<1 second GPS hot-start TTF below -150dBm without A-GPS

David Tester, Senior Member IEEE Air Semiconductor

Cherry Orchard North, Kembrey Park Swindon, Wiltshire, SN2 8UH, UK

david.tester@air-semi.com

Abstract—Minimization of TTFF has driven the architecture for GPS receivers, being motivated by the historical navigation paradigm with more recent cellphone activity and applications. Existing solutions minimize TTFF through use of assist information, eliminating any requirement to collect the live satellite ephemeris and minimize acquisition time using maximum effective correlators. Cellular solutions obtain information through A-GPS assistance. In-car solutions use local or remote calculated extended ephemeris. Recent receiver solutions deliver ‘continuous location awareness’ [1] [2]. The emergence of this new category of GPS receivers supporting proactive rather than reactive operation of LBS services raises additional system level trade-offs, some conflicting with TTFF. Receivers optimized for TTFF can be adapted for pseudo-proactive GPS functionality. However improved performance can be delivered through use of an architecture not explicitly optimized for TTFF. The impact of local reference frequency error for these ‘dual mode’ GNSS receivers is examined. The different receiver architectures capable of delivering continuous location awareness are compared.

I. INTRODUCTION Location has emerged as core functionality for consumer

devices such as mobile phones and digital cameras. GPS enabled mobile phones offer navigation capabilities and other location based services. GPS enabled digital cameras can location-stamp photographs (often called “geotagging”). This paper outlines the performance required by the emerging generation of proactive location-aware end-user applications. Alternative architecture options to deliver proactive GPS are considered and the relative strengths of each are compared. The paper concludes with details of the architecture capable of providing continuous GPS operation in this new paradigm.

II. SUMMARY OF THE PAPER Sections III and IV outline details of the GPS and A-GPS

systems. Section V describes the performance needed for various location based service (LBS) applications. Section VII details the constraints for minimization of time-to-first-fix (TTFF) and time-to-fix (TTF). Section VIII investigates architecture options for TTF rather than TTFF optimization. Finally, section IX compares the performance of the proposed approach with alternative architectures based around A-GPS.

III. SUMMARY OF GPS SYSTEM PERFORMANCE The GPS air interface is defined in [3]. Additional details

on system design and operation can be found in [4] and [5]. Each satellite transmits a CDMA signal at 154x the system frequency of 10.23MHz at 1.58GHz. The C/A signal at L1 is spread using Gold codes [6]. Worst case cross-correlation between the 1023 chip codes used for L1 GPS is 21.6dB. Unobstructed receive power is no less than -130dBm over the satellite lifetime with a spread of 6dB due to satellite age. Observed power in a typical environment can be 30dB less! Each satellite transmits a 37,500 bit navigation message through a 25 frame TDMA protocol. Each frame contains 1,500 bits of data and is comprised of 5 sub-frames each lasting 6 seconds containing ten 30 bit words. The entire message provides both satellite (ephemeris) and constellation (almanac) information. Ephemeris transmission requires 30s.

IV. SUMMARY OF A-GPS NETWORK ASSISTANCE A-GPS is an enhancement to GPS. Aiding information is

provided to the receiver by a cellular network. Satellite data relating to orbits (ephemeris), coarse receiver location and system time are provided. Minimum performance requirements for assisted GPS are defined for both 2G and 3G cellphone networks by various standardization bodies such as 3GPP, TIA and OMA [7], [8], [9], [10] and [11].

Various assistance scenarios are defined [7] and minimum receiver time-to-fix (TTF) and location accuracy performance is specified. Scenarios correspond to coarse-time assistance, fine-time assistance, dynamic, open-sky and urban operation.

The open-sky coarse-time sensitivity scenario operates with eight satellites, HDOP range 1.1 to 1.6 and time assistance of ±2s. Receive power for all satellites is -130dBm and the minimum requirement for CEP95 position error is 30m (2D position error to 95% probability) within a TTF of 20 seconds. The urban coarse-time sensitivity scenario operates with eight satellites, HDOP range 1.1 to 1.6 and time assistance of ±2s. Receive power for one satellite is -142dBm with the other seven satellites receive power of -147dBm. The minimum requirement for CEP95 error is 100m within a TTF of 20s. The fine-time sensitivity scenario operates with eight satellites, HDOP range 1.1 to 1.6 and time assistance of ±10µs with receive power for all satellites at -147dBm. Minimum

requirement for CEP95 error is 100m with TTF of 20 seconds. The second coarse-time dynamic scenario operates with six satellites, HDOP range 1.4 to 2.1 and time assistance of ±2s. Receive power for one satellites is -129dBm, one satellite at -135dBm, one satellite at -141dBm and three satellites at -147dBm. Maximum CEP95 error is 100m with 20s TTF. Coarse-time multipath performance scenario operates with five satellites, HDOP range 1.8 to 2.5 and time assistance of ±2µs. Receive power for two satellites is -130dBm with the remaining three satellites direct receiver power of -130dBm with each of these three satellites also providing a multipath signal at -136dBm. CEP95 error is 100m with a TTF of 20s. The final dynamic scenario operates with five satellites, HDOP range 1.8 to 2.5, time assistance of ±2s with all satellites at -130dBm. Requirement for CEP95 position error is 100m with an position update rate of 2s.

TTF in all cases is 20s. Required position accuracy is 30m in open-sky static conditions and 100m in all other scenarios.

V. DISCUSSION OF LBS APPLICATION REQUIREMENTS The killer application for GPS today is point-to-point

navigation. Initially used only for in-car navigation this has become widely used with many cellphones [12]. As location becomes available for mobile devices, further services become available [13] along with additional privacy concerns [14]. Navigation demands a positioning solution capable of providing maximum accuracy with the maximum practical update rate and minimum time-to-first-fix (TTFF). Target performance is 1Hz update rate with <1m position error. Early cellphone applications for GPS assumed location would be required infrequently and that power consumption of the GPS solution would, as a result, not impact the power budget for the cellphone. Weak signal GPS operation and TTFF was a major concern. Target performance is weak signal TTFF not exceeding 20s with position accuracy better than 100m [7]. Emerging LBS applications require a positioning sub-system which is capable of continuous background operation. When the receiver moves into or close to a geographic area of significance the GPS sub-system triggers the LBS application. Continuous background operation of the GPS receiver enables proactive operation of the LBS application. The user is automatically alerted rather than enabling the GPS to determine if desired services are available in that area. Proactive LBS requires continuous operation of the GPS sub-system which in turn requires a GPS engine with a power footprint compatible with the average power consumption of the host device. For cellphone use 5mW operation is required. When user location is continuously available, geographic triggers can be defined to automatically launch LBS services. If location is not continuously available these services can only be triggered in response to the user enabling the GPS sub-system. Examples of proactive triggers are listed in [15]. Proactive LBS applications enable the immediate delivery of services. An example is location-aware push advertising. Provision of continuous positioning requires a continuous stream of location information from the GPS sub-system to the LBS application(s). Different LBS services will require differing levels of position quality from the GPS sub-system. Providing a continuous stream of location updates is not the same as delivering updates as frequently as possible. If the

LBS application only requires course location then low update rates are appropriate. However if the application requires accurate location continuously then conventional 1Hz rates are suitable. Understanding that future LBS applications can operate with varying update rate GPS sub-systems is critical to the delivery of proactive LBS applications [16] [17] [18].

VI. ARCHITECTURE FOR PROACTIVE LBS APPLICATIONS Releasing the GPS receiver from the constraints of

traditional continuous-mode tracking with fixed frequency update rate provides a new degree of freedom in architecture definition and enables the development of GNSS receivers capable of operating at very low power levels of around 5mW. With total receiver power in the region of 5mW the GPS receiver can continuously operate in the background without impacting power budget and significantly affecting the time between battery recharge cycles for mobile devices.

Critically, background operation of the GPS receiver delivers three major advantages: predictable (and minimal) TTF for immediate position update in push-to-fix operation, guaranteed availability of recent location with zero second TTF and pseudo-operation indoors since indoor operation of GPS is difficult and low-power indoor GPS is an oxymoron.

The receiver architecture described in this paper is capable of providing push-to-fix operation with TTF effectively independent of GPS signal conditions. LBS operation in indoor conditions is maintained as a side-effect of continuous background operation. Alternative approaches would fail to detect satellite signals indoors, not deliver service quality and eventually report “location unavailable” to LBS applications.

Traditional GPS receivers operate in either search mode or navigation tracking mode. Minimization of TTFF has lead to ever increasing numbers of effective correlators for the search engine, resulting in solutions offering efficient performance when searching huge numbers of candidate bins. A-GPS receivers maximize the number of effective correlators. Conventional tracking operation operates the GPS radio and tracking subsystems continuously. Power consumption for radio operation approaches practical limit of 10mW [19] [20]. Reduction of GPS sub-system power consumption below this level demands the receiver is operated in discontinuous mode rather than traditional continuous mode triggering a decision on receiver architecture. The receiver must be periodically activated to “duty-cycle” the operation and minimize power. Should the receiver activate only when location is requested or would a more effective solution automatically activate itself to maintain more detailed knowledge for visible GPS signals?

VII. FREQUENCY - CODE PHASE - SV PRN SEARCH SPACE As received GPS signal strength decreases from -130dBm

to -160dBm the resulting coherent integration time required to maintain target SNR increases with corresponding decrease in bandwidth of each search bin from 500Hz to below 10Hz [20]. Stability of the local reference frequency translates to error in conversion of the RF signal to IF due to difference between the locally generated LO and the target mixing frequency. Mixing from RF to IF results in additional pre-correlation frequency error, which will depend on reference conditions. 0.5ppm reference stability leads to frequency error of 788Hz.

Figure 1. Effect of Local Reference Frequency Error

Cold start TTFF is defined by number of code phase and frequency search bins, number of satellites, elapsed time to collect ephemeris and solve position. Minimum time is 30s. In contrast, the aided hot start TTFF is defined by the time to only search frequency and code-phase and solve for position. A-GPS hot start TTFF can be 1s in suitable signal conditions. Reduction in GPS signal strength from -130dBm to -160dBm increases the number of search bins as shown in Figure 2.

Provision of coarse receiver location and ephemeris allows the receiver to determine which satellites are known to be not visible and reduces TTFF by 30s. The resulting aided hot start time is defined by the frequency-code phase search space, number of effective correlators and time to solve for position. Lack of accurate time aiding and knowledge of variation in reference frequency limits the aided hot-start TTFF and as the GPS signal strength decreases the increased number of search bins coupled with increased dwell time per bin impacts TTFF.

Provision of accurate time aiding allows the code-phase search space to be minimized. A-GPS offers two levels of time aiding: ±10µs fine-time aiding and 2s coarse-time aiding. With no external time aiding an autonomous GPS receiver drifts from GPS time at a rate of around 0.06ms/min corresponding to loss of the 1ms epoch within 15 minutes.

The exponential increase in frequency-code phase search space results from the loss of accurate time and the uncertainty around local receiver reference frequency. Controlling impact of these two factors enables the hot-start search space to be minimized and delivers TTF that is (almost) independent of the receiver GPS signal power. The architecture presented in the next section delivers push-to-fix TTF that is effectively independent of GPS signal conditions, exceeding A-GPS performance, delivering TTF of 2.5s even with received signal levels of -150dBm but requiring only 200 local correlators. Alternative approaches require 200,000+ correlators and network aiding information to deliver comparable TTF. VIII. SELF-ASSIST GPS ARCHITECTURE AND PERFORMANCE

When tracking the GPS transmission the receiver is locked directly to GPS time and whilst not tracking, the receiver local time will drift compared to satellite time. The rate of drift depends on the relative performance of the receivers ability to either predict reference variations or maintain the frequency reference with known performance. Maintaining an accurate local estimate of system GPS time enables self-assistance.

Figure 2. Increase in correlation bins with GPS signal strength

The receiver has no absolute time or frequency reference and must make time hypothesis which are validated against the GPS signal itself to ensure local receiver time predictions remain within suitable tolerances. This requires the receiver to periodically activate and re-lock to the GPS transmission. Existence of accurate local time enables use of minimum size search windows for re-detection of the GPS satellite signals. The virtuous circle that results is the critical factor enabling self-assistance of the GPS receiver [22], [23] and [24]. The resulting architecture needs a micro-searcher for re-detection of GPS time. Since the receiver operates by maintaining GPS time rather than accurate receiver location, only one satellite needs to be detected (in stationary conditions) for operation. Location is a side-effect of fine-time receiver self-assistance.

The fine-time self-assistance approach forms the basis of a recent GPS receiver development. Tracking sensitivity of the solution in self-assist mode has been measured to -150dBm and is expected to operate to at least -154dBm. Unfiltered CEP50 position accuracy (over 12 hours) for the receiver operating without a Kalman filter is 2.8m and the self-assisted hot-start TTF is 2.5s over signal power -130dBm to -150dBm.

Performance of the resulting self-assisting GPS receiver exceeds all sensitivity, TTF and accuracy requirements for the 3GPP standard yet needs 200 rather than 200,000+ correlators.

IX. CONCLUSIONS Traditional GPS receivers deliver time from tracking

location, alternative architectures can deliver location through tracking time. Despite additional complexity tracking time provides the ability for a GPS receiver to provide self-assist information, enabling enhanced push-to-fix TTF compared to alternative traditional approaches.

Earlier approaches have adapted GPS receivers originally intended for navigation to deliver LBS functionality [20] [25].

The approach described in this paper forms the basis for a GPS receiver optimized for use with LBS applications [22]. The receiver has been successfully used to enable the emerging “geotagging” application for use in digital cameras.

Resulting performance for the self-assist GPS receiver exceeds the 3GPP sensitivity, TTF and accuracy requirements for A-GPS operation without any network aiding requirement!

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Figure 3. Performance of Self-Assist GPS receiver (over receiver signal power -130dBm to -150dBm)

ACKNOWLEDGMENT Development of any complex system-level semiconductor

product is a group activity involving (and often demanding) system, silicon and software optimizations and tradeoffs. The approach described in this paper forms part of a system-level GPS semiconductor product developed by the team at Air. The product detailed in this paper results from the combined contributions of all team members.

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