CN111970708A - Method and device for reducing transmission delay of fog radio access network - Google Patents

Method and device for reducing transmission delay of fog radio access network Download PDF

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CN111970708A
CN111970708A CN202010509671.6A CN202010509671A CN111970708A CN 111970708 A CN111970708 A CN 111970708A CN 202010509671 A CN202010509671 A CN 202010509671A CN 111970708 A CN111970708 A CN 111970708A
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precoding
transmission delay
fbss
base station
optimization
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CN111970708B (en
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朱政宇
郝万明
宋燚
孙钢灿
郭亚博
李哲
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Zhengzhou University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H04W16/20—Network planning tools for indoor coverage or short range network deployment
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/22—Traffic simulation tools or models
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/22—Traffic simulation tools or models
    • H04W16/225—Traffic simulation tools or models for indoor or short range network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
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Abstract

The invention provides a method and a device for reducing transmission delay of a fog radio access network, comprising the following steps: establishing a millimeter wave fog radio access network (F-RAN) system model based on a Femto Base Station Cluster (FBSC); by optimizing hybrid analog/digital precoding, the problem of minimizing transmission delay is proposed; the problem presented is translated into two independent problems, namely: hybrid precoding design problems of multi-Femto Base Stations (FBSs) and precoding design problems of Base Stations (BS); aiming at the design problem of hybrid precoding of a multi-femto base station, an iterative algorithm based on continuous convex approximation (SCA) is provided to optimize digital precoding, and aiming at the precoding design problem of the base station, a similar iterative algorithm is adopted to solve, so that the algorithm can minimize the transmission delay of a system and has higher convergence speed. By optimizing the two problems, the problem of transmission delay of the millimeter wave communication fog radio access network based on the femto base station cluster can be solved.

Description

Method and device for reducing transmission delay of fog radio access network
Technical Field
The invention relates to the technical field of communication, in particular to a method and a device for reducing transmission delay of a fog radio access network.
Background
In order to meet the rapidly increasing rate demand of future wireless communication, advanced communication technologies such as coordinated multi-point transmission, millimeter wave communication (mmWave), massive multiple input multiple output (mimo), and cloud radio access network (C-RAN) have been proposed in recent years. However, challenges still remain in applying the above techniques. For example, a cloud radio access network can efficiently coordinate large-scale resource scheduling and Base Band Unit (BBU) pool allocation to reduce interference and improve transmission efficiency, but the front-end link is still insufficient to provide huge capacity requirements. In addition, millimeter waves are receiving wide attention due to their broadband characteristics, and because of the large propagation loss of millimeter wave signals, large-sized antenna arrays are installed in base stations. To reduce hardware cost and energy consumption, sparse Radio Frequency (RF) chain antenna array structures are often employed, which presents greater challenges for millimeter wave communications.
Currently, a fog radio access network (F-RAN) is proposed to address the above challenges. Conventional base stations have signal processing and data storage functions: the base station can pre-select the most frequently requested files to a local cache, so that the overhead of the front end is reduced, and the delay is reduced. Aiming at the problem of front-end overhead, a two-stage transmission scheme based on cache comes along, the scheme forms a sum rate maximization problem in each stage of transmission and develops two types of centralized and decentralized optimization algorithms to solve the formed problems, but the scheme does not consider transmission delay; aiming at the problem of transmission delay, a loose coupling structure and a beamforming optimization algorithm appear firstly, but only a single base station model is considered in the algorithm. Next, a combined base station cluster and beamforming optimization scheme is presented, which researches dynamic base station cluster and multicast beamforming problems according to a buffer state to minimize network total cost, only considers Spectrum Efficiency (SE) and Energy Efficiency (EE) optimization problems, and does not research minimization delay. And then, an optimization scheme of data hybrid cache layout appears, and the scheme researches the optimization problem of the data hybrid cache layout in the coordinated relay network. On the other hand, there is also a placement and delivery strategy that effectively reduces the delay, which considers only a single base station model, by studying the fundamental limits of high snr metrics from an information theory perspective and referring them as normalized delivery time. Subsequently, a joint optimal resource allocation and probabilistic cache design for communication between devices in a heterogeneous network with full-duplex relay appears, and an advanced cache protocol and a low-complexity algorithm are proposed, which do not consider a wireless front-end link. In addition, hybrid analog/digital precoding designs are also a challenge in millimeter wave communications. Several advanced design concepts for this problem are: firstly, analog precoding is designed according to a predefined codebook, then an equivalent channel is obtained according to the designed analog precoding, and digital precoding is designed by utilizing Zero Forcing (ZF) technology or convex optimization theory.
Disclosure of Invention
In view of the defects in the prior art, the present invention provides a method and apparatus for reducing transmission delay in a misty radio access network, and due to the intensive deployment of base stations in millimeter wave communication, coordinated transmission between base stations is necessary. A novel F-RAN structure of mixed millimeter wave/microwave communication based on a femto base station cluster is provided, and the problem of minimized transmission delay can be solved.
In a first aspect, the present invention provides a method for reducing transmission delay in a fog radio access network, the method comprising:
s1: establishing a millimeter wave F-RAN system model based on FBSC, and proposing a hybrid analog/digital precoding optimization problem by taking minimized transmission delay as a target;
s2: the minimization delay problem is translated into two separate optimization problems: the mixed precoding design problem of the FBSs and the precoding design problem of the base station;
s3: aiming at the problem of mixed precoding design of FBSs, a coordinated simulation precoding design scheme is provided;
s4: when the mixed precoding problem of the FBSs is optimized, converting non-convex optimization constraints into convex optimization constraints, optimizing digital precoding by adopting a continuous convex approximation iterative algorithm, and solving by adopting a similar iterative algorithm aiming at the precoding design problem of the base station to obtain the minimized transmission delay;
preferably, the step S1 specifically includes:
s11: according to the system parameters: 1 central processing unit (CP),
Figure BDA0002527631580000031
FBSCs. The central processor comprises a microwave band base station equipped with an S (S is more than or equal to K) antenna, a BBU pool and a plurality of large-scale content servers, each FBSC comprises an FBSH equipped with a single antenna,
Figure BDA0002527631580000032
equipped with millimeter wave FBSs
Figure BDA0002527631580000033
An antenna connected to a dedicated RF chain, an
Figure BDA0002527631580000034
And each user establishes a millimeter wave F-RAN system model based on the FBSC.
The content or file required by user is cached in the content server of central processor
Figure BDA0002527631580000035
Represent, and assume that all files are the same size. At the same time, using binary variables
Figure BDA0002527631580000036
Buffer file in l FBS representing m FBSC
Figure BDA0002527631580000037
Can be expressed as:
Figure BDA0002527631580000038
s12: the transmission delays include front-end link transmission (from the central processing units to the FBSHs) delay and access link transmission (from the FBSs to the subscribers) delay. The transmission delay expression of the optimization target user (m, n) is as follows:
Figure BDA0002527631580000039
in the formula (I), the compound is shown in the specification,
Figure BDA00025276315800000310
indicates a file desired by the user (m, n), and c indicates a file size.
If the file required by user (m, n) is cached in the mth FBSC, all FBSs transmit the file to the user in coordination, and the received signal can be represented as
Figure BDA00025276315800000311
The achievable rate of the user is calculated as
Figure BDA00025276315800000312
In the formula
Figure BDA00025276315800000313
The achievable rate of the mth FBSH is calculated as
Figure BDA00025276315800000314
In the formula
Figure BDA00025276315800000315
Preferably, the step S2 specifically includes:
the goal is to minimize the total transmission delay by optimizing the analog/digital precoding, which can be expressed as:
Figure BDA0002527631580000041
Figure BDA0002527631580000042
Figure BDA0002527631580000043
wherein, tm，n(l) Represents tm，nThe ith element. The constraints include power constraints for each FBS and power constraints for the central processor central base station. The above problem is in its original form difficult to solve directly. The precoding design of each FBSC and the base station in the central processor is relatively independent, and the above problems can be divided into the following two optimization problems:
Figure BDA0002527631580000044
hybrid precoding design problem of FBSs
Figure BDA0002527631580000045
Figure BDA0002527631580000046
Figure BDA0002527631580000047
Precoding design problem for base station
Figure BDA0002527631580000048
Figure BDA0002527631580000049
Respectively solve the problems mentioned above
Figure BDA00025276315800000410
And
Figure BDA00025276315800000411
two problems, namely, the problem of minimizing transmission delay can be solved.
Preferably, the step S3 specifically includes:
aiming at optimization problem
Figure BDA00025276315800000415
F in analog precodinglOnly quantized phases can be used in practical applications. Assuming b bit quantization phase shift, FlNon-zero elements belonging to
Figure BDA00025276315800000412
In addition, due to
Figure BDA00025276315800000413
Analog precoding can be designed to maximize array gain
Figure BDA00025276315800000414
Namely, it is
Figure BDA0002527631580000051
Preferably, the step S4 specifically includes:
when the hybrid precoding problem of the FBSs is optimized, the non-convex optimization constraint is converted into the convex optimization constraint, and the solved problem can be converted into the convex optimization problem which is solved as follows:
Figure BDA0002527631580000052
Figure BDA0002527631580000053
Figure BDA0002527631580000054
Figure BDA0002527631580000055
Figure BDA0002527631580000056
the continuous convex approximation iterative algorithm is adopted to optimize the problem, and the transmission delay is minimized based on the idea.
In a second aspect, the present invention provides an apparatus for reducing transmission delay in a fog radio access network, the apparatus comprising:
the modeling module is used for establishing a millimeter wave F-RAN system model based on FBSC, and proposing a hybrid analog/digital precoding optimization problem by taking minimized transmission delay as a target;
a problem decomposition module that converts the minimization delay problem into two separate optimization problems: the mixed precoding design problem of the FBSs and the precoding design problem of the base station;
the scheme design module is used for providing a coordinated simulation precoding design scheme aiming at the mixed precoding design problem of the FBSs;
the optimization solving module is used for converting the non-convex optimization constraint into the convex optimization constraint when optimizing the mixed precoding problem of the FBSs, and optimizing the digital precoding by adopting a continuous convex approximation iterative algorithm; aiming at the precoding design problem of the base station, solving by adopting a similar iterative algorithm to obtain the minimized transmission delay;
preferably, the modeling module specifically includes:
a system model modeling module, 1 central processing unit,
Figure BDA0002527631580000057
FBSCs. The central processor comprises a microwave band base station equipped with an S (S is more than or equal to K) antenna, a BBU pool and a plurality of large-scale content servers, each FBSC comprises an FBSH equipped with a single antenna,
Figure BDA0002527631580000061
equipped with millimeter wave FBSs
Figure BDA0002527631580000062
An antenna connected to a dedicated RF chain, an
Figure BDA0002527631580000063
And each user establishes a millimeter wave F-RAN system model based on the FBSC.
And a transmission delay module, wherein the transmission delay comprises front-end link transmission (from the central processing unit to the FBSHs) delay and access link transmission (from the FBSs to the user) delay. The transmission delay expression of the optimization target user (m, n) is as follows:
Figure BDA0002527631580000064
in the formula (I), the compound is shown in the specification,
Figure BDA0002527631580000065
indicates a file desired by the user (m, n), and c indicates a file size. Perfect Channel State Information (CSI) is assumed to exist in the central processor and the FBSCs. The content or file required by user is cached in the content server of central processor
Figure BDA0002527631580000066
Indicate, and assume that all files are the same size.
Meanwhile, all FBSCs are relatively independent and do not share the cached content. Content may be shared between FBSs within each FBSC over high speed cables, i.e., multiple FBSs cooperatively serve subscribers on each FBSC. Using binary variables
Figure BDA0002527631580000067
Buffer file in l FBS representing m FBSC
Figure BDA0002527631580000068
Can be expressed as:
Figure BDA0002527631580000069
if the file required by user (m, n) is cached in the mth FBSC, all FBSs transmit the file to the user in coordination, and the received signal can be represented as
Figure BDA00025276315800000610
The achievable rate of the user is calculated as
Figure BDA00025276315800000611
In the formula
Figure BDA00025276315800000612
The achievable rate of the mth FBSH is calculated as
Figure BDA00025276315800000613
In the formula
Figure BDA00025276315800000614
Preferably, the problem decomposition module specifically includes:
the goal is to minimize the total transmission delay by optimizing the analog/digital precoding, which can be expressed as:
Figure BDA0002527631580000071
Figure BDA0002527631580000072
Figure BDA0002527631580000073
wherein, tm，n(l) Represents tm，nThe ith element. The constraints include power constraints for each FBS and power constraints for the central processor central base station. The above problem is in its original form difficult to solve directly. The precoding design of each FBSC and the base station in the central processor is relatively independent, and the above problems can be divided into the following two optimization problems:
Figure BDA0002527631580000074
mixed precoding design module of FBSs (fiber Bragg gratings)
Figure BDA0002527631580000075
Figure BDA0002527631580000076
Figure BDA0002527631580000077
Precoding design problem for base station
Figure BDA0002527631580000078
Figure BDA0002527631580000079
Are respectively designed as above
Figure BDA00025276315800000710
And
Figure BDA00025276315800000711
two modules, the problem of minimizing transmission delay can be solved.
Preferably, the scheme design module specifically includes:
aiming at optimization problem
Figure BDA00025276315800000712
F in analog precodinglOnly quantized phases can be used in practical applications. Assuming b bit quantization phase shift, FlNon-zero elements belonging to
Figure BDA00025276315800000713
In addition, due to
Figure BDA00025276315800000714
Analog precoding can be designed to maximize array gain
Figure BDA00025276315800000715
Namely, it is
Figure BDA00025276315800000716
Second, the n-th element vector of the analog precoding
Figure BDA0002527631580000081
Meanwhile, in order to guarantee fairness for users, each user must be allocated at least one F to maximize array gain.
Preferably, the optimization solving module specifically includes:
when the hybrid precoding problem of the FBSs is optimized, the non-convex optimization constraint is converted into the convex optimization constraint, and the solved problem can be converted into the convex optimization problem which is solved as follows:
Figure BDA0002527631580000082
Figure BDA0002527631580000083
Figure BDA0002527631580000084
Figure BDA0002527631580000085
Figure BDA0002527631580000086
the continuous convex approximation iterative algorithm is adopted to optimize the problem, and the transmission delay is minimized based on the idea.
According to the technical scheme, the method and the device for reducing the transmission delay of the fog radio access network have the advantages that the algorithm has high convergence speed, and the proposed network structure not only can effectively reduce the transmission delay, but also can reduce the overhead of a system.
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In order to more clearly illustrate the embodiments or technical solutions of the present invention in the prior art, the drawings used in the description of the embodiments or prior art are briefly introduced below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for reducing transmission delay in a misty radio access network according to the present invention;
FIG. 2 is a schematic diagram of a FBSC-based millimeter wave F-RAN system model;
fig. 3 is a scheduling flow diagram in an FBSC-based F-RAN;
FIG. 4 is a schematic diagram of delay versus number of iterations;
FIG. 5 is a simulation comparison graph of delay and maximum transmission power of a base station;
fig. 6 is a schematic structural diagram of an apparatus for reducing transmission delay of a misty radio access network according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a method for reducing transmission delay in a misty radio access network according to an embodiment of the present invention includes the following steps:
s1: establishing a millimeter wave F-RAN system model based on FBSC, and proposing a hybrid analog/digital precoding optimization problem by taking minimized transmission delay as a target;
s2: the minimization delay problem is translated into two separate optimization problems: the mixed precoding design problem of the FBSs and the precoding design problem of the base station;
s3: aiming at the problem of mixed precoding design of FBSs, a coordinated simulation precoding design scheme is provided;
s4: when the mixed precoding problem of the FBSs is optimized, converting non-convex optimization constraints into convex optimization constraints, and optimizing digital precoding by adopting a continuous convex approximation iterative algorithm; aiming at the precoding design problem of the base station, solving by adopting a similar iterative algorithm to obtain the minimized transmission delay;
as shown in fig. 2, the method of the present embodiment may be applied to a mmwave F-RAN communication system based on FBSC, and the method mainly aims at a process of acquiring a file by a user in an indoor scene.
In this embodiment, the specific process of step S1 is as follows:
s11: for a cache-supporting F-RAN system, the system consists of a central processor and
Figure BDA0002527631580000091
FBSCs, and microwave as front-end chain carrier. The central processing unit includes: the system comprises a microwave band base station provided with S (S is more than or equal to K) antennas, a BBU pool and a plurality of large-scale content servers. Each FBSC comprises: a FBSH equipped with a single antenna,
Figure BDA0002527631580000101
Millimeter wave FBSs equipment
Figure BDA0002527631580000102
An antenna connected to a dedicated RF chain and
Figure BDA0002527631580000103
and (4) users. In the indoor scenario, the FBSH is installed outdoors and connected to the indoor FBSs via high speed cables. In addition, perfect channel state information is assumed to exist in the central processor and the FBSCs. The content or file required by user is cached in the content server of central processor
Figure BDA0002527631580000104
Indicate, and assume that all files are the same size.
Meanwhile, all FBSCs are relatively independent and do not share the cached content. However, content may be shared between FBSs within each FBSC via high speed cables, i.e., multiple FBSs cooperatively serve subscribers on each FBSC. Using binary variables
Figure BDA0002527631580000105
Buffer file in l FBS representing m FBSC
Figure BDA0002527631580000106
Can be expressed as:
Figure BDA0002527631580000107
in a clear view of the above, it is known that,
Figure BDA0002527631580000108
or
Figure BDA0002527631580000109
Indicating that different FBSs cache different files.
S12: the transmission delays include front-end link transmission (from the central processing units to the FBSHs) delay and access link transmission (from the FBSs to the subscribers) delay. Here, it is assumed that the FBSC must wait for the arrival of the requested file that is not processed before transmitting all the requested files to the user. The transmission delay of a user (m, n) can be calculated as:
Figure BDA00025276315800001010
in the formula (I), the compound is shown in the specification,
Figure BDA00025276315800001011
indicates a file desired by the user (m, n), and c indicates a file size.
On one hand, if the file required by user (m, n) is cached in the ith FBSC, all FBSs transmit the file to the user in coordination, and the received signal may be represented as:
Figure BDA00025276315800001012
in the formula
Figure BDA00025276315800001013
At the same time
Figure BDA00025276315800001014
Representing the channel parameters from FBS (m, l) to user (m, n),
Figure BDA00025276315800001015
it is indicated that the digital pre-coding,
Figure BDA00025276315800001016
represents a user (m, n)) The transmission signal of (a) is transmitted,
Figure BDA0002527631580000111
representing independent identically distributed additive white gaussian noise. Analog precoding FmCan be expressed as Fm＝Diag(fm，1，fm，2，...，fm，L) Wherein
Figure BDA0002527631580000112
Denotes the analog precoding at FBS (m, l) with the same amplitude
Figure BDA00025276315800001112
But in different phases.
In equation (3), the first term is the desired signal and the second term is the trunking interference. Inter-cluster interference is not considered here because millimeter wave communications are typically noise limited. Furthermore, in an indoor scenario, signal interference between two different indoor locations is negligible. Thus, the achievable rate for the user is calculated as:
Figure BDA0002527631580000113
in the formula
Figure BDA0002527631580000114
On the other hand, if a file required by the user (m, n) is not cached in the mth FBSC, the file first needs to be converted from the central processor to the mth FBSH through the front-end link of the microwave band. The signal received at the mth FBSH can be expressed as:
Figure BDA0002527631580000115
in the formula (I), the compound is shown in the specification,
Figure BDA0002527631580000116
respectively representing channel coefficients and precoding vectorsAnd a transmission signal from the central processor to the mth FBSH. The achievable rate for the mth FBSH is calculated as:
Figure BDA0002527631580000117
in the formula
Figure BDA0002527631580000118
In this embodiment, the specific process of step S2 is as follows:
first, assuming that the state information and required files are predetermined, the goal is to minimize the total transmission delay by optimizing the analog/digital pre-coding, which can be expressed as:
Figure BDA0002527631580000119
Figure BDA00025276315800001110
Figure BDA00025276315800001111
wherein, tm，n(l) Represents tm，nThe ith element. (8) Equation (1) represents the power constraint of each FBS, and equation (9) represents the power constraint of the BS in the central processor. The problem (7) is in its original form difficult to solve directly.
Secondly, the precoding design of each FBSC and the base station in the central processor is relatively independent, and the problem (7) can be divided into the following two optimization problems:
Figure BDA0002527631580000121
Figure BDA0002527631580000122
in this embodiment, the specific process of step S3 is as follows:
first solving for each FBSC
Figure BDA0002527631580000123
For F in analog precoding equation (10)mIn practical application, only quantized phase can be used. Assuming b bit quantization phase shift, FlNon-zero elements belonging to
Figure BDA0002527631580000124
In addition, due to
Figure BDA0002527631580000125
Analog precoding can be designed to maximize array gain
Figure BDA0002527631580000126
Namely, it is
Figure BDA0002527631580000127
Second, the n-th element vector of the analog precoding
Figure BDA0002527631580000128
Meanwhile, in order to guarantee fairness for users, each user must be allocated at least one FBS in order to maximize an array gain.
Next, new variables are introduced
Figure BDA0002527631580000129
Equation (12) for a medium variablem，nThe following optimization problems can be translated:
Figure BDA00025276315800001210
Figure BDA00025276315800001211
Figure BDA00025276315800001212
(8)
however, due to the non-convex constraint of equation (15), equation (13) remains difficult to solve by introducing a new variable { ω }m，nThe problem can be converted into:
Figure BDA0002527631580000131
Figure BDA0002527631580000132
Figure BDA0002527631580000133
(8)(14)
equation (17) remains a non-convex constraint in the new problem, then, assume
Figure BDA0002527631580000134
Is a feasible solution, a small constraint is defined:
Figure BDA0002527631580000135
then, the following results are obtained:
Figure BDA0002527631580000136
therein, sigmam，n＝hm，nFm(hm，nFm)HIn addition, the first and second substrates are, in addition,m，nωm，nthe upper bound of (A) is:
Figure BDA0002527631580000137
in the formula (I), the compound is shown in the specification,
Figure BDA0002527631580000138
and
Figure BDA0002527631580000139
are respectively omegam，nAndm，nthe value of the ith iteration. Finally equation (17) can be translated into the following convex constraint:
Figure BDA00025276315800001310
in this embodiment, the specific process of step S4 is as follows:
the problem sought can be converted to solve the following convex optimization problem:
Figure BDA00025276315800001311
s.t.(8)(14)(18)(21)
a convex solver may be used to solve the problem (22). The algorithm is summarized as follows: to solve the original problem (16), an iterative solution of the optimal value { v } is requiredl，k}，{βl，k}，{θl，kAnd { tau } andl，kthrough (22). In addition, since { v is obtainedl，k}，{βl，k}，{θl，kAnd { tau } andl，kit is at each iteration that the optimal solution is solved (22), and iteratively updating these variables will reduce or maintain the value of the objective function (16). Due to the limited transmit power, the proposed iterative algorithm will converge to at least one locally optimal solution. In addition, similar algorithms can be employed to solve
Figure BDA00025276315800001312
This process is omitted due to the limited space.
The proposed resource allocation and scheduling procedure of the FBSC-based F-RAN is summarized as shown in fig. 3. It can be seen that the central processor does not need to optimize global resource allocation, and thus the overhead of the central processor can be reduced. On the other hand, each FBSH can optimize and schedule local resources only by acquiring local channel state information. Therefore, the proposed network structure can not only effectively reduce the transmission delay, but also reduce the overhead of the system.
Thus, the method design work for reducing the transmission delay of the fog radio access network is completed.
The simulation result analysis of the present embodiment will be given below.
Fig. 4 shows the convergence performance of the proposed algorithm, assuming that there are 3 FBSCs L and 4 FBSs M in each FBSC. The base station is equipped with 32 antennas and each FBS is equipped with 16 antennas. Assume that K is 4 users in each FBSC. The noise power is set to-100 dBm. The maximum transmit power of each FBS is set to 40 dBm. For simplicity, the size of each file is normalized to a uniform size, one file per user. While assuming that the caching time for each content is long enough so that the user can obtain the cached content before deletion. Here, it is assumed that files required by the user are cached in the local FBSCs. It can be seen that the proposed iterative algorithm can achieve convergence after multiple iterations, thereby ensuring the effectiveness of the algorithm.
Fig. 5 shows the relationship between the transmission delay and the transmission power of the base station under different schemes. The "number of cached files" refers to the number of files cached in each FBSC. When the number of cached files is 4, this means that files required by the user are all cached in the FBSC. Thus, there is no front-end link delay, only access link delay. It can be seen that the latency increases as the number of cached files decreases. It will be readily appreciated that some files must be fetched from the central processor, which results in additional front-end link delay. In addition, the conventional RAN structure is compared in the figure (i.e. no buffering), and it is clear that the delay is the largest without buffering in the base station.
Fig. 6 is a schematic structural diagram of an apparatus for reducing transmission delay in a misty radio access network according to an embodiment of the present invention, including: the modeling module is used for establishing a millimeter wave F-RAN system model based on FBSC, and proposing a hybrid analog/digital precoding optimization problem by taking minimized transmission delay as a target; a problem decomposition module for transforming the minimization delay problem into two separate optimization problems: the mixed precoding design problem of the FBSs and the precoding design problem of the base station; the scheme design module is used for providing a coordinated simulation precoding design scheme aiming at the mixed precoding design problem of the FBSs; the optimization solving module is used for converting the non-convex optimization constraint into the convex optimization constraint when optimizing the mixed precoding problem of the FBSs, and optimizing the digital precoding by adopting a continuous convex approximation iterative algorithm; aiming at the precoding design problem of the base station, a similar iterative algorithm is adopted for solving, and the minimum transmission delay is obtained.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims (10)

1. A method for reducing transmission delay in a misted radio access network, the method comprising:
s1: establishing a millimeter wave F-RAN system model based on FBSC, and proposing a hybrid analog/digital precoding optimization problem by taking minimized transmission delay as a target;
s2: the minimization delay problem is translated into two separate optimization problems: the mixed precoding design problem of the FBSs and the precoding design problem of the base station;
s3: aiming at the problem of mixed precoding design of FBSs, a coordinated simulation precoding design scheme is provided;
s4: when the mixed precoding problem of the FBSs is optimized, converting non-convex optimization constraints into convex optimization constraints, and optimizing digital precoding by adopting a continuous convex approximation iterative algorithm; aiming at the precoding design problem of the base station, a similar iterative algorithm is adopted for solving, and the minimum transmission delay is obtained.
2. The method as claimed in claim 1, wherein the step S1 specifically includes:
s11: according to the system parameters: 1 central processing unit (CP), M (M ≧ 1,., M }) FBSCs comprising a microwave band base station equipped with S (S ≧ K) antennas, a BBU pool, and several large content servers, each FBSC comprising an FBSH equipped with a single antenna, L (L ≧ 1,.., L }) millimeter wave FBSs equipped with K (K ═ 1,.., K }) antennas connected to dedicated RF chains, and N (N ═ 1,.., N }) users, establishing a FBSC-based millimeter wave F-RAN system model;
s12: the transmission delay includes the front-end link transmission (from the central processor to the FBSHs) delay and the access link transmission (from the FBSs to the user) delay, and the transmission delay expression of the optimized target user (m, n) is as follows:
Figure FDA0002527631570000011
in the formula, Fm,nIndicates a file desired by the user (m, n), and c indicates a file size.
3. The method as claimed in claim 1, wherein the step S2 specifically includes:
the precoding design of each FBSC and the base station in the central processor is relatively independent, and the above problems can be divided into the following two optimization problems:
p1: hybrid precoding design problem of FBSs
Figure FDA0002527631570000021
Figure FDA0002527631570000022
P2: precoding design problem for base station
Figure FDA0002527631570000023
Figure FDA0002527631570000024
The above two problems of P1 and P2 are solved separately, i.e. the problem of minimizing transmission delay can be solved.
4. The method as claimed in claim 1, wherein the step S3 specifically includes:
simulating F in precoding for optimization problem P1lIn practical applications only quantized phase can be used, assuming b bit quantized phase shift, FlNon-zero elements belonging to
Figure FDA0002527631570000025
In addition, due to
Figure FDA0002527631570000026
Analog precoding can be designed to maximize array gain
Figure FDA0002527631570000027
Namely, it is
Figure FDA0002527631570000028
5. The method as claimed in claim 1, wherein the step S4 specifically includes:
when the mixed precoding problem of the FBSs is optimized, the non-convex optimization constraint is converted into the convex optimization constraint, the digital precoding is optimized by adopting a continuous convex approximation iterative algorithm, and the transmission delay is minimized based on the idea.
6. An apparatus for reducing transmission delay in a misted radio access network, the apparatus comprising:
the modeling module is used for establishing a millimeter wave F-RAN system model based on FBSC, and proposing a hybrid analog/digital precoding optimization problem by taking minimized transmission delay as a target;
a problem decomposition module that converts the minimization delay problem into two separate optimization problems: the mixed precoding design problem of the FBSs and the precoding design problem of the base station;
the scheme design module is used for providing a coordinated simulation precoding design scheme aiming at the mixed precoding design problem of the FBSs;
the optimization solving module is used for converting the non-convex optimization constraint into the convex optimization constraint when optimizing the mixed precoding problem of the FBSs, and optimizing the digital precoding by adopting a continuous convex approximation iterative algorithm; aiming at the precoding design problem of the base station, a similar iterative algorithm is adopted for solving, and the minimum transmission delay is obtained.
7. The apparatus of claim 6, wherein the modeling module specifically comprises:
a system model modeling module, wherein the system model modeling module comprises 1 central processing unit (CP), M (M) { 1.,. M }) FBSCs, the central processing unit comprises a microwave band base station equipped with an S (S ≧ K) antenna, a BBU pool and several large content servers, each FBSC comprises an FBSH equipped with a single antenna, L (L) { 1.,. L }) millimeter wave FBSs equipped with K (K) { 1.,. K }) antennas connected to a dedicated RF chain, and N (N ═ 1.,. N }) users, and the FBSC-based millimeter wave F-RAN system model is established;
a transmission delay module, wherein the transmission delay comprises front-end link transmission (from the central processor to the FBSHs) delay and access link transmission (from the FBSs to the users) delay, and the transmission delay expression of the optimized target user (m, n) is as follows:
Figure FDA0002527631570000031
in the formula, Fm,nIndicates a file desired by the user (m, n), and c indicates a file size.
8. The apparatus of claim 6, wherein the problem decomposition module specifically comprises:
p1: mixed precoding design module of FBSs (fiber Bragg gratings)
Figure FDA0002527631570000041
Figure FDA0002527631570000042
P2: precoding design problem for base station
Figure FDA0002527631570000043
Figure FDA0002527631570000044
The above two modules P1 and P2 are designed separately, so as to solve the problem of minimizing transmission delay.
9. The apparatus of claim 6, wherein the scheme design module specifically comprises:
simulating F in precoding for optimization problem P1lIn practical applications only quantized phase can be used, assuming b bit quantized phase shift, FlIs non-zeroItem elements belong to
Figure FDA0002527631570000045
In addition, due to
Figure FDA0002527631570000046
Analog precoding can be designed to maximize array gain
Figure FDA0002527631570000047
Namely, it is
Figure FDA0002527631570000048
10. The apparatus of claim 6, wherein the optimization solving module specifically comprises:
when the mixed precoding problem of the FBSs is optimized, the non-convex optimization constraint is converted into the convex optimization constraint, the digital precoding is optimized by adopting a continuous convex approximation iterative algorithm, and the transmission delay is minimized based on the idea.
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