CN105282061B - The throughput optimization method of PLC system based on OFDM - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03159—Arrangements for removing intersymbol interference operating in the frequency domain
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L27/34—Amplitude- and phase-modulated carrier systems, e.g. quadrature-amplitude modulated carrier systems
- H04L27/38—Demodulator circuits; Receiver circuits
- H04L27/3845—Demodulator circuits; Receiver circuits using non - coherent demodulation, i.e. not using a phase synchronous carrier
- H04L27/3854—Demodulator circuits; Receiver circuits using non - coherent demodulation, i.e. not using a phase synchronous carrier using a non - coherent carrier, including systems with baseband correction for phase or frequency offset
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03821—Inter-carrier interference cancellation [ICI]
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Abstract
The invention discloses a kind of throughput optimization method of the PLC system based on OFDM, comprise the following steps：Transmitting terminal setting uses the maximum transmission power binding occurrence that t easet ofasubcarriers, overall transmission power binding occurrence and each subcarrier allow first, then weight is introduced, it is weight minimization mean square error problem by the throughput-maximized problem equivalent under power constraint, block coordinate descent algorithm and dichotomy iterative is recycled to obtain final power allocation scheme, last transmitting terminal sets the transimission power of each subcarrier according to power allocation scheme, so as to realize that the business of PLC system is transmitted.Due to the optimized throughput problem under power constraint be one can not be direct the problem of, therefore the problem equivalent is weight minimization mean square error problem by ingenious design by the present invention, so that problem is able to use straightforward procedure iterative, so as to maximize the handling capacity of system.
Description
Technical Field
The invention relates to the technical field of Power Line Communication (PLC), in particular to a design of a Power Line Communication system throughput optimization scheme based on Orthogonal Frequency Division Multiplexing (OFDM) technology.
Background
In recent years, the rapid development of information technology has placed higher demands on the development of modern communications. At present, the access of the internet in China has the following bottleneck problem that a backbone network has a bandwidth with a considerable capacity, but the bandwidth of a line used by the access of a user is narrow, so that the transmission rate is greatly limited. Power line communication is considered as a powerful solution to this problem. Power line communication refers to a communication method for transmitting data and media signals using a power line. The PLC technology plays a very important role in building a road of a smart grid with its advantages of high coverage, low communication and laying costs, and the like.
The modulation techniques adopted by power line communication mainly include OFDM, spread spectrum, and conventional QPSK, FSK, etc. While the conventional modulation techniques such as QPSK, FSK, etc. have low band utilization rate and are only suitable for low-speed transmission, and the spread spectrum technique is also difficult to adapt to high-speed transmission because the maximum data transmission rate is limited under the condition that the bandwidth is limited. Therefore, in order to meet the requirement of high-speed transmission, the OFDM technology is one of the most effective methods for solving the problem of low utilization rate of the transmission band, and the technology is widely adopted at present.
In the power line OFDM system, inter-carrier Interference (ICI) and Inter-Symbol Interference (ISI) significantly reduce the performance of the OFDM system, so that the resource management optimization method designed under ideal conditions is less efficient in practical use. For this purpose. The invention aims to focus on the power distribution problem in the presence of Interference, namely Inter-carrier Interference (ICI) and Inter-Symbol Interference (ISI) in a power line OFDM system, optimize the system throughput and improve the system performance by optimizing the transmission power of subcarriers. As is well known, the throughput optimization problem under the power constraint is a non-convex non-linear problem, which is difficult to solve directly. Therefore, the invention constructs a virtual flat attenuation real channel model by ingenious conception, and equates the problem of throughput optimization under the power constraint to the problem of weighted minimum mean square error. Although the problem is still non-convex, the iterative solution can be realized by combining a simple block coordinate descent method and a dichotomy method, and meanwhile, the method can ensure that an objective function is optimized, namely the throughput of the system is monotonously not reduced in the iterative process, so that the aim of optimizing the throughput of the system is fulfilled.
Disclosure of Invention
The invention aims to provide a throughput optimization method of a PLC system based on OFDM aiming at the defects of the prior art.
The purpose of the invention is realized by the following technical scheme: a throughput optimization method of a PLC system based on OFDM comprises the following steps:
step 1: the sending end determines the used subcarrier set A use And find L = | A use L represents the set A use While setting the maximum transmission power constraint value P allowed for each sub-carrier max (m)，m∈A use And a total transmission power constraint value P total ；
Step 2: introduce weight value t m And equating the continuous throughput optimization problem under the power constraint to a weighted minimum mean square error problem, namely:
wherein F 0 Which indicates the spacing between the sub-carriers,the values of the MMSE error estimates are shown,α (m) denotes a channel gain of the mth subcarrier, P (m) denotes a transmission power of the mth subcarrier, and u (m) denotes a channel gain of the mth subcarrier m MMSE equalizer representing mth subcarrier, Γ represents the SNR difference, W represents the interference matrix, where W (m) 0 M) denotes the mth subcarrier pair 0 The interference of the individual sub-carriers, for the noise powerVector of whereinRepresenting the noise power of the mth subcarrier;
and 3, step 3: the problem is solved iteratively by using a block coordinate descent algorithm and a bisection method, namely: initialization: iteration number n =1, MMSE equalizerAnd correspondingWeight ofWherein:andrespectively representing the MMSE equalizer, the MMSE error estimation value and the weight value which are solved by the nth iteration of the mth subcarrier, and then calculating the target value of the weighted minimum mean square error problem
And 4, step 4: updating iteration times n = n +1, and solving a subcarrier transmission power set { P) by using a dichotomy (n) (m)}，P (n) (m) represents the transmission power value of the nth iteration of the mth subcarrier;
and 5: first solve the MMSE equalizerAnd corresponding estimation errorThen, the weight is obtainedThereby finding the target value of the corresponding weighted minimum mean square error problemWherein
Step 6: judgment ofIf yes, wherein epsilon is a decision threshold, if yes, output { P } (n) (m) is the final solution of the original problem, i.e.Wherein P is * (m) represents the m-th sub-carrier final transmission power to find the final throughputWherein Representing a final transmission power allocation vector; otherwise, repeating the steps 4 to 6;
and 7: and the sending end sets the transmission power of each subcarrier according to the final power distribution scheme, so that the service transmission of the PLC system is realized.
Further, the step 4 specifically includes the following sub-steps:
step 4.1: let lagrange multiplier λ =0, according to the equation:
determining the transmission powerDetermine whether a total power constraint is satisfied, i.e.If yes, then orderAnd outputting the solution, wherein:
otherwise, executing the next step;
step 4.2: let λ = λ + L λ Wherein L is λ For step length, obtain correspondingRepeating the steps until a Lagrange multiplier lambda meeting the total power constraint condition is found, and outputting an upper bound lambda of the Lagrange multiplier u ＝λ；
Step 4.3: solving lagrange multipliers, commands, by using the dichotomy ideaWherein λ l The value of =0 is the lower bound of the Lagrange multiplier, and the solution is obtainedJudging whether a total power constraint condition is met, if so, commanding lambda u ＝λOtherwise let λ be l = λ, repeating the step untilWhere ε is the decision threshold, getOrder toAnd outputs the solution.
The invention has the beneficial effects that: the throughput optimization problem of the PLC system based on OFDM is a non-convex nonlinear complex problem which is difficult to solve directly, the throughput optimization problem under power constraint is equivalent to a weighted minimum mean square error problem by constructing a virtual flat attenuation real channel model, and then the problem is solved by adopting a simple block coordinate descent method and a dichotomy idea in an iteration mode, so that the throughput can be ensured to be increased continuously until convergence in the iteration process, and the purpose of optimizing the system performance is achieved.
Drawings
Fig. 1 is a flowchart of a PLC system throughput optimization method based on OFDM according to an embodiment of the present invention.
Fig. 2 is a flowchart of a binary solution transmission power scheme according to the embodiment of the present invention.
Fig. 3 is a convergence diagram of the throughput optimization method according to the embodiment of the present invention.
FIG. 4 is a comparison graph of performance simulation of the embodiment of the present invention.
Detailed Description
In order to make the purpose and effect of the present invention clearer, the following describes the power line OFDM communication system model and the method of the present invention in detail.
Unlike conventional OFDM systems, consider aA single user windowed OFDM system. Assuming that the system has U subcarriers, the total occupied bandwidth is BMHz, and the cyclic prefix length of the OFDM system is T cp s (here, s represents a unit: second): t is cp = GI + RI, where GI is guard interval and RI is roll-off length. In a conventional OFDM system, RI =0 is generally used, but is not equal to zero in a PLC system. Further, the OFDM symbol length is Ts, where T = T 0 +GI，T 0 For the duration of the FFT window, the period,is the subcarrier spacing. Assuming that L subcarriers are used among U subcarriers for data transmission, the nth subcarrier is known from the principle of multicarrier communication system 0 M-th in one OFDM symbol 0 Demodulated samples y (m) of subcarriers 0 ,n 0 ) Can be expressed as:
wherein: alpha (m) 0 ,n 0 )、ICI(m 0 ,n 0 )、ISI(m 0 ,n 0 ) And b (m) 0 ,n 0 ) Respectively represent the n-th 0 M-th in one OFDM symbol 0 Channel gain of individual subcarriers, modulation symbols, inter-carrier interference, inter-symbol interference, and cyclic complex gaussian system noise.
Without loss of generality, considering a block-time invariant channel, equation (1) can be simplified as:
because the number L of subcarriers used in an actual PLC system is relatively large, it can be assumed that interference is normally distributed on L subcarriers according to the central limit theorem. Thus, m is 0 Signal to interference and noise ratio (SINR, S) on subcarriersThe signal to interference plus noise ratio) can be expressed as:
wherein: p (m) 0 ) Is the carrier m 0 The transmission power of the mobile station (c),is a carrier m 0 The noise power of (c).
Correspondingly, carrier m 0 The upper capacity function can be expressed as:
wherein: Γ denotes the signal-to-noise ratio difference.
For convenience, define A use Set of subcarriers used for L, i.e. | A use L, | = L, wherein | a use I represents the set A use The number of elements (c). According to the literature [ Thanh Nhan Vo, karine Amis, thierry Choonavel, pierre Siohan, 'Achievable through Optimization in OFDM Systems in the Presence of Interference and its Application to Power Line Networks' IEEE Transactions On Communications, vol.62, no.5, may 2014]It can be seen that the following equation:
wherein: w (m) 0 M) denotes the m-th subcarrier pair m 0 Interference of one subcarrier, and m 0 ,m∈A use 。
According to the formula (5), is definedIn order to be a vector of the power allocation,for the noise power vector, the matrix W is an interference matrix, i.e.
Thus, the formulae (5) and (3) may be respectively equivalent to:
P I (m 0 )＝[WP](m 0 ) (7)
for power line OFDM communication systems, an important metric scale of system performance is throughput, so the throughput maximization design problem under satisfying the power constraint can be described as:
wherein: p total Representing a total power constraint value, P max (m) maximum transmission power allowed for subcarrier m.
An analysis model knows that the problem (9) is a non-convex non-linear problem and is difficult to directly solve, so the problem (9) is equivalent to a Weighted Minimum Mean Square Error (WMMSE) problem according to a concave-convex transformation idea, and the purpose of optimizing the problem (9) is achieved by optimizing the problem.
First, defineThe method for constructing the virtual flat attenuation real channel model comprises the following steps:
wherein: s m N (0, 1) represents the mth transmitter virtualThe symbols are transmitted and,andrepresenting additive white gaussian noise.
At the m-th position, the first,sub-carriers, we use MMSE equalizer u m To s m Minimum mean-square error estimation (MMSE, min-mean-square-error) is performed, corresponding estimation error e m Can be expressed as:
introduce the weight t m And (4) according to the virtual channel model, the problem (9) is equivalent to the following problem:
from (12) it is known that the problem is still non-convex, but the problem can be solved iteratively using a simple block coordinate descent method, i.e. the idea of fixing one or more variables to solve for another variable, based on which the problem is solved when t is fixed m ，q m Then, u can be obtained from (11) m I.e. MMSE equalizer:
thereby solving to obtain e m ＝1-u m h m q m Then q is fixed m ，e m Find t m Namely:
final fixation of e m ，t m Solving for q m The method comprises the following steps:
according to equation (12), introducing a lagrangian multiplier λ to the total power constraint term to obtain a partial lagrangian function:
and the corresponding dual problem, namely:
max d(λ)
(16)
s.t.λ>0
wherein: the dual function d (λ) is expressed as:
looking at the problem, we find that d (λ) is a convex function and the derivation with respect to λ is:
therefore, in combination with the above formula, we can solve the Lagrange multiplier λ by using the dichotomy, thereby obtaining { q } m In which q is m ，The specific solution is as follows:
decompose problem (17) to concern q m L independent sub-questions, and the mth sub-question is expressed as:
the formula (17) is decomposed into a formula (19),we ignore some and q m Independent constant terms, and since problem (19) is a univariate convex problem, derivation of this problem yields q m The closed-form solution of (a), namely:
wherein:
in summary, the final transmission power of the problem (12) can be obtained by combining the block coordinate descent method and the binary iterative solution, namely, the purpose of optimizing the continuous throughput is achieved.
Referring to fig. 1 and 2, a method for optimizing throughput of a PLC system based on OFDM includes the following steps:
step 1: the sending end determines the used subcarrier set A use And find L = | A use L represents the set A use While setting the maximum allowable transmission power constraint value P of each sub-carrier max (m)，m∈A use And a total transmit power constraint value P total ；
Step 2: introduce weight value t m And equating the continuous throughput optimization problem under the power constraint to a weighted minimum mean square error problem, namely:
wherein F 0 Which indicates the spacing between the sub-carriers,the values of the MMSE error estimates are shown,α (m) denotes a channel gain of the mth subcarrier, P (m) denotes a transmission power of the mth subcarrier, and u (m) denotes a channel gain of the mth subcarrier m MMSE equalizer representing mth subcarrier, Γ represents the SNR difference, W represents the interference matrix, where W (m) 0 M) denotes the m-th subcarrier pair m 0 The interference of the individual sub-carriers, is a noise power vector ofRepresents the noise power of the mth subcarrier;
and 3, step 3: the problem is solved iteratively by using a block coordinate descent algorithm and a dichotomy, namely: initialization: iteration number n =1, MMSE equalizerAnd correspondingWeight ofWherein:andrespectively representing the MMSE equalizer, the MMSE error estimation value and the weight value which are solved by the nth iteration of the mth subcarrier, and then calculating the target value of the weighted minimum mean square error problem
And 4, step 4: updating the iteration number n = n +1, and solving the subcarrier transmission power set { P ] by using a dichotomy (n) (m)}，P (n) (m) represents the transmission power value of the nth iteration of the mth subcarrier;
and 5: first solve the MMSE equalizerAnd corresponding estimation errorThen, the weight is obtainedThereby finding the target value of the corresponding weighted minimum mean square error problemWherein
Step 6: judgment ofIf yes, wherein epsilon is a decision threshold, if yes, output { P } (n) (m) is the final solution of the original problem, i.e.Wherein P is * (m) represents the m-th sub-carrier final transmission power to find the final throughputWherein Representing a final transmission power allocation vector; otherwise, repeating the steps 4 to 6;
and 7: and the transmitting end sets the transmission power of each subcarrier according to the final power distribution scheme, so that the service transmission of the PLC system is realized.
Further, the step 4 specifically includes the following sub-steps:
step 4.1: let lagrange multiplier λ =0, according to the equation:
determining the transmission powerDetermine whether a total power constraint is satisfied, i.e.If yes, then orderAnd outputting the solution, wherein:
otherwise, executing the next step;
and 4.2: let λ = λ + L λ Wherein L is λ For step length, obtain correspondingRepeating the steps until a Lagrange multiplier satisfying the total power constraint condition is foundSub λ, output Lagrange multiplier upper bound λ u ＝λ；
Step 4.3: solving lagrange multipliers, commands, by using the dichotomy ideaWherein λ l The value of =0 is the lower bound of the Lagrange multiplier, and the solution is obtainedJudging whether a total power constraint condition is met, if so, commanding lambda u = λ, otherwise let λ l = λ, repeating the step untilWherein epsilon is a decision threshold value, obtainingOrder toAnd outputs the solution.
Fig. 3 and 4 are simulation verifications of the designed scheme through Matlab. The parameters are specifically set as: bandwidth B from 1.8MHz to 100MHz, sampling time T s ＝0.01us，T 0 ＝40.96us，GI＝5.56us，RI＝4.96us，P max (1)＝…＝P max (L)＝P max = 55dbm/Hz, Γ =4.038 (corresponding SER = 10) -3 )，A use For the first L =100 subcarrier sets (i.e. from the 74 th subcarrier), the step size for solving the Lagrange multiplier upper bound is 1, and the decision threshold is ε =1e-6, and the Interference matrices W and α (m) are all in accordance with the document [ Achievable through Optimization in OFDM Systems in the Presence of Interference and its Application to Power Line Networks [ ]]Similarly set, the noise model is according to the literature [ R.Hashmat, P.Pagani, and T.Chonavel, "Analysis and modeling of background noise for the same MIMO-PLC channels,”in Proc.2012IEEE ISPLC,pp.316–321]Part B of chapter iii in (iv) is obtained by:
wherein: n is a radical of ES For noise power spectral density, a = -140, b = -38.75, c = -0.720 are noise model parameters, f is sampling point frequency, for representation simplicity, we use normalization in the simulation to identify total transmit power constraint values, where the actual total transmit power constraint values aren is any real number greater than 0, and the number of Monte Carlo simulations is 1000.
FIG. 3 is a convergence chart of the PLC system throughput optimization method based on OFDM, wherein an actual total transmission power constraint value is setThe ordinate represents the throughput required by the method, the abscissa represents the number of iterations, three curves in the graph respectively represent convergence graphs obtained under three random channels, and the graph can show that: with the continuous increase of the iteration times, the throughput is continuously increased until the throughput converges to a horizontal straight line, so that the method can ensure that the throughput is continuously increased until the throughput converges, and the iteration times can be converged within 40-60 times.
FIG. 4 is a graph showing the relationship between the total transmission power constraint value and the average throughput, wherein the abscissa represents the total transmission power constraint value (after normalization), and the ordinate represents the average throughput obtained by the method of the present invention, wherein the asterisk curve represents the setting of the present invention
The method is counted, and the circle curve represents the commonly adopted water filling algorithm. It can be seen from the figure that as the constraint value of the total transmission power increases, the average throughput value of the two schemes also increases, especially when the total transmission power P is increased total Equal to or more than 100 (after normalization), the average throughput is not increased any moreRemaining on the same horizontal line means that the total transmission power is no longer an important parameter affecting the average throughput at this time, and the maximum transmission power allowed for each sub-carrier becomes an important parameter affecting it, because the transmission power of each sub-carrier at this time is exactly equal to the maximum transmission power allowed for it. Meanwhile, the trends of the two curves are consistent according to the graph, but the system performance obtained by the design method is still higher than that of a water injection scheme.
Through the performance simulation comparison, the method can realize the maximization of the throughput of the PLC OFDM system, and certainly, the method is not limited to the PLC OFDM system, and the idea can be adopted for the maximization of the rate function, so that the method has immeasurable prospect in the system optimization.
The present invention is not limited to the above-described embodiments, and those skilled in the art can implement the present invention in other various embodiments based on the disclosure of the present invention. Therefore, the design of the invention is within the scope of protection, with simple changes or modifications, based on the design structure and thought of the invention.
Claims (2)
1. A throughput optimization method of a PLC system based on OFDM is characterized by comprising the following steps:
step 1: the sending end determines the used subcarrier set A use And find L = | A use L represents the set a use While setting the maximum transmission power constraint value P allowed for each sub-carrier max (m)，m∈A use And a total transmission power constraint value P total ；
And 2, step: introduce weight value t m And equating the continuous throughput optimization problem under the power constraint to a weighted minimum mean square error problem, namely:
wherein F 0 Which indicates the spacing between the sub-carriers,the values of the MMSE error estimates are shown,α (m) denotes a channel gain of the mth subcarrier, P (m) denotes a transmission power of the mth subcarrier, and u (m) denotes a channel gain of the mth subcarrier m MMSE equaliser representing the m-th subcarrier, Γ representing the signal-to-noise ratio difference, W representing the interference matrix, where W (m) 0 M) denotes the m-th subcarrier pair m 0 The interference of the individual sub-carriers, is a noise power vector, whereinRepresenting the noise power of the mth subcarrier;
and step 3: the problem is solved iteratively by using a block coordinate descent algorithm and a bisection method, namely: initialization: iteration number n =1, MMSE equalizerAnd correspondingWeight ofWherein:andrespectively representing the MMSE equalizer, the MMSE error estimation value and the weight value which are solved by the nth iteration of the mth subcarrier, and then calculating the target value of the weighted minimum mean square error problem
And 4, step 4: updating iteration times n = n +1, and solving a subcarrier transmission power set { P) by using a dichotomy (n) (m)}，P (n) (m) represents the transmission power value of the nth iteration of the mth subcarrier;
and 5: first solve the MMSE equalizerAnd corresponding estimation errorThen, the weight is obtainedThereby finding the target value of the corresponding weighted minimum mean square error problemWherein
Step 6: judgment ofWhether or not the above-mentioned conditions are satisfied,where ε is the decision threshold, if satisfied, output { P (n) (m) }, i.e. the final solution of the original problem, i.e.Wherein P is * (m) represents the m-th sub-carrier final transmission power to find the final throughputWherein Representing a final transmission power allocation vector; otherwise, repeating the steps 4 to 6;
and 7: and the sending end sets the transmission power of each subcarrier according to the final power distribution scheme, so that the service transmission of the PLC system is realized.
2. The method as claimed in claim 1, wherein the step 4 comprises the following sub-steps:
step 4.1: let lagrange multiplier λ =0, according to the equation:
determining the transmission powerDetermine whether a total power constraint is satisfied, i.e.If yes, then orderAnd outputting the solution, wherein:
otherwise, executing the next step;
step 4.2: let λ = λ + L λ Wherein L is λ For step length, obtain correspondingRepeating the steps until a Lagrange multiplier lambda meeting the total power constraint condition is found, and outputting an upper bound lambda of the Lagrange multiplier u ＝λ；
Step 4.3: solving lagrange multipliers, commands, by using the dichotomy ideaWherein λ is l The value of =0 is the lower bound of the Lagrange multiplier, and the solution is obtainedJudging whether a total power constraint condition is met, if so, controlling lambda u = λ, otherwise let λ l = λ, repeat this step untilWhere ε is the decision threshold, getOrder toAnd outputs the solution.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102497259A (en) * | 2011-12-02 | 2012-06-13 | 中国科学院微电子研究所 | Subcarrier allocation method and device applied to power line communication |
| WO2013004319A1 (en) * | 2011-07-05 | 2013-01-10 | Sony Corporation | Power line communication modem, power line communication system and power line communication method |
| CN103414675A (en) * | 2013-03-07 | 2013-11-27 | 华北电力大学 | Single-user quick bit loading method for broadband power line OFDM system |
| CN103701576A (en) * | 2013-06-26 | 2014-04-02 | 国家电网公司 | Power line communication frequency band allocation method and device |
| CN104135769A (en) * | 2014-07-01 | 2014-11-05 | 宁波大学 | Method of OFDMA (Orthogonal Frequency Division Multiple Access) ergodic capacity maximized resource allocation under incomplete channel state information |
-
2015
- 2015-09-09 CN CN201510570058.4A patent/CN105282061B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013004319A1 (en) * | 2011-07-05 | 2013-01-10 | Sony Corporation | Power line communication modem, power line communication system and power line communication method |
| CN102497259A (en) * | 2011-12-02 | 2012-06-13 | 中国科学院微电子研究所 | Subcarrier allocation method and device applied to power line communication |
| CN103414675A (en) * | 2013-03-07 | 2013-11-27 | 华北电力大学 | Single-user quick bit loading method for broadband power line OFDM system |
| CN103701576A (en) * | 2013-06-26 | 2014-04-02 | 国家电网公司 | Power line communication frequency band allocation method and device |
| CN104135769A (en) * | 2014-07-01 | 2014-11-05 | 宁波大学 | Method of OFDMA (Orthogonal Frequency Division Multiple Access) ergodic capacity maximized resource allocation under incomplete channel state information |
Non-Patent Citations (3)
| Title |
|---|
| "一种吞吐量最大化的电力线OFDM分子带自适应算法";蔡丽萍，刘盈，薛先俊;《计算机应用与软件》;20120630;第29卷(第6期);73-77 * |
| "一种基于电力线通信的OFDM自适应比特与功率分配算法";李姣军，曾孝平，张众发;《信息与电子工程》;20070228;第5卷(第1期);15-21 * |
| "低压电力线自适应OFDM系统比特功率分配算法";张锐，刘世辉，赛颖夫;《哈尔滨理工大学学报》;20110831;第16卷(第4期);260-263 * |
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