CN107241124A - High energy efficiency self-adaptive modulation method in a kind of distributing antenna system based on power distribution - Google Patents

Abstract

The present invention discloses high energy efficiency self-adaptive modulation method in a kind of distributing antenna system based on power distribution, the energy efficiency of antenna system in a distributed manner of the invention, which is maximized, is used as optimization aim, the modulation system of the power and signal of each remote antenna of antenna system is used as optimized variable in a distributed manner, Adaptive Modulation handoff threshold is obtained using the approximate bit error rate formula of modulation system, then the general type of power distribution is given, and every kind of modulation system is searched with this, so as to find out optimal modulation system and its power distribution.Method proposed by the invention not only can effectively draw the optimum allocation of each remote antenna power and the optimal setting of signal modulation mode, and algorithm flow is simple, be calculated without complicated function.

Description

A power-allocation-based adaptive modulation for energy-efficient distributed antenna systems method

Technical field:

The invention belongs to the field of mobile communication, and relates to the design of a physical layer transmission scheme of a mobile communication system, in particular to an adaptive modulation method with high energy efficiency in a distributed antenna system based on power distribution.

Background technique:

With the continuous development of mobile communication technology, the number of mobile communication devices and the number of users are increasing rapidly, and the energy consumed by the mobile communication system is also increasing exponentially. Facing the increasingly tense global energy situation, research institutions at home and abroad are constantly seeking information transmission technologies with higher energy efficiency (EE, Energy Efficiency), and "green communication" has become a topic of widespread concern. Finding a transmission technology that can effectively improve the energy efficiency of the system is becoming the trend of wireless communication in the future.

Distributed Antenna System (DAS, Distributed Antenna System) is a communication system that arranges multiple transmitting antennas in different positions of the cell. Each transmitting antenna in the system communicates with the central processing unit of the cell through optical fiber, coaxial cable or wireless link. connected to the device. Studies have shown that DAS solutions can improve spectral efficiency and reduce the cost of signal transmission. Compared with traditional centralized antenna systems, DAS systems have huge advantages in terms of capacity, energy consumption and coverage. Under the same spectral efficiency, the distributed antenna system can effectively reduce the access distance required by the mobile station, that is, expand the coverage of the base station and reduce the transmission power of the system transmitting end. Distributed antenna systems have shown incomparable advantages over traditional cellular systems in terms of increasing system capacity, reducing transmit power, increasing diversity, reducing the number of handovers, and reducing the probability of interruption. It is considered to be an ideal substitute for traditional cellular systems. One of the options.

Power allocation has always been one of the research hotspots in distributed antenna systems. Since the distance between the user and each transmitting antenna is not equal, the channel conditions between each antenna and the user are also different. In order to improve energy efficiency, the antennas of the DAS system are not necessarily used to send signals to users, and users can selectively allow users to communicate with several sending antennas, that is, according to the channel conditions of each antenna to the user, different antennas are assigned to each antenna. the sending power. This can improve the overall energy efficiency of the system and reduce unnecessary power consumption. Document 1 (Xin Chen, Xiaodong Xu, XiaofengTao. Energy efficient power allocation in generalized distributed antennasystem [J]. IEEE Communications Letters, 2012, 16(7): 1022-1025.) treats this problem as a fractional programming problem, using The general optimization solution method obtains an iterative algorithm. Document 2 (Heejin Kim, Sang-Rim Lee, Changick Song, Kyoung-Jae Lee, Inkyu Lee, Optimal power allocation scheme for energy efficiency maximization in distributed antenna systems[J]. IEEE Transactions on Communications, 2015, 63(2): 431-440 .) uses the Karush-Kuhn-Tucker (KKT) condition to obtain the closed form of the power allocation problem, and gives the closed form solution according to the Lambertian function.

In addition to power allocation can improve the energy efficiency of the DAS system, adaptive modulation (AM, Adaptive Modulation) is also a very effective method. Energy efficiency adaptive modulation can adaptively change the modulation mode of the signal according to the current channel information conditions of the system, and maximize the energy efficiency of the system under the premise of ensuring the target bit error rate. In the current research, there are few systems that directly take energy efficiency as the optimization goal for adaptive modulation, and adaptive modulation is used to improve spectral efficiency most of the time. Because energy efficiency is not only related to the modulation method, but also related to power. If only the modulation mode is adaptive and the power is not adaptive, this is no different from frequency effect adaptation. Document 3 (XiangbinYu, Wenting Tan, Binbin Wu, Yang Li. Discrete-rate adaptive modulation with variable threshold for distributed antenna system in the presence of imperfect CSI[J]. China Communications, 2014,11(13):31-39.) Research The transmission scheme and performance of discrete rate adaptive modulation of distributed antenna system under the condition of incomplete channel information are studied, and the goal of optimization is spectrum efficiency. The goal of this patent is to optimize the energy efficiency of the DAS system, which will simultaneously adapt to power and modulation. Power allocation is the adaptation of power in space, and adaptive modulation is the adaptation of the signal modulation method. Therefore, the method proposed in this patent is a method that can adaptively adjust the transmission power and signal modulation mode of each remote antenna according to the current channel information.

Invention content:

In order to improve the energy efficiency of the distributed antenna system, the present invention proposes a high-energy-efficiency adaptive modulation method in a distributed antenna system based on power distribution. This method utilizes the channel gain and noise power ratio between each distributed antenna and the user to Calculate the power allocated to each distributed antenna by the system and the modulation mode adopted by the signal.

The technical solutions adopted in the present invention include: a high-energy-efficiency adaptive modulation method in a distributed antenna system based on power distribution, comprising the following steps:

(1) Determine the set of alternative signal modulation modes, and calculate the corresponding adaptive switching threshold under a certain target bit error rate requirement;

(2) Obtain the channel gain to noise power ratio from each remote antenna to the user in the distributed antenna system, and arrange them in descending order: Establish the corresponding power vector to be optimized: Where N _t is the number of remote antennas;

(3) According to the switching threshold of adaptive modulation in the step (1) and the channel gain and the noise power ratio of each remote antenna to the user in the step (2), find out the feasible modulation mode in the candidate signal modulation mode set;

(4) For each feasible modulation mode in step (3), give its power allocation scheme respectively, and calculate the corresponding energy efficiency;

(5) According to the energy efficiency calculated in step (4), select the largest one, the corresponding power allocation scheme is the power allocation scheme adopted by the system, and the corresponding modulation mode is the modulation mode adopted by the system.

Further, the set of alternative modulation modes in the step (1) is composed of N different Gray coded QAM modulations, and its corresponding switching threshold is obtained by the following formula

ρ _n =[erfc ^-1 (BER ₀ /a _n )] ² /b _n

where BER ₀ is the target bit error rate, a _n and b _n are the parameters of the nth modulation scheme, n∈{1,2,...,N}.

Further, the step of selecting a feasible modulation mode in the step (3) is: calculating Among them, P _max,i is the maximum power that can be allocated by the i-th antenna, and all corresponding switching thresholds are not greater than The modulation schemes of the set form a set of feasible modulation schemes. If the set is empty, the signal transmission of the system is interrupted.

Further, the step of calculating the power allocation corresponding to the nth modulation mode in the step (4) is:

(a) Let m=1,P _m =P _max,m , if And m<N _t execute step (b), otherwise execute step (c);

(b) m=m+1,P _m =P _max,m , if And m<N _t repeatedly execute step (b), otherwise execute step (c);

(c)

(d) The power distribution of each antenna is P=[P _max,1 ,...P _max,m-1 ,P _m ,0,...,0] ^T ;

(e) Calculate the energy efficiency according to the power obtained in step (d) Where M _n is the information rate corresponding to the nth modulation mode, and P _c is the system loop power consumption.

The invention has the following beneficial effects: the invention can obtain the maximization of energy efficiency, and by adopting a specific modulation mode and allocating specific power to each remote antenna, the energy efficiency of the system can be improved as much as possible. The calculation process of the method is simple, and there is no complicated function calculation. The judgment of the feasible modulation mode effectively avoids some unnecessary calculations and reduces the search times.

Description of drawings:

Fig. 1 is a flowchart of an embodiment of the present invention.

FIG. 2 is a model diagram of a distributed antenna system in an embodiment of the present invention.

Fig. 3 is a spectrum efficiency diagram of the embodiment.

Fig. 4 is an energy efficiency diagram of the embodiment.

detailed description:

In order to clarify the technical scheme and technical purpose of the present invention, the present invention will be further introduced below in conjunction with the accompanying drawings and specific implementation methods.

The hardware devices involved in the high-energy-efficiency adaptive modulation method in the distributed antenna system based on power allocation of the present invention include remote antennas distributed in different positions of the cell, and a central processing unit (CPU, Central Processing Unit) connected to each remote antenna , A mobile station (MS, Mobile Station) receiving service in the cell. In this embodiment, as shown in FIG. 2 , there are N _t remote antennas scattered in the cell, denoted as RA _i , i=1,...,N _t . Each remote antenna is equipped with 1 antenna and is connected to the central processing unit through a specific transmission channel. A mobile station (MS) within a cell has one or more antennas. Define h _i as the channel fading coefficient from the i-th remote antenna to the mobile station, define is the power of the complex white Gaussian noise of the mobile station.

A high-energy-efficiency adaptive modulation method in a distributed antenna system based on power distribution of the present invention comprises the following steps:

Step 1: Determine the set of candidate signal modulation modes, and calculate the corresponding adaptive switching threshold. The alternative modulation mode adopts QAM modulation encoded in N different Gray code modes. In this embodiment, it is assumed to be {BPSK, 4QAM, 8QAM, 16QAM, 32QAM, 64QAM}. For the nth modulation method, its bit error rate in a Gaussian white noise channel can be approximately expressed as:

Among them, the parameters a _n and b _n are given in Table 1.

Table 1

BPSK 4QAM 8QAM 16QAM 32QAM 64QAM a _n 1/2 1/2 5/12 3/8 13/40 7/24 b _n 1 1/2 1/6 1/10 1/26 1/42

Let this approximate expression be equal to the target bit error rate BER ₀ , the switching threshold of adaptive modulation can be obtained according to the following formula:

ρ _n =[erfc ^-1 (BER ₀ /a _n )] ² /b _n

Step 2. By obtaining the channel fading coefficient from each remote antenna to the mobile station and the power of the complex white Gaussian noise of the mobile station, the distributed antenna system calculates the channel gain to noise power ratio from each remote antenna to the mobile station. The calculation formula is as follows:

Wherein, h _i is generally determined jointly by large-scale fading and small-scale fading, that is, h _i =g _i Ω _i . g _i represents small-scale fading, and commonly used small-scale fading models include Rayleigh fading and Rice fading. Ω _i represents large-scale fading, generally including path loss and shadow fading.

The signal processing unit of the distributed antenna system ranks the channel gain to noise power ratio of each remote antenna to the mobile station in descending order:

The signal processing unit establishes a power allocation vector to be optimized Among them, P _i and γ _i are in one-to-one correspondence in sequence.

Step 3 selects a feasible modulation method from the set of candidate modulation methods. Not all modulation methods are suitable for use under current channel conditions, and some inappropriate modulation methods can be eliminated in advance. Knowing the channel gain and noise ratio γ _i from each remote antenna to the receiving end, the maximum signal-to-noise ratio that the whole system can obtain is At this point all remote antenna powers have reached their maximum power P _max,i . All thresholds greater than Any modulation method can be excluded, because it is impossible for the system to achieve such a large signal-to-noise ratio under the current channel conditions. If the threshold values of all modulation schemes are greater than This means that without a suitable modulation method, the system signal transmission will be interrupted.

In step 4, for each feasible modulation mode in step 3, the power allocation scheme is given respectively, and the corresponding energy efficiency is calculated. The energy efficiency optimization problem of the DAS system when using the nth modulation method can be written as:

0≤P≤P _max,i

Among them, P _c is the loop power consumption of the system, and M _n represents the information rate of the modulation mode adopted by the current system. Through the Lagrange multiplier method, it can be proved that the optimal power allocation must satisfy the following two conditions:

P＝[P _max,1 ,...,P _max,k-1 ,P _k ,0,...,0] ^T

In order to obtain the power allocation that satisfies the above two conditions, an iterative calculation method can be used, the steps are as follows:

(a) Let m=1,P _m =P _max,m , if And m<N _t execute step (b), otherwise execute step (c);

(b) m=m+1,P _m =P _max,m , if And m<N _t repeatedly execute step (b), otherwise execute step (c);

(c)

(d) The power distribution of each antenna is P=[P _max,1 ,...P _max,m-1 ,P _m ,0,...,0] ^T ;

(e) Calculate energy efficiency η _EE according to the power obtained in step (d).

Step 5: According to the power distribution and energy efficiency obtained in step 4 under multiple modulation modes, the system selects the group with the highest energy efficiency. The corresponding modulation mode is the modulation mode adopted by the system, and the corresponding power allocation is the power allocation adopted by the system.

In order to illustrate the technological advancement of the algorithm of the present invention, the spectrum efficiency and energy efficiency of the present invention under different maximum transmission power limits and different target bit error rates are obtained through simulation on the MATLAB platform, as shown in Figures 3 and 4.

In the simulation, for the convenience of analysis, the maximum transmission power of each remote antenna is set equal to a specific value P _max . Figure 3 shows the spectrum efficiency values of the distributed antenna system under different P _max and different target bit error rates BER ₀ . The simulation results show that the method proposed by the present invention can effectively adjust the modulation mode of the signal adaptively according to the current condition of the system. It can be seen that with the increase of P _max , the system will adopt a higher-order modulation mode, thereby increasing the spectral efficiency of the system. When the current target bit error rate becomes smaller, the spectral efficiency of the system also becomes smaller. This is because the lower the target bit error rate is, the higher the system bit error rate performance requirement is, and the system will use a lower-order modulation method to reduce the bit error rate. Figure 4 shows the energy efficiency values of the distributed antenna system under different P _max and different target bit error rates. Simulation results show that the method proposed by the present invention can effectively adjust antenna power and modulation mode adaptively according to the current system conditions. It can be seen that with the increase of P _max , the system will adopt a higher-order modulation mode, and the available power distribution combination will be more optimized, thereby increasing the energy efficiency of the system. When the current target bit error rate becomes smaller, the energy efficiency of the system also becomes smaller. This is because the lower the target bit error rate is, the higher the system bit error rate performance requirements are, and the system will use a combination of lower-order modulation and more conservative power allocation to reduce the bit error rate.

To sum up, the method proposed by the present invention can effectively obtain the optimal modulation mode and power distribution to maximize the energy efficiency. At the same time, the steps of the method are simple, there is no complicated function calculation, only basic addition, subtraction, multiplication and division operations, and the algorithm Efficiency can be guaranteed. This fully demonstrates the effectiveness of the energy-efficient adaptive modulation method in a distributed antenna system based on power allocation proposed by the present invention.

The above is only a preferred embodiment of the present invention, it should be pointed out that for those of ordinary skill in the art, some improvements can also be made without departing from the principle of the present invention, and these improvements should also be regarded as the invention. protected range.

Claims (4)

1. A high-energy-efficiency adaptive modulation method in a distributed antenna system based on power distribution, characterized in that: comprise the following steps: (1) Determine the set of alternative signal modulation modes, and calculate the corresponding adaptive switching threshold under a certain target bit error rate requirement; (2) Obtain the channel gain to noise power ratio from each remote antenna to the user in the distributed antenna system, and arrange them in descending order: Establish the corresponding power vector to be optimized: Where N _t is the number of remote antennas; (3) According to the switching threshold of adaptive modulation in the step (1) and the channel gain and the noise power ratio of each remote antenna to the user in the step (2), find out the feasible modulation mode in the candidate signal modulation mode set; (4) For each feasible modulation mode in step (3), give its power allocation scheme respectively, and calculate the corresponding energy efficiency; (5) According to the energy efficiency calculated in step (4), select the largest one, the corresponding power allocation scheme is the power allocation scheme adopted by the system, and the corresponding modulation mode is the modulation mode adopted by the system. 2. The energy efficient adaptive modulation method in the distributed antenna system based on power allocation according to claim 1, characterized in that: in the step (1), the set of alternative modulation modes is encoded by N different Gray code modes Composed of QAM modulation, the corresponding switching threshold is obtained by the following formula ρ _n =[erfc ^-1 (BER ₀ /a _n )] ² /b _n where BER ₀ is the target bit error rate, a _n and b _n are the parameters of the nth modulation scheme, n∈{1,2,...,N}. 3. the energy efficient adaptive modulation method in the distributed antenna system based on power allocation according to claim 1, is characterized in that: the step (3) of selecting feasible modulation mode is: calculating Among them, P _max,i is the maximum power that can be allocated by the i-th antenna, and all corresponding switching thresholds are not greater than The modulation schemes of the set form a set of feasible modulation schemes. If the set is empty, the signal transmission of the system is interrupted. 4. The energy-efficient adaptive modulation method in the distributed antenna system based on power distribution according to claim 1, characterized in that: the step of calculating the power distribution corresponding to the nth modulation mode in the step (4) is: (a) Let m=1,P _m =P _max,m , if And m<N _t execute step (b), otherwise execute step (c); (b) m=m+1,P _m =P _max,m , if And m<N _t repeatedly execute step (b), otherwise execute step (c); (c) (d) The power distribution of each antenna is P=[P _max,1 ,...P _max,m-1 ,P _m ,0,...,0] ^T ; (e) Calculate the energy efficiency according to the power obtained in step (d) Where M _n is the information rate corresponding to the nth modulation mode, and P _c is the system loop power consumption.