deletion method in a heterogeneous network, belonging to the technical field of wireless communication. The method includes obtaining full-duplex micro base station information, micro base station verifying the feasibility of serial interference cancellation, micro base station calculating the weighted value of transmitted signals, micro base station sending weighted training signals to micro users, judging the feasibility of fSICIC and giving feedback The adjustment information and weights are adjusted by the micro base station to transmit signals according to the received adjustment information and weights. The full-duplex-based serial interference cancellation technology proposed by the present invention only requires each micro base station to complete independently, without the cooperation of macro base stations, and can effectively improve the performance of micro users without reducing the performance of macro users. Compared with the existing fICIC technology, the proposed method can more effectively eliminate strong interference; compared with the existing SIC technology in half-duplex mode, the proposed method has a wider range of applicable scenarios.

Description

A Cross-Layer Serial Interference Cancellation Method Based on Full-duplex Communication in Heterogeneous Networks

technical field

The invention relates to a cross-layer serial interference deletion technology based on full-duplex communication in a heterogeneous network, and belongs to the technical field of wireless communication.

Background technique

By deploying different types of low-power small base stations, such as micro base stations (Micro BSs) and pico base stations (Pico BSs), in a traditional homogeneous network composed of macro base stations (BSs), the heterogeneous network can Significantly improve the capacity and network coverage quality of the cellular system. For the convenience of expression, the low-power small base stations are collectively referred to as micro base stations hereinafter, and the users served by them are referred to as micro users. Compared with the traditional homogeneous network, there is more complex inter-cell interference in the heterogeneous network, especially the high-power macro base station will generate strong cross-layer interference to the micro-users within its coverage, which seriously limits the performance. Therefore, the effective suppression of cross-layer interference is one of the core issues of the heterogeneous network system (see reference [1]: N.Bhushan, J.Li, D.Malladi, R.Gilmore, D.Brenner, A.Damnjanovic, R.T. Sukhavasi, C. Patel, and S. Geirhofer, “Network densification: the dominant theme for wireless evolution into 5G,” IEEE Commun.Mag., vol.52, no.2, pp.82–89, Feb.2014.) .

Aiming at the problem of cross-layer interference suppression in heterogeneous networks, existing work has proposed some solutions. For example, the long-term evolution system (LTE R10) proposed an enhanced inter-cell interference suppression (eICIC, enhanced inter-cellinterference coordination) technology (see reference [2]: B.Soret, H.Wang, K.I.Pedersen, and C. Rosa, "Multicell cooperation for LTE-advanced heterogeneous network scenarios," IEEE Wireless Commun.Mag., vol.20, no.1, pp.27–34, Feb.2013.), cross-layer possible in both time and frequency domains interference suppression. Among them, the time-domain eICIC technology means that the macro base station remains silent in some subframes, thereby generating almost blank transmission subframes (Almost blank subframes), and the micro base stations and micro users perform data transmission in these non-interfering subframes . The frequency domain eICIC technology means that the macro base station and the micro base station use orthogonal spectrum resources for data transmission, so as to avoid cross-layer interference. eICIC is a low-complexity and easy-to-implement interference coordination technology. However, since both macro base stations and micro base stations can only use part of the time or spectrum resources, the performance of macro users and micro users is greatly limited. In addition to eICIC techniques in the time and frequency domains, cooperative beamforming can be viewed as a space-domain eICIC technique (see reference [3]: C.Yang, S.Han, X.Hou, and A.F.Molisch, " How do wedesign CoMP to achieve its promised potential?” IEEE Wireless Commun.Mag.,vol.20,no.1,pp.67–74,Feb.2013.), but the interference suppression ability of this technology is limited by Acer The number of antennas at the station.

The aforementioned eICIC technologies all avoid interference to micro users in the time, frequency or space domains by controlling the transmission mode of the macro base station. In contrast, reference [4] (S.Han, C.Yang, and P.Chen, "Full duplex assisted inter-cell interference cancellation in heterogeneous networks," IEEETrans.Commun., to appear.) proposed a method based on Full-duplex communication cross-layer interference suppression technology (fICIC, full-duplex assisted ICIC). The basic idea of fICIC is to apply the full-duplex technology to the micro base station, so that the micro base station forwards the intercepted interference signal from the macro base station while sending useful signals to the micro users. By properly designing the weights of the two signals, the fICIC technology can make the interference forwarded by the micro base station reach the micro user, superimpose and cancel the interference directly received by the micro user, thereby achieving the purpose of suppressing cross-layer interference. However, considering the transmission power limitation of the micro base station, fICIC cannot effectively suppress strong cross-layer interference.

Based on eICIC technology and fICIC technology, micro users regard the cross-layer interference received from macro base stations as white Gaussian noise when demodulating data. Serial interference cancellation (SIC, successive interference cancellation) is another common interference suppression method. Based on the SIC technology, the micro-user first estimates the cross-layer interference signal from its received signal, and then deletes the estimated cross-layer interference signal from the received signal, and then solves the desired signal under interference-free conditions. However, because the SIC technology needs to solve the interference signal first, it can only be used in limited scenarios such as low data rate of the interfering user or strong cross-layer interference in the traditional half-duplex system.

Contents of the invention

In order to solve the problems in the prior art, the present invention provides a method for deleting cross-layer serial interference based on full-duplex communication in a heterogeneous network, which includes the following steps:

The first step is to obtain full-duplex micro base station information;

The information includes channels from the macro base station to the micro base station, from the macro base station to the micro user, from the micro base station to the micro user, and the self-interference channel of the full-duplex micro base station, the processing delay of the full-duplex self-interference deletion module of the micro base station, the micro base station The channel propagation delay difference from the macro base station to the micro user, and the modulation and coding method of the interference signal;

In the second step, the femto base station verifies the feasibility of serial interference cancellation:

1) According to the modulation and coding mode of the interference signal, the micro base station calculates the interference signal-to-noise ratio required for demodulation of the interference signal, which is denoted as γ _M ;

2) Under the constraint condition of the maximum transmission power of the micro base station, find the maximum interference signal-to-noise ratio ISNR of the user terminal;

3) Determine the maximum value of ISNR, ISNR _m , and the size of the interference signal-to-noise ratio γ _M required to demodulate the interference signal. If ISNR _m ≥ γ _M , then fSICIC technology is feasible, and enter the third step; otherwise, fSICIC technology is not feasible, Existing eICIC or fICIC methods should be used to suppress cross-layer interference;

In the third step, the micro base station calculates the weighted value of the transmitted signal:

1) The transmitted signal x _s of the micro base station is the weighted sum of the received signal y _s and the useful signal s _s sent to the micro user, expressed as:

where w _I and w _D are the weights of the signal received by the micro base station and the useful signal sent to the micro user, respectively, f is the carrier frequency, and _t1 is the processing delay of the full-duplex self-interference deletion module in the micro base station;

2) Calculation of weight:

Considering the transmission power constraint of the micro base station and the ISNR constraint of solving the interference signal, and taking the SINR maximization of the micro user as the criterion, the optimal weights w _I and w _D are obtained by solving the following problems:

where P _out is the transmit power of the micro base station, t ₂ is the propagation delay from micro base station and macro base station to micro user.

In the following two cases, the optimal weights w _I and w _D are recorded as w _I ^* and w _D ^* respectively, with different values, respectively:

A. When When , the modulus of w _I ^* is |w _I ^* |＝0, and the modulus of w _D ^* is The phase of w _D ^* is 0.

B. When When , the formulas (4a)~(4c) are transformed into:

Substituting (5c) into the objective function (5a), the result is In the formula, A(|w _I |) is the quadratic polynomial of |w _I |, B(|w _I |) is the quartic polynomial of |w _I |, and the constraint condition (5c) is rewritten as c≤|w _I |≤d, where c and d are two constants, obtained from formulas (5c) and (5b); therefore, formulas (5a)~(5c) are simplified as:

stc≤|w _I |≤d. (6b)

Formulas (6a) and (6b) are solved by the dichotomy method; the corresponding |w _I | when the dichotomy method iteratively converges is recorded as the optimal solution of the formulas (5a)~(5c), namely |w _I ^* |; furthermore, Get P _out from formula (5c), and substitute into (4b) to get |w _D ^* |; at the same time, the phase of w _I ^* is The phase of w _D ^* is 0.

In the fourth step, the micro base station sends a weighted training signal to the micro user:

The micro base station transmits to the micro user in two time slots respectively and w _D ^* z, where z is the original training signal known to both the micro base station and the micro user, and w _D ^* are the weights of the training signals sent twice; the micro-user estimates the weighted equivalent channel according to the received weighted interference signal, namely and

In the fifth step, the micro base station sends a signal to the micro user:

The micro base station substitutes the obtained weights w _I ^* and w _D ^* into formula (3), constructs the transmission signal x _s of the micro base station, and sends it to the micro user.

In the sixth step, the micro-user judges the feasibility of fSICIC and feeds back the adjustment information and weight:

Micro-users first calculate the actual interference signal-to-noise ratio, which is denoted as ISNR′, and the calculation formula is as follows:

In the formula, y _u is the received signal of the micro-user, and E{ } represents the calculated mean value.

Then, compare the size of ISNR′ and γ _M : if ISNR′≥γ _M , that is, fSICIC is feasible, then the micro-user feeds back the binary indicator scalar α=1 to the micro-base station; otherwise, fSICIC is not feasible, and the micro-user feeds back α= 0 and the weight w _D ′ of the desired useful signal, where the calculation formula of w _D ′ is as follows:

In the seventh step, the micro base station adjusts the transmission signal according to the received adjustment information and weight:

If α=1, the micro base station continues to send data to the micro user according to the weight calculated in the third step; otherwise, replace the weight w _D ^* calculated in the third step with w _D ', and return to the fourth step.

The advantages of the present invention are:

Aiming at the problem of cross-layer interference suppression in heterogeneous networks, existing eICIC and cooperative beamforming technologies avoid interference to micro users by limiting the transmission of macro base stations in the time, frequency or space domains, which leads to Users can only perform data transmission in part of the time, frequency or space domain, reducing their performance. The full-duplex-based serial interference cancellation technology proposed by the present invention only requires each micro base station to complete independently, without the cooperation of macro base stations, and can effectively improve the performance of micro users without reducing the performance of macro users. Compared with the existing fICIC technology, the proposed method can more effectively eliminate strong interference; compared with the existing SIC technology in half-duplex mode, the proposed method has a wider range of applicable scenarios.

Description of drawings

Fig. 1 is method flowchart of the present invention;

Figure 2 is a general heterogeneous network topology physical model used when modeling fSICIC;

Fig. 3 is the performance simulation result when considering the influence of edge signal-to-noise ratio;

Fig. 4 is the performance simulation result when considering the influence of distance;

Fig. 5 is a performance simulation result considering the influence of channel feedback bits.

Detailed ways

The present invention will be further described in detail with reference to the accompanying drawings and embodiments.

The present invention considers the general heterogeneous network topology physical model shown in Figure 2, and proposes a full-duplex assisted successive inter-cell interference cancellation method (fSICIC, full-duplex assisted successive inter-cell interference cancellation) in a heterogeneous network based on full-duplex communication ), the process shown in Figure 1 includes the following steps:

The first step, full-duplex micro base station information acquisition:

The full-duplex micro base station obtains the channels from the macro base station to the micro base station, from the macro base station to the micro user, from the micro base station to the micro user, as well as the self-interference channel of the full-duplex micro base station, the processing delay of the full-duplex self-interference deletion module of the micro base station, The channel propagation delay difference between the micro base station and the macro base station and the micro user, and the modulation and coding method of the interference signal. Among them, the channel acquisition method from the macro base station to the micro base station can be that the micro base station first receives the downlink training signal broadcast by the macro base station, and then uses the existing channel estimation method to estimate the channel information from the macro base station to the micro base station; The channel acquisition method can be that the micro user first receives the downlink training signal broadcast by the macro base station, and then estimates it using the existing channel estimation method, and then quantizes the estimated channel and feeds it back to the micro base station through the uplink; the micro base station to the micro user The channel acquisition methods can be divided into two cases: For the time division duplex system, the micro base station first receives the uplink training signal sent by the micro user, and then estimates the uplink channel from the micro user to the micro base station, according to the reciprocity of the uplink and downlink channels The estimated uplink channel is the downlink channel from the micro base station to the micro user; for the frequency division duplex system, the micro user first receives the downlink training signal sent by the micro base station, and then estimates the downlink channel from the micro base station to the micro user , and then quantize the estimated channel and feed it back to the micro base station through the uplink; the self-interference channel of the full-duplex base station can be obtained by sending training signals from the micro base station itself; the processing delay of the full-duplex self-interference deletion module of the micro base station can be Measured at the micro base station; the channel propagation delay difference between the micro base station and the macro base station and the micro user can send test signals to the micro user through the micro base station and the macro base station at the same time, and then the micro user measures the arrival time difference of the two test signals and feeds back For the micro base station; the modulation and coding mode of the interference signal can be notified by the macro base station to the micro base station through the backhaul link between the base stations. In the second step, the femto base station verifies the feasibility of serial interference cancellation:

1) According to the modulation and coding method of the interference signal, the micro base station calculates the Interference-to-signal-plus-noise ratio (ISNR) required to demodulate the interference signal according to the existing method, denoted as γ _M .

2) Under the constraints of the maximum transmit power of the micro base station, find the maximum interference signal-to-noise ratio (ISNR) of the user end. The specific process is as follows: the micro-user ISNR maximization problem can be modeled as:

where h _ms , h _su , h _mu are the channels from the macro base station to the micro base station, from the micro base station to the micro user, and from the macro base station to the micro user, respectively, is the weight of the micro base station forwarding the interference signal, is the transmit power of the micro base station, P _s is the maximum transmit power of the micro base station, is the variance of the self-interference channel of the micro base station, is the variance of the noise power.

By solving the optimization problem formulas (1a), (1b) and (1c), the maximum value of ISNR can be obtained as:

In the formula where |w _I ⁺ | is the variable satisfy the equation

A fixed value of , its numerical solution can be obtained by the dichotomy method.

3) Judging the size of ISNR _m and γ _M , if ISNR _m ≥ γ _M , then fSICIC technology is feasible, and enter the third step; otherwise, fSICIC technology is not feasible, and existing eICIC or fICIC methods should be used to suppress cross-layer interference .

In the third step, the micro base station calculates the weighted value of the transmitted signal:

1) The transmitted signal x _s of the micro base station is the weighted sum of the signal y _s received by it and the useful signal s _s sent to the micro user, which can be expressed as:

where w _I and w _D are the weights of the signal received by the micro base station and the useful signal sent to the micro user, respectively, f is the carrier frequency, and t ₁ is the processing delay of the full-duplex self-interference cancellation module in the micro base station.

2) Calculation of weight:

Considering the transmit power constraint of the micro base station and the ISNR constraint of solving the interference signal, the optimal weight w _I and w _D can be obtained by solving the following problem:

where P _out is the transmit power of the micro base station, t ₂ is the propagation delay from micro base station and macro base station to micro user.

In the following two cases, the optimal weights w _I and w _D are recorded as w _I ^* and w _D ^* respectively, with different values, respectively:

A. When When , the modulus of w _I ^* is |w _I ^* |＝0, and the modulus of w _D ^* is The phase of w _D ^* is 0;

B. When When , the optimization problem formulas (4a)~(4c) can be transformed into:

Substituting (5c) into the objective function (5a), the result is In the formula, A(|w _I |) is a quadratic polynomial of |w _I |, B(|w _I |) is a quartic polynomial of |w _I |, and the constraint (5c) can be rewritten as c≤| w _I |≤d, where c and d are two constants, which can be obtained from formulas (5c) and (5b). Therefore, formulas (5a)~(5c) can be simplified as:

stc≤|w _I |≤d. (6b)

Equations (6a) and (6b) can be solved using the dichotomy method. Specific steps are as follows:

a) take Pick where t is any value of |w _I | in its domain;

b) Given Solve the following unary quartic equation:

A(|w _I |)＝(1+λ)B(|w _I |), (7)

The solution of |w _I | is obtained.

c) If there is any solution of |w _I | that can satisfy formula (6b), then let λ _min =λ, otherwise let λ _max =λ.

d) Repeat steps b) to c) until the precision solution requirements are met.

The corresponding |w _I | when the above dichotomy converges iteratively is recorded as the optimal solution of formulas (5a)~(5c), namely |w _I ^* |. Furthermore, P _out can be obtained from formula (5c), and |w _D ^* | can be obtained by substituting it into (4b). Meanwhile, the phase of w _I ^* is The phase of w _D ^* is 0.

In the fourth step, the micro base station sends a weighted training signal to the micro user:

The micro base station transmits to the micro user in two time slots respectively and w _D ^* z, where z is the original training signal known to both the micro base station and the micro user, and w _D ^* are the weights of the training signals sent twice, respectively. According to the weighted interference signal received by the micro-user, the weighted equivalent channel can be estimated, that is, and

In the fifth step, the micro base station sends a signal to the micro user:

The micro base station substitutes the obtained weights w _I ^* and w _D ^* into formula (3), constructs the transmission signal x _s of the micro base station, and sends it to the micro user.

In the sixth step, the micro-user judges the feasibility of fSICIC and feeds back the adjustment information and weight:

Micro-users first calculate the actual interference signal-to-noise ratio, which is denoted as ISNR′, and the calculation formula is as follows:

In the formula, y _u is the received signal of the micro-user, and E{ } represents the calculated mean value.

Then, ISNR' is compared with the size of _γM . If ISNR′≥γ _M , that is, fSICIC is feasible, then the micro-user feeds back the binary indicator scalar α=1 to the micro-base station; otherwise, fSICIC is not feasible, and the micro-user feeds back α=0 and the desired useful signal weight w _D to the micro-base station ′, where the calculation formula of w _D ′ is as follows:

In the seventh step, the micro base station adjusts the transmission signal according to the received adjustment information and weight:

If α=1, the micro base station continues to send data to the micro user according to the weight calculated in the third step; otherwise, replace the weight w _D ^* calculated in the third step with w _D ', and return to the fourth step.

Example

The present invention proposes a cross-layer serial interference deletion method based on full-duplex communication in a heterogeneous network, the flow chart of which is shown in FIG. 1 . The example simulation uses the matlab simulation platform to simulate and analyze the performance of this method. The physical model of the heterogeneous network is shown in Figure 2. The macro base station is located in the center of the macro cell, and the micro base station is located at (d _s , 0). d _s represents the distance between the macro base station and the micro base station in m, and the UE at S Located at (d _s , r), r=40m, which represents the distance between the micro base station and the micro user, and the macro cell radius r _mc =500m. The transmit power of the macro base station P _m =46dBm, and the maximum transmit power of the micro base station P _s =30dBm. The path loss of the channel from the macro base station is 128.1+37.6log ₁₀ d, d represents the distance between the macro base station and the micro base station or the macro base station and the micro user, the unit is Km, and the path loss of the channel from the micro base station is 141.7+36.7 log ₁₀ d, d represents the distance between the micro base station and the micro user, and the unit is Km. In addition, a penetration loss of 20dB is considered for any channel to the micro-user. SNR _edge represents the average received signal-to-noise ratio of macro users at the edge of the macro cell, and the formula for calculating the noise variance is Define self-interference The unit is dB, and P ₁ is the transmit power of the macro base station. In addition, the outage probability is set to 0.95 in the simulation process, and the performance in the simulation process is measured by the data rate log ₂ (1+SINR) of the signal received by the micro-user, and the unit is bps/Hz.

Figure 3, Figure 4 and Figure 5 show the simulation results. In Fig. 3, the performances of fSICIC and HD-SIC are respectively considered when the data rate R _M of the signal transmitted by the macro base station is 1bps/Hz and 2bps/Hz, and the SIR _self is 90dB and 110dB. In Figure 3, the horizontal axis represents the size of the edge SNR _edge , and the vertical axis represents the average received data rate at the micro-user. In Fig. 4, the horizontal axis represents the size of the distance d _s , and the vertical axis represents the average received data rate at the micro-user. ICI-free in the legend indicates the scene without ICI, and its performance is determined by the formula Obtained, HD-nonSIC represents the scene when the micro base station in fICIC adopts half-duplex mode, and FD-hybrid represents the mixed use of fSICIC and fICIC. This method means that the performance of fSICIC and fICIC is better under the conditions of each channel and distance. In the same way, HD-hybrid means that HD-SIC and HD-nonSIC are used in combination. In Fig. 5, the influence on the performance when the channel feedback is respectively 4, 6 and 8 bits in actual scenarios is considered. It can be seen that when SIR _self and SNR _edge increase and _RM decreases, the performance of fSICIC will increase. When the distance d _s is small, the performance of fSICIC is better and significantly higher than fICIC. When considering imperfect channels, the higher the feedback bits, the better the performance.

Claims (3)

1. a kind of cross-layer serial interference delet method based on full-duplex communication in heterogeneous network, it is characterised in that：Including following several A step,

The first step, full duplex micro-base station acquisition of information；

Described information include macro base station to micro-base station, macro base station to micro- user, micro-base station to micro- user channel and full duplex The self-interference channel of micro-base station, processing delay, micro-base station and the macro base station of micro-base station full duplex self-interference removing module to micro- use The Channel propagation delay at family is poor and the modulation coding scheme of interference signal；

Second step, the feasibility that micro-base station verification serial interference is deleted：

1) according to the modulation coding scheme of interference signal, micro-base station calculates the dry signal-to-noise ratio needed for demodulation interference signal, is denoted as γ_M；

2) under micro-base station maximum transmission power constraints, the maximum dry signal-to-noise ratio ISNR of user terminal is sought；

3) the maximum ISNR of ISNR is judged_mWith the dry signal-to-noise ratio γ needed for demodulation interference signal_MSize, if ISNR_m≥γ_M, Then, fSICIC technical feasibilities, into the 3rd step；Otherwise fSICIC technologies are infeasible, should use existing eICIC or fICIC side Method is disturbed to inhibit cross-layer；The fSICIC technologies refer to the cross-layer serial interference delet method based on full-duplex communication；Institute The eICIC methods stated refer to enhance inter-cell interference suppression technology；The fICIC methods refer to based on full-duplex communication across Layer interference mitigation technology；

3rd step, micro-base station calculate the weighted value of transmitting signal：

1) the transmitting signal x of micro-base station_sIt is received signal y_sThe useful signal s of micro- user is sent to it_sWeighting Be expressed as：

W in formula_IAnd w_DRespectively micro-base station receives signal and is sent to the weight of micro- user's useful signal,F is Carrier frequency, t₁It is the processing delay of full duplex self-interference removing module in micro-base station；

2) calculating of weight：

Consider the transmission power constraint of micro-base station and solve the ISNR constraints of interference signal, with the Signal to Interference plus Noise Ratio SINR of micro- user It maximizes as criterion, optimal weight w_IAnd w_DIt is obtained by solving following problem：

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P in formula_outIt is the transmission power of micro-base station,t₂It is that micro-base station and macro base station are reached at micro- user Propagation delay；h_ms、h_su、h_muIt is letter of the macro base station to micro-base station, micro-base station to micro- user and macro base station to micro- user respectively Road,It is the weight of micro-base station retransmitted jamming signal,It is the transmission power of micro-base station, P_sIt is the emission maximum work(of micro-base station Rate,It is the variance of the self-interference channel of micro-base station,It is the variance of noise power；

In the following two cases, optimal weight w_IAnd w_DW is denoted as respectively_I ^*And w_D ^*, there is different values, be respectively：

A. whenWhen, w_I ^*Modulus value be | w_I ^*|=0, w_D ^*Modulus value bew_D ^*Phase Position is 0；

B. whenWhen, formula (4a)~(4c) is converted to：

<mrow> <mtable> <mtr> <mtd> <munder> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> <mrow> <mo>|</mo> <msub> <mi>w</mi> <mi>I</mi> </msub> <mo>|</mo> <mo>,</mo> <msub> <mi>P</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </mrow> </munder> </mtd> <mtd> <mrow> <mi>S</mi> <mi>I</mi> <mi>N</mi> <mi>R</mi> <mo>=</mo> <mfrac> <mrow> <msub> <mi>P</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>-</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>s</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>|</mo> <msub> <mi>w</mi> <mi>I</mi> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>+</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> </mrow> <mrow> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>|</mo> <msub> <mi>w</mi> <mi>I</mi> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mrow> <mo>(</mo> <msub> <mi>P</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <msubsup> <mi>&amp;sigma;</mi> <mi>e</mi> <mn>2</mn> </msubsup> <mo>+</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> <mo>)</mo> </mrow> <mo>+</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> </mrow> </mfrac> <mo>-</mo> <mn>1</mn> </mrow> </mtd> </mtr> </mtable> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mi>a</mi> <mo>)</mo> </mrow> </mrow>

<mrow> <mtable> <mtr> <mtd> <mrow> <mi>s</mi> <mo>.</mo> <mi>t</mi> <mo>.</mo> </mrow> </mtd> <mtd> <mrow> <mfrac> <mn>1</mn> <mrow> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> </mfrac> <mrow> <mo>(</mo> <mfrac> <mrow> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> <msub> <mi>&amp;gamma;</mi> <mi>M</mi> </msub> </mfrac> <mo>-</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> <mo>)</mo> </mrow> <mo>&amp;le;</mo> <msub> <mi>P</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <mo>&amp;le;</mo> <msub> <mi>P</mi> <mi>S</mi> </msub> </mrow> </mtd> </mtr> </mtable> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mi>b</mi> <mo>)</mo> </mrow> </mrow>

<mrow> <msub> <mi>P</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <mo>=</mo> <mfrac> <msup> <mrow> <mo>(</mo> <mo>(</mo> <mrow> <msub> <mi>P</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <mo>+</mo> <mn>1</mn> </mrow> <mo>)</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>s</mi> </mrow> </msub> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <mo>|</mo> <mo>|</mo> <msub> <mi>w</mi> <mi>I</mi> </msub> <mo>|</mo> <mo>+</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>u</mi> </mrow> </msub> <mo>|</mo> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mrow> <mo>(</mo> <msub> <mi>&amp;gamma;</mi> <mi>M</mi> </msub> <mo>+</mo> <mn>1</mn> <mo>)</mo> <msub> <mi>&amp;gamma;</mi> <mi>M</mi> </msub> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> </mfrac> <mo>+</mo> <mfrac> <mrow> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> <mrow> <mo>(</mo> <msub> <mi>&amp;gamma;</mi> <mi>M</mi> </msub> <mo>+</mo> <mn>1</mn> <mo>)</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> </mfrac> <mo>-</mo> <mfrac> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> <mrow> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> </mfrac> <mo>.</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mi>c</mi> <mo>)</mo> </mrow> </mrow>

(5c) is updated in object function (5a), is as a result usedIt represents, A in formula (| w_I|) be | w_I| it is secondary multinomial Formula, B (| w_I|) be | w_I| quartic polynomial, constraints (5c) be re-written as c≤| w_I|≤d, in formula c and d be two often Number, is obtained by formula (5c) and (5b)；Therefore, formula (5a)~(5c) is reduced to：

<mrow> <mtable> <mtr> <mtd> <munder> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> <mrow> <mo>|</mo> <msub> <mi>w</mi> <mi>I</mi> </msub> <mo>|</mo> </mrow> </munder> </mtd> <mtd> <mrow> <mfrac> <mrow> <mi>A</mi> <mrow> <mo>(</mo> <mo>|</mo> <msub> <mi>w</mi> <mi>I</mi> </msub> <mo>|</mo> <mo>)</mo> </mrow> </mrow> <mrow> <mi>B</mi> <mrow> <mo>(</mo> <mo>|</mo> <msub> <mi>w</mi> <mi>I</mi> </msub> <mo>|</mo> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>-</mo> <mn>1</mn> </mrow> </mtd> </mtr> </mtable> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mi>a</mi> <mo>)</mo> </mrow> </mrow>

s.t.c≤|w_I|≤d. (6b)

Formula (6a) and (6b) are solved using dichotomy；It is corresponding during dichotomy iteration convergence | w_I| it is denoted as i.e. formula (5a) The optimal solution of~(5c), i.e., | w_I ^*|；And then P is obtained by formula (5c)_out, substitute into (4b) and obtain | w_D ^*|；Meanwhile w_I ^*Phase bew_D ^*Phase be 0；

4th step, micro-base station send the training signal of weighting to micro- user：

Micro-base station is sent respectively in two time slots to micro- userAnd w_D ^*Z, wherein z are micro-base stations and micro- with per family Known original training signal,And w_D ^*It is the weights of the training signal sent twice respectively；Micro- user is according to connecing The weighted interference signal received estimates the equivalent channel after weighting, i.e.,With

5th step, micro-base station send signal to micro- user：

The weight w that micro-base station will obtain_I ^*And w_D ^*Formula (3) is substituted into, constructs the transmitting signal x of micro-base station_s, and it is sent to micro- use Family；

6th step, micro- user judge the feasibility and feedback adjustment information and weight of fSICIC：

Micro- user calculates actual dry signal-to-noise ratio first, is denoted as ISNR ', calculation formula is as follows：

Y in formula_uFor the reception signal of micro- user, E { } represents to calculate average；

Then, ISNR ' and γ are compared_MSize：If ISNR ' >=γ_M, i.e. fSICIC is feasible, then micro- user feeds back two to micro-base station System indicates scalar ce=1；Otherwise, fSICIC is infeasible, and micro- user feeds back the power of α=0 and desired useful signal to micro-base station Value w_D', wherein w_D' calculation formula it is as follows：

7th step, micro-base station adjust transmitting signal according to the adjustment information and weight of reception：

If α=1, micro-base station continues to send data to micro- user according to the weight that the 3rd step calculates；It otherwise, will be in the 3rd step The weight w being calculated_D ^*Replace with w_D', and return to the 4th step.

2. the cross-layer serial interference delet method based on full-duplex communication in a kind of heterogeneous network according to claim 1, It is characterized in that：The solution procedure of the maximum dry signal-to-noise ratio ISNR of user terminal is as follows in second step (2),

Micro- user ISNR maximization problems is modeled as：

<mrow> <mtable> <mtr> <mtd> <munder> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> <mrow> <mo>|</mo> <msub> <mi>w</mi> <mi>I</mi> </msub> <mo>|</mo> </mrow> </munder> </mtd> <mtd> <mrow> <mi>I</mi> <mi>S</mi> <mi>N</mi> <mi>R</mi> <mo>=</mo> <mfrac> <msup> <mrow> <mo>(</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>u</mi> </mrow> </msub> <mo>|</mo> <mo>+</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>s</mi> </mrow> </msub> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <mo>|</mo> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>&amp;OverBar;</mo> </mover> <mi>I</mi> </msub> <mo>|</mo> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mrow> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>&amp;OverBar;</mo> </mover> <mi>I</mi> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mrow> <mo>(</mo> <msub> <mover> <mi>P</mi> <mo>&amp;OverBar;</mo> </mover> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <msubsup> <mi>&amp;sigma;</mi> <mi>e</mi> <mn>2</mn> </msubsup> <mo>+</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> <mo>)</mo> </mrow> <mo>+</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> </mrow> </mfrac> </mrow> </mtd> </mtr> </mtable> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mi>a</mi> <mo>)</mo> </mrow> </mrow>

<mrow> <mtable> <mtr> <mtd> <mrow> <mi>s</mi> <mo>.</mo> <mi>t</mi> <mo>.</mo> </mrow> </mtd> <mtd> <mrow> <msub> <mover> <mi>P</mi> <mo>&amp;OverBar;</mo> </mover> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>&amp;OverBar;</mo> </mover> <mi>I</mi> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mrow> <mo>(</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>s</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>+</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>-</mo> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>&amp;OverBar;</mo> </mover> <mi>I</mi> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <msubsup> <mi>&amp;sigma;</mi> <mi>e</mi> <mn>2</mn> </msubsup> </mrow> </mfrac> </mrow> </mtd> </mtr> </mtable> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mi>b</mi> <mo>)</mo> </mrow> </mrow>

<mrow> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>&amp;OverBar;</mo> </mover> <mi>I</mi> </msub> <mo>|</mo> <mo>&amp;le;</mo> <msqrt> <mfrac> <msub> <mi>P</mi> <mi>s</mi> </msub> <mrow> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>s</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>+</mo> <msub> <mi>P</mi> <mi>s</mi> </msub> <msubsup> <mi>&amp;sigma;</mi> <mi>e</mi> <mn>2</mn> </msubsup> <mo>+</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> </mrow> </mfrac> </msqrt> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mi>c</mi> <mo>)</mo> </mrow> </mrow>

H in formula_ms、h_su、h_muIt is letter of the macro base station to micro-base station, micro-base station to micro- user and macro base station to micro- user respectively Road,It is the weight of micro-base station retransmitted jamming signal,It is the transmission power of micro-base station, P_sIt is the emission maximum work(of micro-base station Rate,It is the variance of the self-interference channel of micro-base station,It is the variance of noise power；

By solving-optimizing problem formulations (1a), (1b) and (1c), the maximum for obtaining ISNR is：

<mrow> <msub> <mi>ISNR</mi> <mi>m</mi> </msub> <mo>=</mo> <mfrac> <msup> <mrow> <mo>(</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>u</mi> </mrow> </msub> <mo>|</mo> <mo>+</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>s</mi> </mrow> </msub> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <mo>|</mo> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>~</mo> </mover> <mi>I</mi> </msub> <mo>|</mo> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mrow> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>~</mo> </mover> <mi>I</mi> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mrow> <mo>(</mo> <msub> <msup> <mover> <mi>P</mi> <mo>&amp;OverBar;</mo> </mover> <mo>*</mo> </msup> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <msubsup> <mi>&amp;sigma;</mi> <mi>e</mi> <mn>2</mn> </msubsup> <mo>+</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> <mo>)</mo> </mrow> <mo>+</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>

In formulaWherein | w_I ⁺| it is variable Meet equation

<mfenced open = "" close = ""> <mtable> <mtr> <mtd> <mrow> <mn>2</mn> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>s</mi> </mrow> </msub> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <mo>|</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> <mo>-</mo> <mn>2</mn> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>u</mi> </mrow> </msub> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>~</mo> </mover> <mi>I</mi> </msub> <mo>|</mo> <mrow> <mo>(</mo> <mo>|</mo> <msub> <mover> <mi>P</mi> <mo>&amp;OverBar;</mo> </mover> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <msubsup> <mi>&amp;sigma;</mi> <mi>e</mi> <mn>2</mn> </msubsup> <mo>+</mo> <msubsup> <mi>&amp;sigma;</mi> <mi>n</mi> <mn>2</mn> </msubsup> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>-</mo> <mrow> <mo>(</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>s</mi> </mrow> </msub> <mo>|</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <mo>|</mo> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>~</mo> </mover> <mi>I</mi> </msub> <mo>|</mo> <mo>+</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mi>u</mi> </mrow> </msub> <mo>|</mo> <mo>)</mo> </mrow> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>s</mi> <mi>u</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>~</mo> </mover> <mi>I</mi> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <msubsup> <mi>&amp;sigma;</mi> <mi>e</mi> <mn>2</mn> </msubsup> <mfrac> <mrow> <mi>d</mi> <msub> <mover> <mi>P</mi> <mo>&amp;OverBar;</mo> </mover> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </mrow> <mrow> <mi>d</mi> <mo>|</mo> <msub> <mover> <mi>w</mi> <mo>~</mo> </mover> <mi>I</mi> </msub> <mo>|</mo> </mrow> </mfrac> <mo>=</mo> <mn>0</mn> </mrow> </mtd> </mtr> </mtable> </mfenced>

A definite value, numerical solution acquired using dichotomy.

3. the cross-layer serial interference delet method based on full-duplex communication in a kind of heterogeneous network according to claim 1, It is characterized in that：Formula (6a) and (6b) are solved using dichotomy in 3rd step, are as follows：

A) takeIt takesWherein t is | w_I| any value in its domain；

B) giveSolve following unary biquadratic equation：

A(|w_I|)=(1+ λ) B (| w_I|), (7)

Obtain | w_I| solution；

C) if there is any | w_I| solution disclosure satisfy that formula (6b), then make λ_min=λ, otherwise makes λ_max=λ；

D) step b)~c is repeated), solve requirement until meeting precision.