CN112492676B - Power distribution method for MUSA downlink by comprehensively considering channel capacity and bit error rate - Google Patents

Power distribution method for MUSA downlink by comprehensively considering channel capacity and bit error rate Download PDF

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CN112492676B
CN112492676B CN202011390355.8A CN202011390355A CN112492676B CN 112492676 B CN112492676 B CN 112492676B CN 202011390355 A CN202011390355 A CN 202011390355A CN 112492676 B CN112492676 B CN 112492676B
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base station
musa
channel
downlink
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吴少川
张浩然
李壮
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Beijing Mechanical And Electrical Engineering General Design Department
Harbin Institute of Technology
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Harbin Institute of Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/06—TPC algorithms
    • H04W52/14—Separate analysis of uplink or downlink
    • H04W52/143—Downlink power control
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/241—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account channel quality metrics, e.g. SIR, SNR, CIR, Eb/lo
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/26—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service]
    • H04W52/267—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service] taking into account the information rate

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Abstract

A power allocation method of an MUSA downlink comprehensively considering channel capacity and bit error rate relates to the technical field of communication and aims to solve the problems that the existing power allocation method of an NOMA system is difficult to accurately estimate channel gain and the allocation method is complex. The method comprehensively considers the channel capacity and the error rate performance, and both effectiveness and reliability can be guaranteed. The power allocation algorithm provided by the scheme can allocate power to the downlink users only by transmitting pilot frequency in the uplink in the MUSA system and then estimating the channel gain more accurately, and the method is simple, low in calculation complexity and easy to implement.

Description

Power distribution method for MUSA downlink by comprehensively considering channel capacity and bit error rate
Technical Field
The present application relates to the field of communications technologies, and in particular, to a power allocation technique under a non-orthogonal multiple access technology.
Background
MUSA
With the development of communication technology, the number of wireless access devices and the consumption of data traffic will exhibit explosive growth. In previous wireless communication systems, orthogonal multiple access technology (OMA) was used. However, since the resources allocated to different users in OMA technology need to remain orthogonal, the number of users able to share the same channel resources is limited. To cope with such limitations, researchers have proposed a non-orthogonal multiple access (NOMA) technique. The technology can improve the capacity of the system and improve the spectrum efficiency of the system at the same time, so that the communication can be completed with higher efficiency. The basic idea of NOMA is to achieve sharing of different users over channel resources at the cost of introducing interference between users. The multi-user shared access (MUSA) technology is a code domain NOMA technology proposed by zhongxing communication. In this technique, the modulation symbols of each user are spread by a complex spreading sequence to realize superposition transmission of data of a plurality of users. In addition, the technology utilizes a Serial Interference Cancellation (SIC) technology to complete multi-user detection, and the principle of the SIC is to consider other user data as the interference of the user data to be detected. The MUSA is very suitable for the business of the Internet of things due to the diversity and the low cross correlation of the complex sequence of the MUSA.
In the MUSA technique, the data of each user is distinguished from different users by using a complex multi-element code sequence, and the code sequences used by different users do not need to be guaranteed to be completely orthogonal. Therefore, the MUSA technology has Multiple Access Interference (MAI) caused by non-orthogonality at a receiving end, and in order to cope with the MAI, the MUSA technology adopts an interference cancellation technology at the receiving end to realize detection and reception of data of each user so as to recover the data transmitted by each user. Meanwhile, in the non-orthogonal multiple access technology, how to apply the interference cancellation technology has a great relationship with the distribution situation of the user transmission power in the system.
Power distribution method
The MUSA system selects a complex multivariate sequence to expand data of each user at a transmitting end, the expanded data of each user can be transmitted in a superposition mode, and then MMSE-SIC is adopted at a receiving end to complete multi-user detection. In SIC detection, it is necessary to calculate the SINR of each user first, and detect the data of the user with the highest SINR first. This is because SIC detection has an error propagation phenomenon, that is, the accuracy of the previously detected user data affects the detection of the later user data, and therefore, the accuracy of the previously detected user data needs to be ensured. The power allocation directly affects the SINR of each user, affects the MAI of the receiving-end user, and further affects the detection performance of the receiving end of the MUSA system. Therefore, the impact of power allocation on the performance of the MUSA system needs to be analyzed and discussed.
For the power distribution of the NOMA system, researches find that the power distribution can affect the traversal and rate and the interruption probability of the NOMA system, and for this reason, some new power distribution schemes are proposed in the industry, so that the performance of the NOMA system is ensured to be better than that of the OMA, and meanwhile, the fairness among different users is ensured. However, few studies have been made on power allocation schemes of the MUSA system, and the study on power allocation of the NOMA system only aims at the sum rate and the outage probability, and fails to comprehensively consider the influence of the power allocation on the error rate performance of the system.
The existing power distribution method is further difficult to accurately estimate the channel gain, and the distribution method is complex, high in calculation complexity and difficult to realize.
Disclosure of Invention
The invention aims to solve the problems that the channel gain is difficult to accurately estimate by the power allocation method of the existing NOMA system and the allocation method is complex, thereby providing the power allocation method which comprehensively considers the channel capacity and the bit error rate of the MUSA downlink.
The power allocation method for the MUSA downlink comprehensively considering the channel capacity and the bit error rate is characterized in that: under the condition of MUSA downlink multi-user, the method comprises the following steps:
step one, a base station receives a transmitting signal of each user transmitted by an MUSA uplink from a wireless channel, wherein pilot signals are respectively inserted into the transmitting signals of each user;
secondly, the base station carries out channel estimation according to the pilot frequency in the transmitting signal of each user in the first step to obtain the channel gain h of each user;
step three, the base station sequences the channel gain of each user, and adjusts each user as:
|h1|2≤|h2|2≤…≤|hk|2≤…≤|hK|2the order of (a); wherein K is a user and K is a user number; and K is a positive integer;
step four, the base station calculates to obtain an equivalent channel coefficient f through the channel gain h obtained in the step two and the spreading sequence w selected by each user;
step five, the base station calculates the SINR of the undetected user according to the transmitting signal of each user in the step one, the spreading sequence w selected by each user obtained in the step four and the equivalent channel coefficient f obtained in the step four;
step six, the base station obtains the channel capacity of each user according to the SINR of each user obtained in step five, namely: the rate of each user that can be achieved is Rk；
Step seven, the base station sums the user rates to obtain a user rate sum, and carries out error rate analysis;
step eight, the base station adjusts the power distribution to finish the power distribution of the MUSA downlink for one time, which comprehensively considers the channel capacity and the error rate;
in step eight, the principle of the base station adjusting the power distribution is as follows: the user with large channel gain is allocated with smaller transmitting power, and the user with small channel gain is allocated with larger transmitting power.
The invention has the following beneficial effects:
the method comprehensively considers the channel capacity and the error rate performance, and both effectiveness and reliability can be guaranteed. The power allocation algorithm provided by the scheme can allocate power to the downlink users only by transmitting pilot frequency in the uplink in the MUSA system and then estimating the channel gain more accurately, and the method is simple, low in calculation complexity and easy to implement.
Drawings
FIG. 1 is a schematic diagram of the detection flow of the demodulation decoding process of the present invention;
FIG. 2 is a two-user power allocation scenario model
FIG. 3 is a schematic diagram of a simulation of user and rate versus power allocation coefficient;
FIG. 4 is a simulation diagram of the relationship between the bit error rate and the power distribution coefficient;
Detailed Description
The first embodiment is a power allocation method for the MUSA downlink, which comprehensively considers the channel capacity and the bit error rate,
for the MUSA downlink multi-user scene, the base station distributes power to each user, and each user shares the same time-frequency channel resource. After each user receives the signal, the MMSE-SIC is adopted to respectively detect the required data.
On the basis of power distribution of two users, an MUSA downlink power distribution method giving consideration to both channel capacity and error rate is provided, and a multi-user scene is popularized.
In the scene model, the channel gain of each base station and user k is set as hkThe modulation symbol and spreading sequence of user k are set to xk、wk(ii) a Base stationThe power coefficient allocated to each user is ck. Without loss of generality, channel gains | h of a plurality of users are set1|2≤|h2|2≤…≤|hk|2≤…≤|hK|2. The power distribution coefficient should satisfy c1≥c2≥…≥ck≥…≥cK. In this case, the MUSA system can achieve higher information and rate and error rate performance. The theoretically obtained sum rates are as follows.
SINR of each user at the receiving end is
Figure GDA0003436334810000031
Further, the channel capacity of each user can be obtained, that is, the rate of each user can be reached is
Figure GDA0003436334810000041
Summing the user rates to obtain a user sum rate of
Figure GDA0003436334810000042
The specific power allocation and MMSE-SIC detection schemes are illustrated with two users as an example. Channel gain | h1|2＞|h2|2Then, it is found that c is required to be taken1＜c2I.e. P1＜P2I.e. the base station allocates less power to user 1 than to user 2. At this time, according to the detection principle of MMSE-SIC, at the user 1 end, first detect the data of user 2, then reconstruct the detected data of user 2, then subtract from the received signal, and then detect the data of user 1 by using the new received signal; similarly, at the user 2 side, the data of the user 2 is detected first, but since the user 2 does not need the data of the user 1, the operation of reconstruction elimination is not needed, and the detected user is obtained directly2, the data is only needed; channel gain | h1|2＜|h2|2Then, allocation detection can be performed according to the same principle; consider the special case, | h1|2＝|h2|2According to the proposed power allocation strategy, c should be made1＝c2I.e. the base station allocates equal transmit power to user 1 and user 2. According to the detection principle of MMSE-SIC, the receiving end can select to detect the data of user 1 first, and can also select to detect the data of user 2 first.
The work flow of the whole system is as follows:
Figure GDA0003436334810000043
Figure GDA0003436334810000051
fifthly, the invention has the following effects:
the method can comprehensively consider the channel capacity and the error rate performance, and can ensure the effectiveness and the reliability. The power allocation algorithm provided by the scheme can allocate power to the downlink users only by transmitting pilot frequency in the uplink in the MUSA system and then estimating the channel gain more accurately, and the method is simple, low in calculation complexity and easy to implement.
Sixthly, drawings and description of the drawings (the technical scheme relates to the shape or the structure of a product, and the drawings must be provided):
seventhly, providing at least one specific implementation mode:
a specific embodiment is given herein.
The specific process of the method for performing power allocation and detection of the downlink in the multi-user shared access technology in the two-user scenario in this section is as follows.
It is assumed that the transmitting end, i.e. the base station, has one antenna and the receiving end is two single-antenna users. The scene model is shown in fig. 2. The base station allocates the transmitting power of the user 1 and the user 2, the user 1 and the user 2 share the same time-frequency channel resource, and the receiving signals of the user 1 end and the user 2 end both contain the data of the user 1 and the user 2.
FIG. 2 is a diagram of two user power distribution scenario models
Step one, the base station performs channel coding and QPSK modulation on the data of two users by adopting Turbo coding with code rate 1/2, and then randomly selects a spreading sequence of multi-user shared access to perform sequence spreading on the modulation symbols.
And step one (two), initializing channel parameters, adopting an ideal white Gaussian noise channel, and respectively initializing channel gains of a user 1 and a user 2 to be 0.15 and 0.2.
And step two, the two users respectively send pilot frequencies to the base station, and the base station carries out channel estimation according to the received pilot frequencies and calculates channel gains. The channel estimate is an ideal estimate.
And step three, sorting the channel gains of the two users according to the channel estimation result, wherein the user with large channel gain distributes smaller transmitting power, and the user with small channel gain distributes larger transmitting power. The transmit power varies as the power allocation coefficient varies. Transmitted into a gaussian white noise channel through an antenna.
And step four, after the two users receive the signals, selecting one user side, calculating the signal to interference plus noise ratio (SINR) of each user in the signals and sequencing the SINR. Firstly, MMSE detection is carried out on a user with a larger SINR, then QPSK demodulation and Turbo decoding are carried out, whether information is correct or not is checked, if the information is correct, data of the user are reconstructed and eliminated, the reconstructed data can be regarded as interference of the user to be detected, therefore, the interference needs to be subtracted from a received signal, and if the decoding is wrong, reconstruction elimination operation is not carried out. Detecting whether the information of the user side is detected, and if not, repeating the fourth step; if yes, the next step is performed.
And step five, detecting whether each user side is detected to obtain information. If yes, ending; if not, the user side serial number is increased by one, and the step four is executed.
The parameter configuration is as follows:
Figure GDA0003436334810000061
Figure GDA0003436334810000071
modeling simulation is carried out by using parameters in the table, and the performance of the obtained user, the rate and the error rate is shown in figure 3;
FIG. 3 shows the power allocation at | h in the actual user power allocation1|2＜|h2|2Under the conditions of (a) so that c is1＞c2This makes the sum rate of user 1 and user 2 more optimal, and achieves better channel capacity. At the same time, it can still be seen from the results that as the P/N increases, the channel capacity is less and less affected by the power allocation.
FIG. 4 shows the signal at | h1|2＜|h2|2Under the condition of (c)1＞c2The detection BER of the MUSA system is lower, the detection performance is better, and the detection performance is consistent with the analysis result of the previous user and the rate. According to the simulation result, the BER of the user 1 is in c1In the range of < 0.5, decreasing first and then increasing, in c1BER is continuously reduced in the range of more than or equal to 0.5; while the BER of user 2 is at c1BER is increased continuously in the range of < 0.5, at c1The range of more than or equal to 0.5 is firstly reduced and then increased; average BER of user 1 and user 2 is at c1In the range of < 0.5, decreasing first and then increasing, in c1In the range of not less than 0.5, the mean BER is also decreased and then increased10.65, i.e. c2The minimum value was obtained at 0.35.
In summary, through analysis of two angles of channel capacity, namely user and rate, and BER detection, it can be obtained that power allocation of users will affect the detection performance of the MUSA, and meanwhile, because MMSE-SIC detection has the characteristic of error propagation, the result of the previous detection of user data will affect the detection of the following user data.
In addition, in the MUSA downlink scene, the generality is not lostAt | h1|2≤|h2|2≤…≤|hk|2≤…≤|hK|2Under the condition, in order to achieve better user and rate and better BER detection, the power distribution coefficient should be set as c1≥c2≥…≥ck≥…≥cK. When the signal power is large compared with the noise power, namely P/N is large, the sum rate of the system user is hardly influenced by the power distribution, and when P/N → ∞ is only related to the channel gain between the user and the base station. In the analysis of the BER detection, the influence of the power distribution coefficient on the actual BER detection of the system is specifically analyzed, and meanwhile, the accuracy of the channel capacity analysis is verified.

Claims (3)

  1. The power allocation method for comprehensively considering the channel capacity and the bit error rate of the MUSA downlink is characterized by comprising the following steps: under the condition of MUSA downlink multi-user, the method comprises the following steps:
    step one, a base station receives a transmitting signal of each user transmitted by an MUSA uplink from a wireless channel, wherein pilot signals are respectively inserted into the transmitting signals of each user;
    secondly, the base station carries out channel estimation according to the pilot frequency in the transmitting signal of each user in the first step to obtain the channel gain h of each user;
    step three, the base station sequences the channel gain of each user, and adjusts each user as:
    |h1|2≤|h2|2≤…≤|hk|2≤…≤|hK|2the order of (a); wherein K is a user and K is a user number; and K is a positive integer;
    step four, the base station calculates to obtain an equivalent channel coefficient f through the channel gain h obtained in the step two and the spreading sequence w selected by each user;
    step five, the base station calculates the SINR of the undetected user according to the transmitting signal of each user in the step one, the spreading sequence w selected by each user obtained in the step four and the equivalent channel coefficient f obtained in the step four;
    step six, baseThe station obtains the channel capacity of each user according to the SINR of each user obtained in step five, that is: the rate of each user that can be achieved is Rk；
    Step seven, the base station sums the user rates to obtain a user rate sum, and carries out error rate analysis;
    step eight, the base station adjusts the power distribution to finish the power distribution of the MUSA downlink for one time, which comprehensively considers the channel capacity and the error rate;
    in step eight, the principle of the base station adjusting the power distribution is as follows: the user with large channel gain is allocated with smaller transmitting power, and the user with small channel gain is allocated with larger transmitting power.
  2. 2. The method of claim 1 wherein the step five is performed after the base station calculates the SINR of the undetected user;
    fifthly, selecting the user with the maximum SINR from the undetected users, and executing the fifth step and the second step;
    step two, MMSE detection is carried out on the user with the maximum SINR selected in the step one, and then step three is carried out;
    and step three, demodulating, decoding and outputting the transmission signal of the user with the maximum SINR selected in the step five.
  3. 3. The power allocation method for MUSA downlink in consideration of both channel capacity and error rate according to claim 2, wherein during the demodulation and decoding in step three, the base station determines whether the decoding result is correct, if so, performs step five four, and if not, performs step five,
    step five four, reconstructing and eliminating the data of the user, ending the power distribution,
    and fifthly, not reconstructing and eliminating the data of the user, and returning to execute the fifthly.
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