Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W74/00—Wireless channel access
  • H04W74/002—Transmission of channel access control information
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04B—TRANSMISSION
  • H04B17/00—Monitoring; Testing
  • H04B17/30—Monitoring; Testing of propagation channels
  • H04B17/309—Measuring or estimating channel quality parameters
  • H04B17/345—Interference values
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04J—MULTIPLEX COMMUNICATION
  • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes
  • H04J11/0023—Interference mitigation or co-ordination
  • H04J11/0026—Interference mitigation or co-ordination of multi-user interference
  • H04J11/0036—Interference mitigation or co-ordination of multi-user interference at the receiver
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L27/00—Modulated-carrier systems
  • H04L27/26—Systems using multi-frequency codes
  • H04L27/2601—Multicarrier modulation systems
  • H04L27/2602—Signal structure
  • H04L27/261—Details of reference signals
  • H04L27/2613—Structure of the reference signals
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L27/00—Modulated-carrier systems
  • H04L27/26—Systems using multi-frequency codes
  • H04L27/2601—Multicarrier modulation systems
  • H04L27/2647—Arrangements specific to the receiver only
  • H04L27/2655—Synchronisation arrangements
  • H04L27/2668—Details of algorithms
  • H04L27/2673—Details of algorithms characterised by synchronisation parameters
  • H04L27/2675—Pilot or known symbols
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W28/00—Network traffic management; Network resource management
  • H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
  • H04W28/18—Negotiating wireless communication parameters
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
  • H04W52/04—Transmission power control [TPC]
  • H04W52/18—TPC being performed according to specific parameters
  • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
  • H04W52/241—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account channel quality metrics, e.g. SIR, SNR, CIR or Eb/lo
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
  • H04W52/04—Transmission power control [TPC]
  • H04W52/18—TPC being performed according to specific parameters
  • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
  • H04W52/243—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account interferences
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
  • H04W52/04—Transmission power control [TPC]
  • H04W52/30—Transmission power control [TPC] using constraints in the total amount of available transmission power
  • H04W52/32—TPC of broadcast or control channels
  • H04W52/325—Power control of control or pilot channels
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
  • H04W52/04—Transmission power control [TPC]
  • H04W52/38—TPC being performed in particular situations
  • H04W52/50—TPC being performed in particular situations at the moment of starting communication in a multiple access environment

Definitions

• This relates in general to wireless networks, and in particular to a method and apparatus for estimating signal to interference plus noise ratio for a random access channel of a wireless network.
• UE user equipment
• PRACH physical random access channel
• the preambles used in the PRACH are constant-amplitude Zadoff-Chu (ZC) sequences of a prime length, such that the cyclic auto-correlation of the ZC sequence is an ideal delta function and the cyclic cross-correlation of two ZC sequences with different root sequence indices is a constant of magnitude , where N zc is the ZC sequence length.
• ZC Zadoff-Chu
• the preamble SINR can be estimated at the base station.
• TPC transmit power control
• the estimate should reflect the channel condition on the ULSCH even through the estimation is performed on the PRACH.
• a wireless device includes a preamble detector configured to identify preambles transmitted via a random access channel of a wireless network.
• the preamble detector includes a noise floor estimator.
• the noise floor estimator is configured to estimate, for a given preamble root sequence identified by the preamble detector, a noise floor value as mean energy of received signal samples, excluding detected preamble samples on the given preamble root sequence, below a noise floor threshold assigned to the given preamble root sequence.
• the noise floor estimator is configured to compute the noise floor threshold as a product of: average energy of the received signal samples less total signal energy contained in each cyclic prefix window in which a preamble is detected using the given preamble root sequence; and a predetermined normalized relative noise floor threshold based on a target false preamble detection rate.
• a method includes receiving signals transmitted via a random access channel of a wireless network. Preambles are detected in the received signals. For a given preamble root sequence with any preamble detected, a noise floor value is estimated as mean energy of received signal samples, excluding detected preamble samples on the given preamble root sequence, below a noise floor threshold assigned to the given preamble root sequence.
• the noise floor threshold is computed as a product of: average energy of the received signal samples less total signal energy contained in each cyclic prefix window in which a preamble is detected using the given preamble root sequence; and a predetermined normalized relative noise floor threshold based on a target false preamble detection rate.
• apparatus for implementing a wireless base station includes a preamble detector configured to identify preambles transmitted via a random access channel of a wireless network.
• the preamble detector includes a noise floor estimator.
• the noise floor estimator is configured to estimate, for a given preamble root sequence identified by the preamble detector, a noise floor value as mean energy of received signal samples, excluding detected preamble samples on the given preamble root sequence, below a noise floor threshold assigned to the given preamble root sequence.
• the noise floor estimator is configured to compute the noise floor threshold as a product of: average energy of the received signal samples less total signal energy contained in each cyclic prefix window in which a preamble is detected using the given preamble root sequence; and a predetermined normalized relative noise floor threshold based on a target false preamble detection rate.
• the noise floor estimator is configured to adjust the noise floor value for the given preamble root sequence based on interference energy of all preambles detected using a preamble root sequence other than the given preamble root sequence, for the purpose of SINR estimation for each detected preamble.
• FIG. 1 is a block diagram of a wireless network of various embodiments.
• FIG. 2 is a block diagram of a preamble detector for use in a base station of a wireless network of various embodiments.
• FIG. 3 is a diagram of received signal power samples for a root sequence of various embodiments.
• FIG. 4 is a flow diagram of a method of determining signal to noise and interference ratio (SINR) in a wireless device of various embodiments.
• SINR signal to noise and interference ratio
• a noise floor estimate is used for computing a preamble detection threshold based on a target false preamble detection rate (i.e., target false alarm rate).
• target false preamble detection rate i.e., target false alarm rate.
• the noise floor estimate for a root sequence can include interference from the preambles received for different root sequences.
• the noise floor estimate for the given root sequence also increases. This is due to the fact that the total received power for a root sequence is used for computing the noise floor estimate for preamble detection, which includes the power of all received preambles for the given root sequence.
• Embodiments of the present disclosure provide an improved noise floor estimate for use in signal to interference plus noise ratio (SINR) determination.
• Embodiments generate the improved noise floor estimate by excluding preamble signal energy from the signal energy applied to compute the noise floor estimate.
• embodiments can compute an SINR value for use with the uplink shared channel (ULSCH) that is more accurate than conventional systems.
• ULSCH uplink shared channel
• FIG. 1 is a block diagram of a wireless network 100 of various embodiments.
• the example wireless network includes base stations 101, 102 and 103.
• embodiments of the network 100 may include any number of base stations.
• Each of base stations 101, 102 and 103 is operable over corresponding coverage areas 104, 105 and 106.
• Each base station's coverage area is further divided into cells. In the illustrated network, each base station's coverage area is divided into three cells.
• Handset or other user equipment (UE) 109 is shown in Cell A 108.
• Cell A 108 is within coverage area 104 of base station 101.
• Base station 101 transmits to and receives transmissions from UE 109.
• UE 109 may be handed over to base station 102. Because UE 109 is synchronized with base station 101, UE 109 can employ non-synchronized random access to initiate handover to base station 102.
• Non-synchronized UE 109 also employs non-synchronous random access to request allocation of up-link 111 time or frequency or code resources. If UE 109 has data ready for transmission (such as traffic data, measurements reports, and tracking area updates), UE 109 can transmit a random access signal on up-link 111. The random access signal notifies base station 101 that UE 109 requires up-link resources to transmit the UE's data. Base station 101 responds by transmitting to UE 109 (via down- link 110) a message containing the parameters of the resources allocated for UE 109 up-link transmission along with a possible timing error correction.
• UE 109 After receiving the resource allocation and a possible timing advance message transmitted on down- link 110 by base station 101, UE 109 optionally adjusts its transmit timing and transmits the data on up-link 111 employing the allotted resources during the prescribed time interval.
• UE 109 obtains uplink synchronization by transmitting a preamble to base station 101 via a physical random access channel (PRACH).
• the preamble includes Zadoff-Chu (ZC) sequences of prime length. Such sequences possess ideal periodic autocorrelation and optimum periodic cross-correlation.
• the preamble can be a root ZC sequence or a cyclic shifted version of a root ZC sequence.
• the base stations 101, 102 and 103 include preamble detectors that identify preambles transmitted by a UE, compute SINR for the PRACH, and determine transmit power to be applied by the UE on the Uplink Shared Channel based on the SINR computed for the PRACH.
• the preamble detectors included in the base stations 101, 102 and 103 provide PRACH noise and PRACH SINR values that are more accurate than those provided by convention base stations. Accordingly, the base stations 101, 102 and 103 can determine the transmit power to be applied by the UE on the ULSCH more accurately than conventional base stations.
• FIG. 2 is a block diagram of a preamble detector 200 of various embodiments for use in a base station of the wireless network 100.
• preamble detector 200 radio frequency signal is received via antennas 202 A and 202B.
• the received signals are digitized, and cyclic prefix (CP) removers 204a and 204b remove the cyclic prefixes from the received signals.
• CP cyclic prefix
• the signals are converted to frequency domain by frequency domain transformers 206a and 206b.
• a discrete Fourier transform (whose size is either the entire preamble length or its constituent sequence length) may be performed, depending on whether coherent or non-coherent accumulation is used.
• Subcarrier demappers 208a and 208b extract the subcarriers used by preambles in the frequency domain.
• one preamble detector can be used for detecting all signatures based on one root preamble sequence.
• the received signal is correlated with all available root preamble sequences to detect UE preamble transmissions.
• Each available root preamble sequence includes a corresponding root preamble frequency response 210A-210N and 220A-220N.
• Complex conjugators 212A-212N and 222A-222N compute complex conjugates of the root preamble frequency responses 210A-210N and 220A-220N.
• Multipliers 214A-214N and 224A-224N multiply subcarrier by subcarrier the demapped subcarriers with the complex conjugates of the root preamble sequences to perform the correlation.
• PRACH preamble detection in the preamble detector 200 uses power sample based processing that compares each power sample with a preamble detection threshold.
• the base station declares corresponding detected signatures and estimates associated UE delays for any power samples exceeding the detection threshold.
• Embodiments of the preamble detector 200 generalize sample-based preamble detection using a sliding window of data of CP duration. Instead of each power sample, the received preamble energy within the sliding window is compared with a preamble detection threshold defined as:
• T Ael is the absolute preamble de is the predetermined relative
• preamble detection threshold based on a predefined false alarm probability when no preamble is transmitted
• N n is the number of receive antennas
• R seq is the number of sequence repetitions
• ⁇ ⁇ is the noise floor estimate.
• the window can be the result of a windowing filter, such as a unit impulse window filter, a rectangular window filter, a triangular window filter, a Hamming window filter, a Hann window filter, a cosine window filter, a Lanczos window filter, a Bartlett window filter, a Gauss window filter, a Bartlett-Hann window filter, a Blackman window filter, or a Kaiser window filter. Filter taps of the window filter may be computed adaptively.
• a windowing filter such as a unit impulse window filter, a rectangular window filter, a triangular window filter, a Hamming window filter, a Hann window filter, a cosine window filter, a Lanczos window filter, a Bartlett window filter, a Gauss window filter, a Bartlett-Hann window filter, a Blackman window filter, or a Kaiser window filter. Filter taps of the window filter may be computed adaptively.
• the preamble detector 200 up-samples the preamble by zero padding the correlations at zero padders 216A-216N and 226A-226N in the frequency domain, such that signal length is a power of 2.
• the inverse frequency transformers 218 and 228 convert the frequency domain signals to time domain signals.
• Signal power converters 219 and 229 compute the square of the absolute value of the time-domain signal.
• Summer 230 sums the resultant power signals.
• the noise floor estimator 232, peak searcher 234, and SINR estimator 338 operate on time domain signals.
• the preamble detection threshold T det is derived assuming a predefined false alarm probability when no preamble is transmitted. With sliding window based preamble detection, the preamble detection threshold is a straightforward extension of the single sample case with a sliding window length W cp of W cp > L samples, where L is the preamble upsampling ratio.
• the noise floor estimator 232 may generate two different noise floor estimates based on the time domain power samples provided by the summer 230.
• a first noise floor estimate y n is generated for use in preamble detection, and a second noise floor estimate Y n (which is different from ⁇ ⁇ ) is generated for use in SINR computation after preamble detection.
• the noise floor estimator computes a noise floor threshold as:
• N R N -f P fa is a predefined PRACH false alarm rate
• N rx R seq predetermined normalized relative noise floor threshold based on a predefined false alarm rate.
• N s is the number of samples z(z ' ) summed.
• the preamble detector 200 may include a combination of dedicated circuitry and a processor executing instructions to provide the functionality disclosed herein.
• CP removers 204a and 204b, frequency domain transformers 206a and 206b, and subcarrier demappers 208a and 208b may be implemented by dedicated hardware circuitry.
• Functionality downstream of the subcarrier demappers 208a and 208b may be implemented via a processor (e.g., a digital signal processor) executing instructions, retrieved from a storage device by the processor, so that such execution causes the processor to perform the operations disclosed herein.
• the noise floor estimator 232 and SINR estimator 238 may implemented by the processor executing instructions stored in a computer-readable medium, such as a memory.
• the noise floor estimate ⁇ ⁇ for a root sequence can include interference from the preambles received at a different root sequence.
• the noise floor estimate at the given root sequence also increases due to the increase in total received power of the multiple preambles. The increased noise floor detrimentally impacts SINR.
• the noise floor estimator 232 computes the second noise floor estimate ⁇ ⁇ after preamble detection.
• Noise floor estimate f n excludes preamble signal energy from the noise floor computation, which provides a more accurate noise floor value and ultimately a more accurate SINR value.
• FIG. 3 is a diagram of signal power samples generated for a root sequence by the summer 230 of various embodiments.
• two preamble search windows corresponding to two preambles using two cyclic shifts of one ZC root sequence are shown as a matter of convenience.
• the preamble detector 200 may apply any number of preamble search windows contingent on specific cell configuration.
• a preamble detection threshold computed as described herein is shown, and example noise floor threshold values applied to compute ⁇ ⁇ and f n are shown.
• Window 302 is a sliding preamble detection window of length W cp (i.e., cyclic prefix length).
• the noise floor estimator 232 For each preamble identified by the preamble detector 200, the noise floor estimator 232 computes the total sample power E cp within the window W CP containing the detected preamble.
• the window may start at a position at which maximum total power is contained within the window, or the window may start at the maximum detected sample position, depending on the employed preamble detection method.
• Sample power E cp for each identified preamble is excluded from the sample power of a root sequence applied to compute the noise floor ⁇ ⁇ .
• the noise floor estimator 232 excludes the total preamble power E cp for preambles detected for the given root sequence, and excludes cross-correlation interference power derived from E cp for preambles detected for other root sequences.
• FIG. 4 is a flow diagram of a method 400 of determining noise floor and SINR in the preamble detector 200 of various embodiments. Although depicted sequentially as a matter of convenience, at least some of the actions shown can be performed in a different order and/or performed in parallel. Additionally, some embodiments may perform only some of the actions shown. At least some of the operations of the method 400 may be performed by a processor executing instructions retrieved from a non-transitory computer readable storage medium.
• the preamble detector 200 is operating as a component of a base station (such as base station 101 in the network 100).
• the preamble detector 200 is receiving wireless signals transmitted by user equipment, and detecting preambles transmitted by the user equipment at each of multiple root sequences.
• the noise floor estimator 232 computes the power E cp for each preamble detected (i.e., sum of sample powers within window W cp ), and computes the average received sample power for each root sequence excluding E cp for each preamble detected for the root sequence. Thus, the noise floor estimator 232 computes the power for each root sequence excluding preamble samples from the power computation.
• the noise floor estimator 232 computes a second noise floor threshold as a product of: (a) a predetermined normalized relative noise floor threshold that is based on a target false preamble detection rate, and (b) the average received sample power excluding E cp values computed for preambles detected at the root sequence.
• the noise floor estimator 232 computes, for each root sequence, noise floor estimate f n as mean power of received samples, excluding E cp values computed for preambles detected at the root sequence, below the second noise floor threshold.
• the noise floor estimator 232 for each root sequence, computes the total interference energy of the preambles detected at each other root sequence.
• the noise floor estimator 232 computes the interference energy, for each root sequence, as a sum of energy of all preambles detected for the root sequence (E CP ) less the noise energy within the window W CP corresponding to each preamble detected for the root sequence.
• the noise floor estimator 232 for each root sequence, computes cross-correlation interference power for each other root sequence.
• the noise floor estimator 232 computes the cross correlation interference power for a root sequence by dividing the total interference energy for the root sequence by the number of power samples for the root sequence.
• the noise floor estimator 232 adjusts the noise floor estimate n for each root sequence by subtracting (from the noise floor estimate f n ) the cross-correlation interference power calculated for each other root sequence.
• the cross-correlation interference power may be normalized by dividing the cross-correlation interference power by the number of receive antennas ⁇ ⁇ and the number of sequence repetitions R seq .
• the SINR estimator 238 generates an SINR estimate based on the noise floor estimate Y n provided by the noise floor estimator 232 in block 412.
• the base station may apply the SINR estimate to generate, and transmit to the user equipment, a power control value for use by the user equipment in ULSCH transmissions.

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• 2014
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