CN109474317B - Power distribution method of large-scale MIMO bidirectional relay system with hardware damage under MR preprocessing - Google Patents

Power distribution method of large-scale MIMO bidirectional relay system with hardware damage under MR preprocessing Download PDF

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CN109474317B
CN109474317B CN201910011968.7A CN201910011968A CN109474317B CN 109474317 B CN109474317 B CN 109474317B CN 201910011968 A CN201910011968 A CN 201910011968A CN 109474317 B CN109474317 B CN 109474317B
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relay
user
scale mimo
power
power distribution
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CN109474317A (en
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李兴旺
张延良
乔大伟
邓超
陈慧
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Henan University of Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0426—Power distribution
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
    • H04B7/15—Active relay systems
    • H04B7/155—Ground-based stations
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention discloses a power distribution method of a large-scale MIMO bidirectional relay system with hardware damage under MR preprocessing, which distributes power to each user and a large-scale MIMO relay according to an estimated channel so as to ensure that the spectrum efficiency of the system reaches the highest. The method comprises the following steps: 1. receiving a pilot channel sent by a bidirectional user by a hardware-damaged large-scale MIMO relay to obtain an estimated channel matrix; 2. calculating an uplink MRC receiving detection matrix and a downlink MRT precoding matrix according to the estimated channel information, the number of users and the number of base station antennas; 3. establishing a non-convex optimization function for maximizing the spectrum efficiency according to the limitation of the total power of the system, and converting the non-convex optimization function into a convex optimization function; 4. and calculating the distributed power of each user and the large-scale MIMO relay according to the convex optimization function. The invention considers the large-scale MIMO hardware damage and the LOS/NLOS fading environment, and can more reasonably distribute the power scheme for the user and the large-scale MIMO relay.

Description

Power distribution method of large-scale MIMO bidirectional relay system with hardware damage under MR preprocessing
Technical Field
The invention relates to the technical field of wireless communication, in particular to a power distribution method of a large-scale MIMO bidirectional relay system with hardware damage under MR preprocessing.
Background
With the mass increase of mobile intelligent terminals, the data traffic will grow exponentially in the next decade; energy consumption brought by massive intelligent terminals brings huge pressure to the environment, and the problem that how to meet the requirements of improving the spectrum efficiency and the energy efficiency of a communication system becomes urgent to be solved in future movement. In order to solve the above problems, a Time Division Duplex (TDD) large-scale MIMO system obtains a large diversity gain, a large multiplexing gain, and a large array gain by deeply mining spatial resources, thereby greatly improving the spectrum efficiency and the energy efficiency of the system, and becoming one of breakthrough technologies for future 5G mobile communications. A large-scale multiple-input multiple-output (MIMO) terminal deploys a large number of low-cost antennas at the base station end while serving a relatively small number of users, which can effectively reduce the transmission power, reduce inter-cell and intra-cell interference, and simplify the design of the transceiver end. In addition, the cooperative relay can enhance the network coverage and improve the service quality of cell edge users. Currently, massive MIMO cooperation is considered as a strong candidate standard for future efficient communication networks, and is receiving wide attention. The bidirectional relay receives signals of two end links simultaneously by using a network coding principle, and obtains an expected signal at a receiving end by using a Successive Interference Cancellation (SIC) algorithm.
In a bidirectional multi-pair large-scale MIMO relay system, a relay is configured with a large number of low-power-consumption antennas, and N pairs of single-antenna users are randomly distributed at two ends of the relay. In the existing research, a user sends a signal to a massive MIMO relay, the relay receives and detects the signal, performs precoding processing, and then sends the processed signal to an expected user. Under the NLOS and line-of-sight (LOS) fading environments, the problem of power distribution in a large-scale MIMO relay system with bidirectional hardware damage needs to be researched.
Disclosure of Invention
The invention aims to overcome the limitation of the prior art, and considers the use of cheap and low-power antenna arrays by large-scale MIMO, and provides a power distribution method suitable for an MR preprocessing bidirectional large-scale MIMO relay system based on hardware damage.
In order to achieve the purpose, the invention adopts the technical scheme that:
a power distribution method of a large-scale MIMO bidirectional relay system with hardware damage under MR preprocessing comprises the following steps:
s1, with the nth user as the power distribution object, the large-scale MIMO relay calculates each channel statistical characteristic containing hardware damage through the channel estimation algorithm
Figure BDA0001937664680000021
And statistical characterization of the estimation error
Figure BDA0001937664680000022
Are respectively as
Figure BDA0001937664680000023
Figure BDA0001937664680000024
Wherein, betanRepresents the large-scale fading coefficient, K, from the nth user to the massive MIMO relaynIndicating the Rice fading factor (K) of the nth user to massive MIMO relaynRayleigh fading) ppDenotes the training sequence power, τ training sequence length, κ, of the user transmissionrIndicating the relay reception impairment level.
S2, calculating the approximate downlink channel condition characterization quantity of the nth user, including the following steps:
2.1 obtaining an estimated channel matrix according to channel reciprocity, all users sending signals to the massive MIMO relay, which utilizes MRC detection matrix
Figure BDA0001937664680000025
Processing the received signal to obtain a processed signal r;
2.2 Large-Scale MIMO Relay through precoding matrix
Figure BDA0001937664680000026
Processing signals r, large-scale MIMThe O relay system amplifies the processed signals and forwards the amplified signals to a user;
2.3, calculating to obtain a downlink channel condition characteristic quantity of the nth user;
2.4 obtaining approximate downstream channel condition characterization quantity of the nth' user according to the law of large numbers
S3, obtaining a function expression of the spectrum efficiency under the condition of limited power, comprising the following steps:
3.1 maximum value of total transmission power of all users and relays is known as PmaxAnd obtaining the following user and relay power distribution when the spectrum efficiency is highest:
Figure BDA0001937664680000027
wherein p is0And p1Peak power for the user and the relay, respectively.
3.2, converting the non-convex optimization function in the formula (3) into a convex polynomial optimization function
Figure BDA0001937664680000031
S4, the concrete method of the optimal power distribution scheme is as follows:
4.1, initializing parameters epsilon and nu, maximum iteration times L, setting iteration times m and initializing a signal-to-interference-and-noise ratio gamman,1,n＝1,…,2N；
4.2, calculating
Figure BDA0001937664680000032
And
Figure BDA0001937664680000033
solving the geometric programming function in equation (5)
Figure BDA0001937664680000034
Wherein
Figure BDA0001937664680000035
Is composed of
Figure BDA0001937664680000036
Closest to gammanPoint of +1, assume
Figure BDA0001937664680000037
Is the optimal solution;
4.3, judging whether the requirements are met
Figure BDA0001937664680000038
Or if m is equal to L, ending iteration; if not, entering the step (4.4);
4.4, let m be m +1, continue with step 4.2.
The transmitting power of the user and the bidirectional relay is obtained by utilizing the algorithm, so that the sum of the transmission rates of the large-scale MIMO system with hardware damage can be maximized.
The invention has the following beneficial effects:
1. the invention considers the hardware damage of the relay end, and is closer to the actual situation;
2. the invention only needs the base station to estimate the statistical information of the channel, the statistical information only comprises the Rice K factor, the large-scale fading and the hardware loss, and the parameters are easy to obtain in the actual system;
3. the power distribution algorithm designed by the invention has low complexity and is simple to realize;
4. the invention has strong applicability and can be applied to LOS and NLOS fading channels.
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FIG. 1 is a system model of an embodiment of the present invention;
FIG. 2 is a detailed flow chart of the present invention.
Detailed Description
In order to more clearly illustrate the technical method in the embodiment of the present invention, the present invention will be further described in detail with reference to the accompanying drawings.
The multi-pair bidirectional massive MIMO cooperative relay system model of the present example is shown in FIG. 1The method comprises an M-antenna large-scale MIMO relay, N pairs of single-antenna users, wherein the users are randomly distributed on two sides of the large-scale MIMO relay, and M is>>2N, wherein
Figure BDA0001937664680000039
And
Figure BDA0001937664680000041
for bidirectional users exchanging information, TRFor a massive MIMO relay,
Figure BDA0001937664680000042
and
Figure BDA0001937664680000043
for bi-directional user-to-relay multiple access channels, and the same
Figure BDA0001937664680000044
And
Figure BDA0001937664680000045
is a broadcast channel relayed to a bi-directional user. And the massive MIMO relay calculates the statistical information of the estimated channel, and the bidirectional users exchange respective information through the MR base station according to the estimated information.
In an actual communication system, the rice factor, the large-scale fading and the hardware loss are constant or change very slowly, and the large-scale MIMO relay can estimate the parameters by using the channel characteristics. The invention can be used in LOS and NLOS fading environment, and is also suitable for more practical wireless communication system with non-ideal hardware.
As shown in fig. 2, S1, first calculating the statistical characteristics of each estimated sub-channel including hardware impairments, includes the following steps:
1.1, all users send pilot signals to the massive MIMO relay, wherein the pilot signals are known mutually orthogonal signals of a user terminal and the massive MIMO relay;
1.2, the base station takes the nth (n and n' as the user pair, exchanging information) user as the power distribution object, and the large-scale MIMO calculates each channel with hardware damage and the statistical characteristics of estimation error through an uplink channel estimation algorithm
Figure BDA0001937664680000046
Figure BDA0001937664680000047
Wherein, betanRepresents the large-scale fading coefficient, K, from the nth user to the massive MIMO relaynIndicating the Rice fading factor (K) of the nth user to massive MIMO relaynRayleigh fading) ppDenotes the training sequence power, τ training sequence length, κ, of the user transmissionrIndicating the relay reception impairment level.
S2, calculating the approximate downlink channel condition characterization quantity of the nth user, including the following steps:
2.1, all user pairs obtain the statistical information of the estimated channel, send signals to the massive MIMO relay according to the statistical information, and the massive MIMO utilizes the MRC detection matrix
Figure BDA0001937664680000048
Processing the received signal to obtain a processed signal r;
2.2 obtaining statistical information of downlink channel according to TDD channel reciprocity principle, large-scale MIMO relay utilizes MRT precoding matrix
Figure BDA0001937664680000049
Processing the signal r, and amplifying and forwarding the processed signal to a user by the large-scale MIMO relay system;
2.3, calculating to obtain the downlink channel condition characterization quantity of the nth' (n user pairs);
2.4, according to the law of large numbers, further obtaining the approximate downstream channel condition characterization quantity gamma of the nth usern'。
S3, obtaining a function expression of the spectrum efficiency under the power-limited condition according to the step S2, and comprising the following steps:
3.1 maximum value of total transmission power of all users and relays is known as PmaxAnd obtaining the following user and relay power distribution when the spectrum efficiency is highest:
Figure BDA0001937664680000051
wherein p is0And p1Peak power for the user and the relay, respectively.
3.2, converting the non-convex optimization function in the formula (3) into a convex polynomial optimization function
Figure BDA0001937664680000052
S4, the concrete steps of calculating the optimal power distribution scheme are as follows:
4.1, initializing parameters epsilon and nu, maximum iteration times L, setting iteration times m and initializing a signal-to-interference-and-noise ratio gamman,1,n＝1,…,2N；
4.2, calculating
Figure BDA0001937664680000053
And
Figure BDA0001937664680000054
solving the geometric programming function in equation (5)
Figure BDA0001937664680000055
Wherein
Figure BDA0001937664680000056
Is composed of
Figure BDA0001937664680000057
Closest to gammanPoint of +1, assume
Figure BDA0001937664680000058
Is the optimal solution;
4.3, judging whether the requirements are met
Figure BDA0001937664680000059
Or if m is equal to L, ending iteration; if not, entering step 4.4;
4.4, let m be m +1, continue with step 4.2.
The transmitting power is obtained by utilizing the scheme, so that the spectrum efficiency of a multi-pair bidirectional large-scale MIMO system can reach the highest.
The above is only one example of the present invention, and it should be noted that: it will be apparent to those skilled in the art that modifications and variations can be made in the present invention without departing from the principles thereof. Such modifications and variations of the present invention are included in the scope of the claims of the present invention and the technical equivalents thereof.

Claims (1)

1. A power distribution method of a large-scale MIMO bidirectional relay system with hardware damage under MR preprocessing is suitable for M-antenna large-scale MIMO relay, N pairs of single-antenna users are randomly deployed on two sides of the relay, and the method is characterized in that:
s1, firstly, the statistical characteristics of each estimation sub-channel containing hardware damage are calculated, and the method comprises the following steps:
1.1, all users send pilot signals to the massive MIMO relay, wherein the pilot signals are known mutually orthogonal signals of a user terminal and the massive MIMO relay;
1.2, the base station takes the nth user as a power distribution object, and the large-scale MIMO relay calculates each channel statistical characteristic containing hardware damage through a channel estimation algorithm
Figure FDA0002836284970000011
And statistical characterization of the estimation error
Figure FDA0002836284970000012
Are respectively as
Figure FDA0002836284970000013
Figure FDA0002836284970000014
Wherein, betanRepresents the large-scale fading coefficient, K, from the nth user to the massive MIMO relaynIndicating the Rice fading factor (K) of the nth user to massive MIMO relaynRayleigh fading) ppDenotes the training sequence power, τ training sequence length, κ, of the user transmissionrIndicating the level of impairment of reception of the relay,
s2, calculating the approximate downlink channel condition characterization quantity of the nth user, including the following steps:
2.1 obtaining an estimated channel matrix according to channel reciprocity, all users sending signals to the massive MIMO relay, which utilizes MRC detection matrix
Figure FDA0002836284970000015
Processing the received signal to obtain a processed signal r;
2.2 Large-Scale MIMO Relay through precoding matrix
Figure FDA0002836284970000016
Processing the signal r, and amplifying and forwarding the processed signal to a user by the large-scale MIMO relay system;
2.3, calculating to obtain a downlink channel condition characteristic quantity of the nth user;
2.4, obtaining the approximate downlink channel condition characterization quantity of the nth user according to a law of large numbers;
s3, obtaining a function expression of the spectrum efficiency under the condition of limited power, comprising the following steps:
3.1 maximum value of total transmission power of all users and relays is known as PmaxAnd obtaining the following user and relay power distribution when the spectrum efficiency is highest:
Figure FDA0002836284970000021
wherein p is0And p1The peak power of the user and the relay respectively,
3.2, converting the non-convex optimization function in the formula (3) into a convex polynomial optimization function
Figure FDA0002836284970000022
S4, the concrete method of the optimal power distribution scheme is as follows:
4.1, initializing parameters epsilon and nu, maximum iteration times L, setting iteration times m and initializing a signal-to-interference-and-noise ratio gamman,1,n＝1,…,2N；
4.2, calculating
Figure FDA0002836284970000023
And
Figure FDA0002836284970000024
solving the geometric programming function in equation (5)
Figure FDA0002836284970000025
Wherein
Figure FDA0002836284970000026
Is composed of
Figure FDA0002836284970000027
Closest to gammanPoint of +1, assume
Figure FDA0002836284970000028
Is the optimal solution;
4.3, judging whether the requirements are met
Figure FDA0002836284970000029
Or if m is equal to L, ending iteration; if not, entering the step (4.4);
4.4, let m be m +1, continue with step 4.2.
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