CN102413093A - Method for estimating orthogonal frequency division multiplexing (OFDM) network capacity - Google Patents
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Abstract
The invention discloses a method for estimating orthogonal frequency division multiplexing (OFDM) network capacity. The method comprises the following steps of: 101, selecting a specific network scheme and relevant parameters; 102, defining transformation of signal-to-noise ratio (SINR) as SINRtrans; 103, acquiring a channel activity linear function ai according to a slope D and an intercept coefficient G; 104, calculating the channel activity a of a single user according to the channel activity linear function ai; 105. determining the total upper/lower channel activity; 106, checking whether the total upper/lower channel activity is less than 1; 107, if the total upper/lower channel activity is greater than 1, determining that the network capacity is overloaded, removing the relevant parameters, and re-entering the step 101; and 108, if the total upper/lower channel activity is less than 1, determining that the network capacity can be used for service, storing the relevant parameters and re-entering the step 101.
Description
Technical Field
The invention relates to the technical field of data communication, in particular to a capacity calculation method for a wireless network adopting adaptive modulation and coding and orthogonal frequency division multiplexing technology, and specifically relates to an OFDM (orthogonal frequency division multiplexing) network capacity estimation method.
Background
In order to evaluate an existing network or when a wireless network plans a network structure, the capacity and coverage of the entire network or parts of the network and the expected load of the network must be determined. Such a calculation is highly desirable for setting antenna parameters, modifying and matching network elements, and constructing an entirely new wireless network. Capacity describes the potential data throughput in a communication network and the number of users that can be served through the network. Typically, a wireless communication network comprises a number of base stations or antenna stations, each covering a fixed area. When a wireless network user is located in these coverage areas, the network is connected to at least one antenna through a service. Therefore, the location of the station and the antenna parameter setting have a great influence on the capacity of the network and the efficiency of the entire network. To optimize these network parameters, various issues such as the number and location of users, the type of services provided, the user requirements, interference and noise between network devices, and other further issues are considered.
For data transmission, the signal of the wireless link is modulated onto a carrier signal. This may be done by changing the phase, frequency or amplitude of the carrier. Examples of digital modulation techniques include Phase Shift Keying (PSK), Frequency Shift Keying (FSK), and Amplitude Shift Keying (ASK). In phase shift keying, the transmitted signal is modulated by changing the phase of the reference signal. Each of the defined number of phases corresponds to a unique bit pattern forming a symbol defining the bits that a digital signal is allowed to contain. The demodulator at the receiving end can extract the original signal by phase detection or phase inversion. There are also many phases available for phase modulation, such as binary phase shift keying using two phases and quadrature phase shift keying using four phases. Similarly, data transmission by frequency shift keying is achieved by varying the output frequency of the carrier signal, e.g., between two BFSK or more discrete frequencies. Amplitude keying transmits a signal with the frequency and phase unchanged, changing the amplitude, for example, using two different levels of amplitude to represent binary 0's and 1's. More well-known modulation methods, such as Quadrature Amplitude Modulation (QAM), use two carriers of different phases for amplitude modulation. The term "quadrature" refers to the switching of these carriers at 90 ° phase. Further techniques and combinations may be envisaged. In addition, various encoding techniques make the signal more suitable for transmission, which will include improving transmission quality and accuracy, modifying the spectrum of the signal, increasing the amount of information, providing error detection and correction, and security of the data. Many coding schemes are well established and widely used in techniques such as forward error correction.
Each modulation and coding method has its own advantages such as bandwidth implementation, as well as fault and interference tolerance. The modulation and coding scheme therefore has a significant impact on the data transmission rate of the wireless communication network. Adaptive modulation and coding (AMC, also called link adaptation) exploits this technical feature. With AMC, the modulation and coding scheme for data transmission in a subsequent communication link is determined according to the currently obtained signal quality and the current channel conditions. This can be achieved by feeding back the quality of the signal transmitted by the transmitter, or assuming that the received signal approximates the transmitted signal. Some coding schemes may support high transmission rates or data throughput, while others increase interference rejection and reduce bit error rates at the expense of bit rate. The system may select the appropriate modulation and coding scheme in real time to optimize the signal-to-interference-plus-noise ratio (SINR), i.e., the signal quality of the wireless link. When the SINR drops below a predefined threshold value, the modulation method should be changed in order to obtain a better SINR. Other parameters associated with the communication link or protocol may also vary with the modulation and coding scheme.
The OFDM, another modulation method for data transmission, is not limited to wireless communication networks. OFDM is a modulation method based on multiple orthogonal subcarriers. Each sub-carrier is modulated at a low symbol rate by the above-described modulation method such as QAM or PSK. Orthogonality prevents cross-talk between subcarriers despite the close proximity of the frequency bins of the subcarriers.
The concept of OFDM is equally applicable to an access scheme, i.e., OFDMA (orthogonal frequency division multiplexing multiple access). The basic approach is to assign different OFDM sub-carriers to different users. However, OFDM may also be combined with other access schemes, such as Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), and Code Division Multiple Access (CDMA).
Typical networks using OFDM/OFDMA are: LTE (long term evolution), which is a mainstream technology of the latter 3G mobile communication; WiMAX (worldwide interoperability for microwave access), which aims to provide wireless data transmission over long distances; and Flash-OFDM (fast low latency seamless handover OFDM access), packet data exchange based mobile communication networks. The basic principles of these communication networks and related technical standards are not discussed in detail herein.
The above described AMC is suitable for OFDM systems, and each orthogonal sub-carrier uses adaptive modulation and coding, which further improves the stability of the link. Of course, AMC may also be applied to all or some of the subcarriers simultaneously.
In an OFDM-based network, the number of users served by one antenna depends to a large extent on the interference of neighboring antennas. When the interference is large, the resulting signal-to-noise ratio is small, and thus AMC selects a modulation scheme with less throughput but higher noise stability. The interference from other antennas in the network, in turn, depends on their location, setting, and loading, among other things. The load of one antenna in turn depends on the number of users served by the antenna and the interference from other antennas. Therefore, the transmission and user capacity of each antenna cannot be considered individually, but rather a system of coupling equations should be used to take into account all antenna and user factors. Because the number of users and the number of user positions greatly exceed possible antenna positions, the existence of the user positions in the corresponding equation enables the solution and the hybridization of the coupling equation set. Consider, for example, a network containing 100 to 10000 antenna locations, with up to 1000 million user locations to be considered. This makes the performance estimation of the communication network a lengthy solution process for a system of numerical equations.
In a UMTS (universal mobile telecommunications system) wireless network, the basic situation is similar. However, it is known that adaptive power control employed in UMTS networks can be linearized, so that the average effect of the user position need only be taken into account, and the user position can be removed from the system of coupling equations, greatly simplifying the system of equations. Usually only about 100 to 10000 equations remain, which can be easily solved by numerical iterative algorithm, thereby obtaining a simple and fast UMTS network capacity estimation method.
The method employed in the UMTS system described above cannot be used in OFDM networks, since OFDM networks have no adaptive power control mechanism and all signals employ constant transmit power. Therefore, only complex and time consuming simulation techniques are currently used to calculate the capacity of an OFDM network.
Disclosure of Invention
The invention aims to provide an OFDM network capacity estimation method, which is realized by adopting the following technical scheme:
an OFDM network capacity estimation method, characterized by comprising the steps of:
103, obtaining a channel activity linear function a through the slope D and the intercept coefficient Gi；
104, from the activity linear function aiCalculating the channel activity a of a single user;
Further, in step 102,
。
further, in step 103, the channel activity is linear function
。
Further, in step 105, the calculation formula of the total uplink/downlink channel activity is respectively,
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings. The detailed description of the present invention is given in detail by the following examples and the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 shows a schematic diagram of a standard wireless network according to the present invention.
Fig. 2 is an example of a modulation and coding scheme, SINR, and data throughput.
Fig. 3 shows the channel activity and SINR plotted against corresponding linear approximations.
Fig. 4 shows the specific steps of the OFDM network capacity estimation method of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 shows a standard architecture of a wireless communication network by means of several antennas c. The location of the antenna in this example is arbitrarily chosen, and the inventive method optimizes the antenna location by calculating the potential diversity of antenna locations and capacities in the case of deployment. The figure shows only c1To c4The number of antennas, n, is practically unlimited in the application of the invention. The area around each antenna is divided into individual pixels for analysis, each pixel being an area element. Each pixel may have different parameters such as region type (city, county, …). At each pixel, a number of users ui (or user terminal) requests a service of the wireless network. User uiMay be fixed or mobile within the location. The network will provide one or more services each with different parameter criteria such as bit error rate, traffic requirements, etc. The services may include data services, voice services, and the like. The demand for the number of users and the type of service may be derived from the current usage of the network or based on previous usage and an estimate of the average user behavior. An antenna cnThe area of coverage is defined as a cell, e.g. the circle around the antenna in fig. 1. In this example, only one possible state or one snapshot of the network is given, and all potential user locations must be considered in the network performance evaluation.
Given the above parameters, a channel load or channel activity can be determined. Channel activity is defined as the ratio of the necessary throughput to the available throughput. The channel activity of uplink/downlink is defined separately or individually for each user according to the user's requirement for data transmission rate. Uplink refers to from the mobile terminal or user equipment to the antenna, while downlink refers to from the antenna to the user terminal. The throughput that is available or can be provided depends on the signal to interference and noise ratio SINR, which in turn depends dynamically on the modulation and coding scheme provided. The larger the SINR value, the higher the current bit transmission rate. In addition, the user moving speed also has a certain influence on the AMC mechanism, and the moving speed of the user can be faster if the bandwidth is larger under the same SINR. In addition, the SINR also relates to the relative position of the user and the antenna or base station. Users close to the antenna generally achieve higher SINR than users on the boundary. Fig. 2 gives example values of AMC modulation scheme, data throughput and SINR and their correlation.
Therefore, according to the embodiment of the present invention, a mapping relationship between the SINR value and the channel activity may be defined. The mapping may be derived from known (or measured) SINR values and data throughputs obtained based on different coding and modulation schemes. The invention introduces a SINR transformation defined as the power of 10 (-SINR/10) or
The SINR units are in dB.
When the SINR is determinedtransWhen mapping to channel activity at a given user rate v, channel activity and SINR can be derivedtransApproximately linear relationship of (a). Fig. 3 shows several data points and their linear relationship. From the above mapping, two user rate dependent coefficients D and G can be derived, which define a single useriAverage channel activity of aiLinear function of (c):
ai = Di + Gi ∙ SINRtrans = Di + Gi /10SINRi/10 （2）
d and G are constants related to user rate, D defines the y-intercept of the linear channel activity function, and G gives the slope; a isiIs the channel activity, SINR, of each useriIs the signal to interference plus noise ratio of a single user.
In some embodiments D and G are obtained by linear fitting of the channel activity and SINR measurements, as shown in fig. 2. Fig. 3 shows a linear mapping from the channel activity values to the SINR transform values. The straight line fit of the data points in fig. 3 shows that this linear approximation has no significant error. In other embodiments, the coefficients of the linear function may also be calculated by the ratio of the bit energy to the noise density (i.e., E)b/N0) And calculating the transmission activity factor. In many digital communication systems Eb/N0The value is used to specify the minimum power required for channel transmission. The transmission activity factor represents a ratio of a transmission time of a signal in a channel to a designated time interval, and thus the value is in the range of 0 to 1.
The coefficients D and G (and thus the channel activity) depend not only on the user rate but also on the type of service and whether the user is located indoors or outdoors. The coefficients of the up/down channels are also different, so that an average channel activity a is defined for the down channeli dlAnd a correlation coefficient Ddl And GdlThe same is true for the upstream.
For both antennas c and d, the total uplink/downlink channel activity is determined by the sum of the channel activities of all users served by that antenna. The result is the following equation:
wherein,
(in mW) is at the antennaInterference power at c, defined as
Equations (3) and (4) determine the total downlink and uplink channel activity for antenna c. The coefficients U and V will be discussed and defined in more detail below; in any case, own refers to the relevant parameters for the antenna serving the current channel, while other describes the relevant parameters for other antennas in the wireless network.
Is the channel activity of the control channel and,
is the received noise power within the coverage area of antenna c. By solving these linear equations, the capacity of a network can be estimated. The numerical solution of the system of linear equations can be obtained quickly through a small number of iterations, and the iterative method is not discussed in detail here.
When a of the uplink or downlink channelcA value greater than 1 (a)c >1) This means that the corresponding cell c is overloaded and the antenna will not be able to serve all users in the coverage area. Thus, a of the uplink and downlink channelscThe value must simultaneously satisfy the condition of less than 1. This helps to plan a high performance network to provide the necessary services for sufficient users to meet the requirements of user-level quality of service. It is also possible to avoid overload situations in certain cells by adjusting network parameters.
As can be seen from equations (3) to (5), in the downlink channel, the influence of the other antenna d is determined by the coefficientsV d otherAnd adIncluded in the overall channel activity of antenna c; on the uplink channel, this effect is taken into account in the interference powerI cAnd the inside. In equations (3) and (5), the summation takes into account the networkAll antennas except antenna c.
The parameters used in the equations are defined as follows:
the summation of equations (6) to (11) is for all the set S of users served by a given antenna ccTo complete. h isiIs the noise power, P, of the receiving device of user ic dlIs the downlink received power, P, received by user i from antenna cc ulIs uplink received power in units of mW.
The above is just one example of these correlation coefficients. In other embodiments, such as with directional antennas, no interference will occur in areas other than the direction of transmission of the antenna, and therefore these coefficients may be set to 0.
The above described linear approximation of channel activity and the introduction of SINR transform values greatly simplifies the calculation of channel activity/loading for wireless networks. A large number of interdependent, non-linear complex equations are replaced with only a small number of linear equations. This allows a simple and fast calculation of coverage and efficiency for a certain network setting.
The above discussion assumes that the antenna position is predefined and that some position information of the user. The above method can also be applied to any antenna combination when there are multiple possible antenna positions to be calculated. An optimal solution is obtained by comparing all the calculated results (based on a given demand situation).
Fig. 4 shows the specific steps of the OFDM network capacity estimation method of the present invention. In general, various possible wireless network networking schemes need to be considered and the best scheme is determined according to its quality of service (QoS) and the number of users served. The adjustable parameters of the networking scheme include the antenna position when planning a new network, and other parameters such as transmission power, offered services, service specifications, carrier frequency, etc.
A specific network scenario and associated parameters are first selected in step 101. The parameters for planning and optimizing use may be parameters of an existing network or calculated on the basis of other networks. In step 102, the SINR transform defined in equation (1) above is determined. With this SINR transformation, a linear approximation of the channel activity is obtained in step 103 by determining the slope and intercept coefficients. As described above, this coefficient may be obtained from a linear fit of the channel activity to the SINR transform value mapping, the resulting linear function describing the channel activity. The channel activity of the individual user is determined in step 104. The total uplink/downlink channel activity is determined in step 105 by equations (3) and (4) considering all antennas in the network and all users under different modes of service per antenna. For planning and optimization purposes it will be checked in step 106 whether the total up/down channel activity is less than 1. A value greater than 1 indicates that the cell is overloaded and a value less than 1 indicates that all users can be served under the given parameters. Thus, if the selected network scheme shows overload, the relevant parameters are removed in step 107, new parameters are selected, and the calculation method is re-run. When the network scenario shows an acceptable capacity value, the relevant parameters are stored in step 108. And finally, comparing all the stored acceptable network schemes in terms of quality, cost and efficiency, and selecting the optimal network scheme.
The above embodiments are only for illustrating the technical concept and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention accordingly, and not to limit the protection scope of the present invention accordingly. All equivalent changes or modifications made in accordance with the spirit of the present disclosure are intended to be covered by the scope of the present disclosure.
Claims (4)
1. An OFDM network capacity estimation method, characterized by comprising the steps of:
step 101, selecting a specific network scheme and related parameters;
step 102. define SINR transform to SINRtrans；
103, obtaining a channel activity linear function a through the slope D and the intercept coefficient Gi；
104, from the channel activity linear function aiCalculating the channel activity a of a single user;
step 105, determining the total up/down channel activity;
step 106, checking whether the total up/down channel activity is less than 1;
step 107, if the total up/down channel activity is greater than 1, the network capacity is overloaded, the relevant parameters are removed, and then the step 101 is re-entered;
step 108, if the total up/down channel activity is less than 1, the network capacity can be used for service, the relevant parameters are saved, and then step 101 is re-entered.
2. The OFDM network capacity estimation method of claim 1, wherein: in a step 102, the process is executed,。
3. the OFDM network capacity estimation method of claim 1, wherein: in step 103, a channel activity linear function。
4. The OFDM network capacity estimation method of claim 1, wherein: in step 105, the calculation formulas of the total uplink/downlink channel activity are respectively,
，
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| WO2007121340A1 (en) * | 2006-04-13 | 2007-10-25 | Qualcomm Incorporated | Dynamic carrier sensing thresholds |
| CN101207892A (en) * | 2006-12-19 | 2008-06-25 | 中国移动通信集团设计院有限公司 | Method for planning component channel of OFDM system |
| EP1726105B1 (en) * | 2004-03-05 | 2012-12-05 | Qualcomm, Incorporated | Multi-antenna receive diversity control in wireless communications |
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| EP1967030B1 (en) * | 2005-12-02 | 2013-02-27 | Telefonaktiebolaget LM Ericsson (publ) | Method and apparatus for allocating bandwidth in a wireless communication system |
| CN101384056B (en) * | 2008-06-23 | 2012-09-26 | 中兴通讯股份有限公司 | Scheduling method for service division sector access by uplink packet |
| CN101466139B (en) * | 2008-12-31 | 2010-09-01 | 中兴通讯股份有限公司 | Method and system for scheduling high speed ascending packet access business divided antenna |
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| EP1726105B1 (en) * | 2004-03-05 | 2012-12-05 | Qualcomm, Incorporated | Multi-antenna receive diversity control in wireless communications |
| CN1741412A (en) * | 2004-08-27 | 2006-03-01 | 清华大学 | Sub-channel distributing method in radio network |
| WO2007121340A1 (en) * | 2006-04-13 | 2007-10-25 | Qualcomm Incorporated | Dynamic carrier sensing thresholds |
| CN101207892A (en) * | 2006-12-19 | 2008-06-25 | 中国移动通信集团设计院有限公司 | Method for planning component channel of OFDM system |
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