I. Field
The following description relates generally to wireless communications, and, amongst other things, to evaluating transmitter performance.
II. Background
Wireless networking systems have become a prevalent means by which a majority of people worldwide has come to communicate. Wireless communication devices have become smaller and more powerful in order to meet consumer needs and to improve portability and convenience. Consumers have become dependent upon wireless communication devices such as cellular telephones, personal digital assistants (PDAs) and the like, demanding reliable service and expanded areas of coverage.
A typical wireless communication network (e.g., employing frequency, time, and code division techniques) includes one or more base stations that provide a coverage area and one or more mobile (e.g., wireless) user devices that can transmit and receive data within the coverage area. A typical base station can simultaneously transmit multiple data streams for broadcast, multicast, and/or unicast services, wherein a data stream is a stream of data that can be of independent reception interest to a user device. A user device within the coverage area of that base station can be interested in receiving one, more than one or all the data streams carried by the composite stream. Likewise, a user device can transmit data to the base station or another user device.
Forward Link Only (FLO) technology has been developed by an industry group of wireless communication service providers to utilize the latest advances in system design to achieve the highest-quality performance. FLO technology is intended for a mobile multimedia environment and is suited for use with mobile user devices. FLO technology is designed to achieve high quality reception, both for real-time content streaming and other data services. FLO technology can provide robust mobile performance and high capacity without compromising power consumption. In addition, the technology reduces the network cost of delivering multimedia content by decreasing the number of base station transmitters that are needed to be deployed. Furthermore, FLO technology based multimedia multicasting is complimentary to the wireless operators' cellular network data and voice services, delivering content to the same mobile devices.
Base station transmitter performance is vital to the overall performance of a wireless system. In particular, in a wireless system utilizing FLO technology, which can utilize fewer transmitters, the performance of each transmitter is critical. Therefore, transmitter performance should be carefully monitored before and after installation.
The following presents a simplified summary of one or more embodiments in order to provide a basic understanding of such embodiments. This summary is not an extensive overview of all contemplated embodiments, and is intended to neither identify key or critical elements of all embodiments nor delineate the scope of any or all embodiments. Its sole purpose is to present some concepts of one or more embodiments in a simplified form as a prelude to the more detailed description that is presented later
In accordance with one or more embodiments and corresponding disclosure thereof, various aspects are described in connection determining the modulation type of a received signal to facilitate monitoring transmitter performance in a wireless communication environment. The modulation types can be evaluated over a subset of subcarriers having a consistent modulation type such as a half-interlace, to reduce the possibility of an erroneous modulation type determination to an extremely low level. A metric can be generated for each modulation type that indicates the likelihood of a particular modulation type for the subset of subcarriers. The modulation type can be selected based upon the metric and modulation symbols consistent with the modulation type can be used for the subset.
According to a related aspect, a method for determining a modulation type of a received signal for a set of subcarriers that have a consistent modulation type can comprise determining the closest modulation symbol to the received signal for each of a plurality of modulation types for each subcarrier in the set of subcarriers, generating a metric for each of the modulation types based upon the difference between the closest modulation symbol and the received signal for each subcarrier in the set of subcarriers and selecting the modulation type of the received signal from the modulation types based upon the metric. The method can further comprise representing the received signal and modulation symbols for the modulation types as points in a complex plane, where the closest modulation symbol is determined based upon the distance in the complex plane between the received signal point and the modulation symbol point. The difference between the closest modulation symbol and the received signal can be measured based upon the distance between the received signal point and the modulation symbol point in the complex plane. Furthermore, generating a metric for each modulation type can comprise summing the distance square between the received signal point and the closest modulation symbol point for the modulation type for each subcarrier in the set of subcarriers. The method can further comprise utilizing the closest modulation symbol for the selected modulation type for each subcarrier to generate a metric indicative of transmitter performance.
According to yet another aspect, an apparatus that determines a modulation type of a received signal for a set of subcarriers that have a consistent modulation type comprises a processor that determines a modulation symbol closest to the received signal for each of a plurality of modulation types for each subcarrier in the set of subcarriers, generates a metric for each of the modulation types based upon the difference between the closest modulation symbol and the received signal for each subcarrier in the set of subcarriers and selects the modulation type of the received signal from the modulation types based upon the metric. The apparatus can further comprise a memory, coupled to the processor, that stores information related to the plurality of modulation types. In a further aspect the processor can represent the received signal and modulation symbols for the plurality of modulation types as points in a complex plane, where the closest modulation symbol is determined based upon the distance in the complex plane between the received signal point and the modulation symbol point. In addition, the processor can sum the distance square between the received signal point and the closest modulation symbol point for the modulation type for each subcarrier in the set of subcarriers to generate the metric.
According to another aspect, an apparatus for determining a modulation type of a received signal for a set of subcarriers that have a consistent modulation type, can comprise means for determining a modulation symbol closest to the received signal for each of a plurality of modulation types for each subcarrier in the set of subcarriers, means for generating a metric for each of the modulation types based upon the difference between the closest modulation symbol and the received signal for each subcarrier in the set of subcarriers and means for selecting the modulation type of the received signal from the modulation types based upon the metric. The apparatus can further comprise means for representing the received signal as a constellation point and means for representing modulation symbols for the modulation types as constellation points, where the closest modulation symbol is determined based upon the distance between the received signal point and the modulation symbol point. In addition, the apparatus can comprise means for summing the distance square between the received signal point and the closest modulation symbol point for the modulation type for each subcarrier in the set of subcarriers.
Yet another aspect relates to a computer-readable medium having stored thereon computer-executable instructions for determining a modulation symbol closest to a received signal for each of a plurality of modulation types for each subcarrier in a set of subcarriers that have a consistent modulation type, generating a metric for each of the modulation types based upon the difference between the closest modulation symbol and the received signal for each subcarrier in the set of subcarriers and selecting the modulation type of the received signal from the modulation types based at least in part upon the metric. The computer-readable medium can also have stored thereon instructions for representing the received signal as a point in a complex plane and representing modulation symbols for the plurality of modulation types as points in the complex plane, the closest modulation symbol is determined based upon the distance in the complex plane between the received signal point and the modulation symbol point. In addition, the computer-readable medium can also have stored thereon instructions for summing the distance square between the received signal point and the closest modulation symbol point for the modulation type for each subcarrier in the set of subcarriers to generate the metric.
Yet another aspect relates to a processor that executes instructions for determining a modulation type of a received signal for a set of subcarriers that have a consistent modulation type, the instructions comprise determining a modulation symbol closest to the received signal for each of a plurality of modulation types for each subcarrier in the set of subcarriers, generating a metric for each of the plurality of modulation types based upon the difference between the closest modulation symbol and the received signal for each subcarrier in the set of subcarriers and selecting the modulation type of the received signal from the plurality of modulation types based upon the metric. The processor can execute instructions for representing the received signal as a point in a complex plane and representing modulation symbols for the plurality of modulation types as points in the complex plane, where the closest modulation symbol is determined based upon the distance in the complex plane between the received signal point and the modulation symbol point. In addition, the processor can execute instructions for summing the distance square between the received signal point and the closest modulation symbol point for the modulation type for each subcarrier in the set of subcarriers.
To the accomplishment of the foregoing and related ends, the one or more embodiments comprise the features hereinafter fully described and particularly pointed out in the claims. The following description and the annexed drawings set forth in detail certain illustrative aspects of the one or more embodiments. These aspects are indicative, however, of but a few of the various ways in which the principles of various embodiments may be employed and the described embodiments are intended to include all such aspects and their equivalents.
Various embodiments are now described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident, however, that such embodiment(s) may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to facilitate describing one or more embodiments.
As used in this application, the terms “component,” “system,” and the like are intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between two or more computers. Also, these components can execute from various computer readable media having various data structures stored thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, and/or across a network such as the Internet with other systems by way of the signal).
Furthermore, various embodiments are described herein in connection with a user device. A user device can also be called a system, a subscriber unit, subscriber station, mobile station, mobile device, remote station, access point, base station, remote terminal, access terminal, user terminal, terminal, user agent, or user equipment (UE). A user device can be a cellular telephone, a cordless telephone, a Session Initiation Protocol (SIP) phone, a wireless local loop (WLL) station, a PDA, a handheld device having wireless connection capability, or other processing device connected to a wireless modem.
Moreover, various aspects or features described herein may be implemented as a method, apparatus, or article of manufacture using standard programming and/or engineering techniques. The term “article of manufacture” as used herein is intended to encompass a computer program accessible from any computer-readable device, carrier, or media. For example, computer readable media can include but are not limited to magnetic storage devices (e.g., hard disk, floppy disk, magnetic strips . . . ), optical disks (e.g., compact disk (CD), digital versatile disk (DVD). . . ), smart cards, and flash memory devices (e.g., card, stick, key drive . . . ).
The FLO wireless system has been designed to broadcast real time audio and video signals, as well as non-real time services. The FLO transmission is carried out utilizing tall, high power transmitters to ensure wide coverage in a given geographical area. It is common to deploy multiple transmitters in markets to ensure that the FLO signal reaches a significant portion of the population in a given market.
Typically, FLO technology utilizes orthogonal frequency division multiplexing (OFDM). Frequency division based techniques, such as OFDM, generally separate the frequency spectrum into distinct channels by splitting the frequency spectrum into uniform chunks of bandwidth. For example, the frequency spectrum or band allocated for wireless cellular telephone communication can be split into 30 channels, each of which can carry a voice conversation or, for digital service, digital data. Each channel can be assigned to only one user device or terminal at a time. OFDM effectively partitions the overall system bandwidth into multiple orthogonal frequency channels. An OFDM system may use time and/or frequency division multiplexing to achieve orthogonality among multiple data transmissions for multiple terminals. For example, different terminals may be allocated different channels, and the data transmission for each terminal may be sent on the channel(s) allocated to this terminal. By using disjoint or non-overlapping channels for different terminals, interference among multiple terminals may be avoided or reduced, and improved performance may be achieved.
Base station transmitter performance is vital to the overall performance of a wireless system, particularly a wireless system utilizing FLO technology. Therefore, a system and/or method for testing and evaluating transmitters should be accurate and cost-effective. Transmitters can be tested at the factory or before installation to qualify the transmitters for installation. In addition, transmitters can be tested or monitored after installation to ensure continued transmitter performance. The system and methods described herein can be used to evaluate transmitter performance in wireless environments including, but not limited to, a wireless environment broadcasting FLO, digital multimedia broadcasting (DMB), digital video broadcasting (DVB), DVB-H, DVB-T, DVB-S or DVB-S2 signals.
Referring now to
Processor 106 can provide various types of user interfaces for display component 116. For example, processor 106 can provide a graphical user interface (GUI), a command line interface and the like. For example, a GUI can be rendered that provides a user with a region to view transmitter information. These regions can comprise known text and/or graphic regions comprising dialogue boxes, static controls, drop-down-menus, list boxes, pop-up menus, as edit controls, combo boxes, radio buttons, check boxes, push buttons, and graphic boxes. In addition, utilities to facilitate the presentation such as vertical and/or horizontal scroll bars for navigation and toolbar buttons to determine whether a region will be viewable can be employed.
In an example, a command line interface can be employed. For example, the command line interface can prompt (e.g., by a text message on a display and an audio tone) the user for information by providing a text message or alert the user that the transmitter performance is outside of predetermined bounds. It is to be appreciated that the command line interface can be employed in connection with a GUI and/or application program interface (API). In addition, the command line interface can be employed in connection with hardware (e.g., video cards) and/or displays (e.g., black and white, and EGA) with limited graphic support, and/or low bandwidth communication channels.
In addition, the evaluation system can generate an alert to notify users if the transmitter performance is outside of an acceptable range. The alert can be audio, visual or any other form intended to attract the attention of a user. The evaluation system can include a predetermined set of values indicating the boundaries of the acceptable range. Alternatively, users may dynamically determine the boundaries. In addition, the evaluation system can generate an alert based upon a change in transmitter performance.
Referring now to
To evaluate transmitter performance, the RF signal data produced by exciter 312 can be monitored. Possible sources of transmitter error or noise include up-sampling, digital to analog conversion and RF conversion. The signal data can be sampled at the output of the exciter and at the output of the channel filter, such that the RF signal can be sampled either before or after power amplification and filtering. If the signal is sampled after amplification, the signal should be corrected for power amplification nonlinearity.
Referring now to
Referring now to
The transmitter evaluation system can generate one or more metrics to evaluate the performance of the transmitter. Metrics generated by processor include, but are not limited to, modulation error ratio (MER), group delay or channel frequency response. In particular, MER measures the cumulative impact of flaws within the transmitter. MER for a subcarrier is equivalent to signal to noise ratio (SNR) for a subcarrier. MER can be generated using the following equation:
Here, I is the in phase value of the measured constellation point, Q is the quadrature value of the measured constellation point and N is the number of subcarriers. ΔI is the difference between the in phase values of the transmitted and measured signals and ΔQ is the difference between the quadrature values of the transmitted and measured signals.
Referring to
Referring now to
At 602, the signal is received or sampled from the transmitter. The received signal can be written as follows:
Yk=Hk·Pk+Nk
Here, Hk, is the channel of a subcarrier, k. A known modulation symbol, Pk, can be transmitted on the subcarrier k. Complex additive white Gaussian noise (AWGN) with a zero mean and a variance of σ2 can be represented by Nk.
The possible modulation types for the subcarriers can include, but are not limited to, quadrature phase-shift keying (QPSK), layered QPSK with an energy ratio of 6.25 (ER6.25), 16 QAM (quadrature amplitude modulation) and layered QPSK with energy ratio of 4.0 (ER4). When analyzed based upon the constellation point of view, the layered QPSK with energy ratio 4.0 is identical to that of 16 QAM. Constellation point of view, as used herein, refers to utilization of constellation diagrams to represent digital modulation schemes in the complex plane. Modulation symbols can be represented as constellation points on a constellation diagram.
An initial frequency domain channel estimate for a subcarrier can be determined at 604. An initial channel estimate for each subcarrier can be obtained by dividing the signal Yk by a known symbol, Pk. Selected symbols can be transmitted, such that the symbols are known for the purpose of performance evaluation. For example, during testing prior to installation, a particular pattern of symbols can be transmitted such that the symbol for each subcarrier is predictable and therefore known. Determination of modulation symbols when the transmitted modulation symbols are unknown is discussed in detail below. The initial frequency domain channel estimate for each subcarrier, k, of every OFDM symbol, l, within a superframe, can be represented as follows:
Here, Zk,l is an initial channel estimate for subcarrier k and OFDM symbol l.
An average channel estimate is determined at 606. The channel estimate Zk,l of subcarrier can be refined by averaging over the entire superframe, such that:
Here, k is the OFDM symbol index and L is the number of the OFDM symbols in the superframe (e.g., 1188 symbols). Since the variance of the average channel estimate is smaller than the variance of the initial channel estimate, the variance of the average channel estimate can be used to approximate the channel gain of the subcarrier during metric generation.
At 608, a metric for evaluating the transmitter performance is generated. For example, the MER for a subcarrier k can be generated. Assuming that the transmitted symbols are known, noise variance can be estimated by the following:
Here, the Xk,m represents the transmitted symbol for subcarrier k. It can be shown that the in-phase and quadrature components of the noise, Wk, is approximately:
if random variable Bk is the estimated noise variance, such that:
The MER can be determined based upon the average channel estimate for the subcarrier, the symbol transmitted on the subcarrier and the signal received for the subcarrier. A MER can be calculated based upon the following exemplary equation:
Here, Ĥk is the average channel estimate for subcarrier k, Pk is the symbol transmitted on the subcarrier, Yk is the received signal and Nk is the AWGN. In addition, MER can be calculated by averaging over all of the subcarriers.
Additional metrics can be generated to evaluate transmitter performance. For example metrics can include frequency response and group delay. Group delay of subcarrier k can be calculated as follows:
Here, k=1, . . . , 4000; Δφk,k−1 is the phase difference between subcarriers k and k−1; and Δfk,k−1 is the frequency difference between subcarriers k and k−1.
Referring now to
At 710, the channel estimates are averaged over the superframe to increase accuracy. The average channel estimate can be determined using the coarse channel estimates, the channel estimates based upon the modulation symbols or both sets of channel estimates. A metric for evaluating the transmitter based at least in part upon the channel estimates can be generated at 712. For example, the MER for each subcarrier can be determined based upon the channel estimates and the modulation symbol, as described in detail above.
Referring now to
In addition, since there is (2, 6) pattern staggering of pilot symbols for the OFDM symbols of a super frame, both the 500 pilots of the current OFDM symbol and the 500 pilots of the previous OFDM symbol can be used to obtain the frequency domain channel estimation. In such cases, the channel estimates of the pilot subcarriers are generated using the pilot symbols and the channel estimates of the rest of the subcarriers are obtained by linear interpolation or extrapolation.
Referring now to
Typically, the modulation type remains consistent during a half interlace. In general the modulation type does not change within an interlace due to constraints in the FLO protocol. An interlace, as used herein is a set of subcarriers (e.g., 500 subcarriers). Consequently, a half-interlace is one half of an interlace (e.g., 250 subcarriers). However, for rate-⅔ layered modulation, the modulation type can be switched to QPSK within an interlace when operating in base-layer only mode. Even under these conditions the modulation type within each half-interlace remains constant. Therefore, the modulation type for each half-interlace can be determined using majority voting. To determine the modulation type for a half-interlace or any other subset of subcarriers having a consistent modulation type, the modulation symbol, and consequently the modulation type, can be determined for each subcarrier within the subset. A majority vote based on the modulation type corresponding to each subcarrier can be used to determine the modulation type for the subset. For example, for a half-interlace including 250 subcarriers, the modulation type for 198 of the subcarriers could be consistent with the QPSK modulation type and the modulation symbols for the remaining 52 subcarriers could be consistent with the 16 QAM modulation type. Since the majority of the subcarriers are detected as QPSK, QPSK would be selected as the modulation type for the half-interlace. The 52 subcarriers that were associated with the 16 QAM modulation type can be reevaluated and reassigned to QPSK modulation symbols based upon their location in the constellation diagram. Comparing the subcarrier modulation symbol to the modulation type for the half-interlace and reevaluating subcarrier modulation symbols as needed increases the accuracy of modulation symbol selection.
Referring now to
Referring now to
The closest modulation symbol constellation point for a modulation type can be determined by calculating the distance between the received signal constellation point and possible modulation symbol constellation points and selecting the modulation symbol constellation point corresponding to the minimum distance. Alternatively, the closest modulation symbol constellation points can be determined using regions. The closest modulation symbol constellation point for a particular modulation type can be determined by partitioning the constellation diagram into regions corresponding to the modulation symbols of the modulation type. Regions are defined such that every point in each region has the property that the distance of such a point to the constellation point of the region is less than or equal to the distance between such point to the constellation point of any other region. The modulation symbol corresponding to the region in which the received signal constellation point is located is selected as the closest modulation symbol constellation point for that particular modulation type.
At 1204, if the distance was not calculated above, the distance between the signal constellation point and each of the closest modulation symbol points is determined for each subcarrier in the subset of subcarriers. Whether the distance was calculated previously or at 1204, a distance value for each modulation type will be associated with each subcarrier. For example, if there are three possible modulation types, each subcarrier in the subset will have three distance values associated with it. Each of the distance values corresponds to one of the three possible modulation types. The distance value can be calculated as the minimum distance square between the closest modulation symbol constellation point for a modulation type and the signal constellation point.
At 1206, a metric is generated for each modulation type over the subset. The metric for a modulation type can be generated by summing the distance square values for each subcarrier in the subset for that modulation type. Alternatively, the metric for a modulation type can be generated by averaging the distance values for each subcarrier in the subset for that modulation type. At 1208, the modulation type can be selected based upon the generated metrics. For example, if the metric is generated by summing the distance square values for each subcarrier in the subset for a modulation type, the selected modulation type should correspond to the metric with the smallest value. Once the modulation type for the subset has been selected, modulation symbols corresponding to the closest modulation symbol points for the selected modulation type can be used as the modulation symbol for the subcarrier at 1210.
The transmitter evaluation systems and methods described herein should also include phase correction, intended to reduce or eliminate error or distortions caused by time frequency offsets. If phase correction is not performed, the channel estimate average can be inaccurate and consequently, the evaluation metrics may be incorrect. Typically, phase correction can be performed prior to the averaging of the channel estimates to correct for phase ramp due to frequency offsets.
Referring now to
Referring now to
Here Rn is the complex amplitude of the nth subcarrier and N is the total number of subcarriers. The frequency of the initial subcarrier is represented by ω0, ωs represents the subcarrier spacing and Δω is the frequency offset. A constant frequency offset will result in a linear phase change with time. A frequency offset that varies linearly with time will result in a parabolic phase change over time. Either a constant or linearly changing frequency offset results in a predictable phase change which can be corrected prior to averaging, as shown in
A linear phase change can be corrected using a first order phase correction algorithm by calculating the slope of phase change. For example, the phase change can be calculated as follows:
Here, Δφk+1=φk+1−φk is the phase change of the channel estimation between two adjacent OFDM symbols, φ0 is the phase of the initial channel estimation, L is the number of OFDM symbols and TOFDM is period.
A parabolic phase change can be corrected using a second order phase correction with a LS algorithm to determine the parameters, a, b and c, of the parabolic function. The estimated phase can be written as follows:
φest=a·t2b·t+c
Here, t is time. The estimated phase can be used to correct the estimated channels prior to averaging.
However, the frequency offset is not necessarily constant or linearly varying. Consequently, the phase change is not necessarily linear or parabolic and predictable. One possible solution for correcting for a variable frequency offset includes separating the time duration into segments and then estimating the phase change for each segment. As a result, the estimated noise variance Bk in the MERk equation described with respect to
Here, N is the number of segments.
The noise term for each channel of each OFDM symbol derived from the received signal can be decomposed into two orthogonal dimensions: amplitude dimension and phase dimension. The noise term in the amplitude dimension can be considered additive white Gaussian noise. The noise term in the phase direction can be considered the sum of the additive white Gaussian noise (AWGN) and the distortion that comes from the frequency offset. The distortion caused by the frequency offset should be eliminated. However, the component of AWGN in the phase dimension should be maintained.
As shown in the methodology 1400 illustrated in
In one extreme case, if the variance of the noise in the amplitude dimension is equal to that of the variance of the noise in the phase dimension, the maximum number of segments is equal to the number of OFDM symbols being processed. Consequently, the noise in the phase dimension will be eliminated as well as the distortion due to frequency offset. As a result, the true value of MER, which includes the noise in the phase dimension, will be equal to the value of the generated MER minus a constant (e.g., 3.01 dB).
It will be appreciated that, in accordance with one or more embodiments described herein, inferences can be made regarding transmission formats, frequencies, etc. As used herein, the term to “infer” or “inference” refers generally to the process of reasoning about or inferring states of the system, environment, and/or user from a set of observations as captured via events and/or data. Inference can be employed to identify a specific context or action, or can generate a probability distribution over states, for example. The inference can be probabilistic—that is, the computation of a probability distribution over states of interest based on a consideration of data and events. Inference can also refer to techniques employed for composing higher-level events from a set of events and/or data. Such inference results in the construction of new events or actions from a set of observed events and/or stored event data, whether or not the events are correlated in close temporal proximity, and whether the events and data come from one or several event and data sources.
According to an example, one or more methods presented above can include making inferences regarding the number of segments to utilize for phase correction. In addition, inferences can be made regarding the data and format to display to a user.
Referring now to
Base station 1602 can also include a transmitter monitor 1624. Transmitter monitor 1624 can sample transmitter output and/or transmitter antenna output and evaluate the performance of transmitter 1620. Transmitter monitor 1624 can be coupled to processor 1614. Alternatively, transmitter monitor 1624 can include a separate processor for processing transmitter output. In addition, transmitter monitor 1624 may be independent of base station 1602.
Base station 1602 can additionally comprise memory 1616 that is operatively coupled to processor 1614 and that can store information related to constellation regions, modulation symbols and/or any other suitable information related to performing the various actions and functions set forth herein. It will be appreciated that the data store (e.g., memories) components described herein can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. By way of illustration, and not limitation, nonvolatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM), which acts as external cache memory. By way of illustration and not limitation, RAM is available in many forms such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM). The memory 1616 of the subject systems and methods is intended to comprise, without being limited to, these and any other suitable types of memory.
Referring now to
TMTR 1720 receives and converts the stream of symbols into one or more analog signals and further conditions (e.g., amplifies, filters, and frequency upconverts) the analog signals to generate a downlink signal suitable for transmission over the wireless channel. The downlink signal is then transmitted through an antenna 1725 to the user devices. At user device 1730, an antenna 1735 receives the downlink signal and provides a received signal to a receiver unit (RCVR) 1740. Receiver unit 1740 conditions (e.g., filters, amplifies, and frequency downconverts) the received signal and digitizes the conditioned signal to obtain samples. A symbol demodulator 1745 demodulates and provides received pilot symbols to a processor 1750 for channel estimation. Symbol demodulator 1745 further receives a frequency response estimate for the downlink from processor 1750, performs data demodulation on the received data symbols to obtain data symbol estimates (which are estimates of the transmitted data symbols), and provides the data symbol estimates to an RX data processor 1755, which demodulates (i.e., symbol demaps), deinterleaves, and decodes the data symbol estimates to recover the transmitted traffic data. The processing by symbol demodulator 1745 and RX data processor 1755 is complementary to the processing by symbol modulator 1715 and TX data processor 1710, respectively, at access point 1705.
On the uplink, a TX data processor 1760 processes traffic data and provides data symbols. A symbol modulator 1765 receives and multiplexes the data symbols with pilot symbols, performs modulation, and provides a stream of symbols. A transmitter unit 1770 then receives and processes the stream of symbols to generate an uplink signal, which is transmitted by the antenna 1735 to the access point 1705.
At access point 1705, the uplink signal from user device 1730 is received by the antenna 1725 and processed by a receiver unit 1775 to obtain samples. A symbol demodulator 1780 then processes the samples and provides received pilot symbols and data symbol estimates for the uplink. An RX data processor 1785 processes the data symbol estimates to recover the traffic data transmitted by user device 1730. A processor 1790 performs channel estimation for each active user device transmitting on the uplink. Multiple user devices may transmit pilot concurrently on the uplink on their respective assigned sets of pilot subcarriers, where the pilot subcarrier sets may be interlaced.
Processors 1790 and 1750 direct (e.g., control, coordinate, manage, etc.) operation at access point 1705 and user device 1730, respectively. Respective processors 1790 and 1750 can be associated with memory units (not shown) that store program codes and data. Processors 1790 and 1750 can utilize any of the methodologies described herein. Respective Processors 1790 and 1750 can also perform computations to derive frequency and impulse response estimates for the uplink and downlink, respectively.
For a software implementation, the techniques described herein may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in memory units and executed by processors. The memory unit may be implemented within the processor or external to the processor, in which case it can be communicatively coupled to the processor via various means as is known in the art.
What has been described above includes examples of one or more embodiments. It is, of course, not possible to describe every conceivable combination of components or methodologies for purposes of describing the aforementioned embodiments, but one of ordinary skill in the art may recognize that many further combinations and permutations of various embodiments are possible. Accordingly, the described embodiments are intended to embrace all such alterations, modifications and variations that fall within the spirit and scope of the appended claims. Furthermore, to the extent that the term “includes” is used in either the detailed description or the claims, such term is intended to be inclusive in a manner similar to the term “comprising” as “comprising” is interpreted when employed as a transitional word in a claim.
This application claims the benefit of U.S. Provisional Application Ser. No. 60/734,885 entitled “HALF INTERLACE BASED SEQUENCE DETECTION ALGORITHM FOR MEDIAFLO TEST RECEIVER,” filed on Nov. 8, 2005. This application is also related to U.S. Provisional Application Ser. No. 60/721,372 entitled “A METHOD FOR MEDIAFLO TRANSMITTER QUALIFICATION,” filed on Sep. 27, 2005. The entireties of the above-referenced applications are incorporated herein by reference.
Number | Date | Country | |
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60734885 | Nov 2005 | US | |
60721372 | Sep 2005 | US |