CN108990070A - A kind of power distribution method of the cognitive radio networks based on NOMA technology - Google Patents

Abstract

The invention discloses a power allocation method of a cognitive radio network based on NOMA technology. The method is carried out in the following steps: 1) establish a system model, and analyze the communication situation of secondary users in the edge area; 2) establish a target optimization model ; 3) Solve the target optimization problem, and optimize the maximum information transmission rate of the secondary user and the transmission power of the primary user base station. The objective function proposed by the invention is a standard convex optimization problem, which can be solved directly. The invention can study the optimal power allocation problem between the secondary user's transmitting end and the relay node under the premise of ensuring the communication quality of the primary user, and realize the maximum throughput of the secondary user.

Description

A Power Allocation Method for Cognitive Radio Networks Based on NOMA Technology

technical field

The present invention relates to the field of wireless communication, in particular to a power allocation method of a cognitive radio network based on non-orthogonal multiple access technology.

Background technique

Both non-orthogonal multiple access technology (NOMA) and cognitive radio technology can effectively improve spectrum efficiency and user transmission rate. With the rapid development of mobile communications, the amount of wireless data traffic is growing explosively, which requires a wireless network with higher spectral efficiency and faster rate to meet the transmission requirements. Applying non-orthogonal multiple access (NOMA) to the cognitive radio network under the Underlay spectrum sharing mode can greatly improve the throughput and spectrum efficiency of the system.

However, in such a communication mode, since the sensing base station will interfere with the primary user, the sensing base station must make the interference smaller than the interference threshold, so as not to affect the communication of the primary user. However, if the transmit power of the sensing base station is too small, the signal-to-noise ratio of the secondary users in the edge area is too small, and the target rate will be interrupted, which will affect the communication quality of the system.

Contents of the invention

In view of the deficiencies in the prior art above, the purpose of the present invention is to propose a power allocation method for a cognitive radio network based on NOMA technology, and the cognitive radio network is also implemented based on non-orthogonal multiple access technology.

In order to achieve the above goals, the technical solution adopted in the present invention is: a method for power allocation of a cognitive radio network based on NOMA technology, which is characterized in that it includes the following steps:

Step 1. Establish the downlink model of the cognitive radio network under the Underlay spectrum sharing mode based on non-orthogonal multiple access. The cognitive base station transmits the secondary user signal under the premise of ensuring the communication quality of the primary user. Transmitted to the relay, the relay uses non-orthogonal multiple access to expand and forward the secondary user signal to the secondary user; the cognitive radio network analyzes the signal received by the relay and the secondary user;

Step 2. Establishing an optimization problem model, taking the maximum throughput of secondary users as the optimization goal, and ensuring the transmission power of cognitive base stations and relays, and the minimum signal-to-noise ratio of secondary users as optimization conditions;

Step 3, solving the optimization problem, and realizing the optimization goal of the effective throughput of the secondary user through the power allocation factor and the channel condition.

As a further refinement of the power allocation method of the present invention, the signal received by the relay in step 1 is:

in In order to recognize the fading coefficient of the fading channel between the relays, a ₁ and a ₂ are the power allocation coefficients of secondary user 1 and secondary user 2 respectively, and a ₁ +a ₂ =1, p _s is the cognitive The transmit power of the base station, s ₁ and s ₂ are the signals sent by the cognitive base station to the secondary user 1 and secondary user 2 respectively, _n is the additive white Gaussian noise with a mean value of 0 and a variance of 1, and sp is the primary user The signal transmitted by the base station, _IT is the large-scale path loss, and α is the path loss exponent, d _p,R is the distance between the primary user base station and the relay.

As a further refinement of the power allocation method of the present invention, the signal received by the secondary user 1 in step 1 is: The signal received by the secondary user 2 is: where G is the amplification factor of the relay, and are respectively the fading coefficients of the relay facing the fading channel between secondary user 1 and secondary user 2, n _R is the sum of the interference of the primary user base station to the relay and the additive white Gaussian noise power on the relay, n is Additive white Gaussian noise with a mean of 0 and a variance of 1, I _p1 and I _p2 are large-scale path losses, and α is the path loss index, d _p,i is the distance between the primary user base station and the secondary user i, i=1 or 2.

As a further refinement of the power allocation method of the present invention, the transmission powers of the cognitive base station and the relay in step 2 are respectively:

Among them, I _p represents the interference threshold of the primary user, p _smax and p _Rmax represent the maximum transmission power of the cognitive base station and the relay, respectively.

As a further refinement of the power allocation method of the present invention, the signal-to-noise ratios of the secondary users described in step 2 are respectively: where h _CR , h _R1 , and h _R2 represent the channel power gains from the cognitive base station to the relay, and from the relay to the secondary user 1 and secondary user 2, p _R is the transmit power of the relay, and σ ₁ and σ ₂ are respectively Indicates that the secondary user 1 and secondary user 2 are interfered by the main user base station and the sum of the additive white Gaussian noise power on the secondary user.

As a further refinement of the power allocation method of the present invention, the function of the optimization objective described in step 2 is expressed as: Among them, γ ₂ and γ ₂ are the minimum signal-to-noise ratios of the secondary user 1 and the secondary user 2, respectively.

As a further refinement scheme of the power allocation method of the present invention, solving the optimization target described in step 3 includes steps:

Step a), simplify the function of optimization objective;

Step b), the optimized objective function after the simplification is optimized twice;

Step c), for to analyze when (If it is greater than, it is a monotonically increasing function, and the analysis is similar), the optimization objective function is a monotonically decreasing function, and the value range of a ₂ is:

then when When , the throughput of secondary users reaches the maximum value.

Compared with the prior art, the present invention adopts the above technical scheme and has the following technical effects:

(1) The main user distribution in this method uses the Poisson distribution method to make the system model closer to the actual application;

(2) This method is based on the principle of "maximum throughput", and under the premise of no interruption, the optimal power allocation factor between the secondary users in the cell is obtained, which effectively improves the system throughput.

Description of drawings

FIG. 1 is a flowchart of a power allocation method for a cognitive radio network based on NOMA technology in the present invention.

FIG. 2 is a model diagram of an implementation system of the present invention corresponding to the above-mentioned power allocation method.

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

The invention proposes that on the basis that the secondary user meets the minimum transmission rate requirement, the throughput of the secondary user can be effectively improved by dynamically adjusting the power allocation factor and controlling the power of the sensing base station and the relay.

As shown in FIG. 1 to FIG. 2 , a flow chart of a power allocation method for a cognitive radio network based on NOMA technology based on non-orthogonal multiple access technology and its implementation system model diagram provided by an embodiment of the present invention, the The method includes the following steps:

Step 1: Establish the downlink model of the cognitive radio network under the Underlay spectrum sharing mode based on non-orthogonal multiple access technology, and analyze the signals received by the relay and secondary users. The operation process of the system is: the sensing base station transmits the secondary user signal to the relay under the premise of ensuring the communication quality of the primary user, and the relay uses non-orthogonal multiple access technology to expand and forward the secondary user signal to the secondary user .

As shown in Figure 2, in the Underlay-NOMA system, the cognitive network consists of a Primary User Base Station (PBS), a Cognitive Base Station (CBS), an amplifying repeater (R), a group of Primary Users (PUs) and two consists of Sub-Users (SUs). Primary User Base Stations (PBS) provide communications for Primary Users (PUs). The primary users are randomly distributed in a two-dimensional plane and obey the Poisson distribution. The fading channel between the Kth primary user and the Cognitive Base Station (CBS) is denoted as h' _k . The transmit power of the primary subscriber base station (PBS) is p. In the edge area of the cognitive radio network, there are two secondary users, denoted as secondary user 1 (SU ₁ ) and secondary user 2 (SU ₂ ). The cognitive base station (CBS) first sends a mixed signal with constant power p _s to the extended repeater R, and the signal s is as follows:

a ₁ and a ₂ are power allocation coefficients of secondary user 1 (SU ₁ ) and secondary user 2 (SU ₂ ), respectively, and a ₁ +a ₂ =1. s ₁ and s ₂ are signals sent by a cognitive base station (CBS) to a secondary user 1 (SU ₁ ) and a secondary user 2 (SU ₂ ).

The fading coefficient of the fading channel between the Cognitive Base Station (CBS) and the Extended Relay (R) is expressed as: The fading coefficient of the fading channel between the cognitive base station and the primary user is expressed as: The fading coefficient of the extended fading channel between the repeater R and the primary user is expressed as: The fading coefficients of the fading channel between the extended repeater R and the secondary user 1 (SU ₁ ), secondary user 2 (SU ₂ ) are expressed as: Assuming that the channel condition of secondary user 2 is better than that of secondary user 1, that is, the channel power gain of the two can be expressed as: h _R1 ≤ h _R2 (2),

Set channel power gain According to the principle of NOMA, it can be known that the power allocation factor a ₁ ≥ a ₂ . The signal received on the expanding repeater (R) side is:

n is an additive Gaussian white noise with a mean of 0 and a variance of 1. _sp is the signal transmitted by the primary subscriber base station (PBS), _IT is the large-scale path loss, where:

α is the path loss exponent, _dp,R is the distance between the primary subscriber base station (PBS) and the extended repeater (R). For simple description, the present invention defines the sum of the interference of the primary user base station (PBS) to the repeater (R) and the additive white Gaussian noise power on the repeater (R) as:

Then, formula (3) can be changed to:

Set the transmit power at the expanded repeater as p _R , then:

Therefore, the amplification factor G can be obtained:

In order not to affect the communication quality of the primary user, the transmission power of the Cognitive Base Station (CBS) and the Extended Repeater (R) must meet:

In the formula, I _p represents the interference threshold of the primary user PU, p _smax and p _Rmax represent the maximum transmission power of the cognitive base station (CBS) and the extended relay (R) respectively.

Then the signals received by secondary user 1 and secondary user 2 can be expressed as follows:

where n is the additive white Gaussian noise with mean value 0 and variance 1 on secondary user 1 and secondary user 2. I _p1 , I _p2 are large-scale path losses respectively, where α is the path loss exponent, d _p,i is the distance between the primary user base station (PBS) and the secondary user i (i=1,2).

In order to simplify the calculation, the present invention expresses the sum of the interference of the primary user base station (PBS) and the additive Gaussian white noise power on the secondary user as: σ _i =1+I _pi p, i=1,2 (14).

Because non-orthogonal multiple access technology (NOMA) is used to broadcast user information between the extended repeater (R) and secondary users, in order to avoid mutual interference caused by overlapping information between secondary users, the secondary user When receiving the signal, the serial interference cancellation (SIC) method is used to decode the signal s1 _first , and then decode the signal _s2 . The signal-to-noise ratios of secondary user 1 and secondary user 2 are:

Step 2: Establish a dual-objective optimization problem model.

The problem studied by the present invention is to maximize the total rate of all secondary users under power-limited conditions. Therefore the objective function that the present invention needs optimization is as follows:

SINR ₁ ≥ γ ₁ , SINR ₂ ≥ γ ₂ , γ ₁ , γ ₂ are the minimum signal-to-noise ratios of secondary user 1 and secondary user 2 respectively.

Step 3: Solve the target optimization problem.

The partial derivative of the objective function can be obtained:

From this it can be seen that when (If it is greater than, it is a monotonically increasing function, and the analysis is similar), the objective function is a monotonically decreasing function, and the value range of a ₂ is:

if Then, for a ₂ , there is no suitable value in this interval, which means that the secondary user 1 or the secondary user 2 cannot meet the predetermined SINR threshold, and then an interruption will occur.

Therefore, when the power allocation factor The transmission rate of formula (17) reaches its maximum value, that is, the throughput of the whole system reaches its maximum value.

In summary, this method ensures the transmission power of the cognitive base station and the relay, puts forward the minimum rate requirement for the transmission rate of the secondary user, establishes the rate optimization model of the secondary user and solves it, and the present invention uses power allocation, The effective throughput and spectrum efficiency of the system are optimized.

The above embodiments are only used to illustrate the present invention and are not intended to limit the technical solutions described in the present invention. The understanding of this description should be based on those skilled in the art, although this description has described the present invention in detail with reference to the above-mentioned embodiments. Note, however, those of ordinary skill in the art should understand that those skilled in the art can still modify the present invention or replace it equivalently, and all technical solutions and improvements that do not depart from the spirit and scope of the present invention should be covered in within the scope of the claims of the present invention.

Claims (7)

1. a kind of power distribution method of the cognitive radio networks based on NOMA technology, it is characterised in that include the following steps:

Step 1: establishing under the cognitive radio networks under the Underlay frequency spectrum share mode accessed based on non-orthogonal multiple Under the premise of certain, secondary user's signal is transmitted in the communication quality for guaranteeing primary user for line link model, cognitive base station Relaying, relaying expand forwarding secondary user's signal to secondary user's using non-orthogonal multiple；Cognitive radio networks analysis Relaying and secondary user's received signal；

Step 2: optimization problem model is established, with the throughput-maximized for optimization aim of secondary user's, and to guarantee to recognize base The lowest signal-to-noise of the transimission power and secondary user's that stand, relay is as optimal conditions；

Step 3: solving optimization problem, realizes the effective throughput of secondary user's by power allocation factor and channel conditions Optimization aim.

2. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, it is characterised in that: The signal of relay reception described in step 1 are as follows:

WhereinFading coefficients for cognitive base station towards fading channel between relaying, a₁And a₂Be respectively secondary user's 1 and time The power partition coefficient of grade user 2, and a₁+a₂=1, p_sFor the transmission power of cognitive base station, s₁And s₂It is cognitive base station hair respectively The signal of secondary user's 1 and secondary user's 2 is given, n is the additive white Gaussian noise that mean value is 0, variance is 1, s_pIt is primary user The signal of Base Transmitter, I_TIt is large scale path loss, andα is path loss index, d_p,RIt is primary user base station The distance between relaying.

3. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, which is characterized in that 1 received signal of secondary user's described in step 1 are as follows: 2 received signal of secondary user's are as follows:Its Middle G is the amplification factor of relaying,WithRespectively relaying is respectively for fading channel between secondary user's 1, secondary user's 2 Fading coefficients, n_RIt is main user base station to the sum of the additive white Gaussian noise power in the interference and relaying of relaying, n is mean value The additive white Gaussian noise for being 1 for 0, variance, I_p1, I_p2Respectively large scale path loss, andα is path damage Consume index, d_p,iIt is the distance between primary user base station and secondary user's i, i=1 or 2.

4. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, which is characterized in that The transimission power of cognitive base station, relaying described in step 2 is respectively as follows:

Wherein, I_pIndicate the interference threshold of primary user, p_smax, p_RmaxRespectively indicate the maximum transmission power of cognitive base station and relaying.

5. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, which is characterized in that The signal-to-noise ratio of secondary user's described in step 2 is respectively as follows: Wherein h_CR,h_R1,h_R2Respectively indicate cognitive base station to relaying, be relayed to secondary use The channel power gain at family 1 and secondary user's 2, p_RFor the transmission power of relaying, σ₁And σ₂Respectively indicate secondary user's 1 and secondary User 2 is by the sum of the additive white Gaussian noise power in the interference and secondary user's of primary user base station.

6. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, which is characterized in that The function representation of optimization aim described in step 2 are as follows:SINR₁≥ γ₁, SINR₂≥γ₂, wherein γ₂, γ₂The respectively lowest signal-to-noise of secondary user's 1 and secondary user's 2.

7. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, which is characterized in that Optimization aim is solved described in step 3 comprising steps of

Step a), the function for simplifying optimization aim；

Step b), simplified optimization object function double optimization is obtained:

It is step c), rightIt is analyzed, whenWhen, optimization object function is monotone decreasing letter Number, a₂Value range are as follows:

Then whenWhen, the handling capacity of secondary user's reaches maximum value.