Position tracking, using the Global Navigation Satellite System (GNSS), including Global Positioning System (GPS) and/or Galileo, is driving many consumer electronics applications. GNSS is no longer limited to automotive applications, surveying equipment, marine guidance, or expensive handheld tracking systems, but is now finding its way into many new cost-sensitive applications, including cellular handsets and Personal Navigation Devices (PNDs). Driving down cost is still a key for widespread GNSS acceptance in consumer electronics, however,

For high-end devices with a more flexible price point, GNSS is usually implemented using a stand-alone, hardware- based module. While simplifying GNSS design-in, hardware-based modules provide fully evaluated positionfix data to the host processor; however, these modules introduce a relatively high cost item into the bill of materials (BOM). Since GNSS is intended as a value-added feature rather than the primary purpose in these types of consumer devices, it has not always been feasible to implement GNSS in a consumer electronics product without significantly impacting product cost, with the attendant risk that the product must be sold at a price that doesn’t attract sufficient market interest.

The availability of software-based GNSS has dramatically dropped the cost of adding GNSS to a system. Effectively, the investment of the integrated circuits (ICs) traditionally used for a GNSS baseband microcontroller and memory is not needed in software-based GNSS, thereby providing savings as much as 80 percent compared to the cost of a stand-alone GNSS receiver. Consequently, it has become possible to bring GNSS functionality cost-effectively to a wide range of applications, including portable media players and handsets. Notably, these devices already have a color liquid-crystal display (LCD) available that can be leveraged to display position information, as well as sufficient processing resources for baseband processing without requiring the addition of any new processing resources or capabilities.

Developing a GNSS subsystem for consumer electronic devices can, however, appear daunting to developers with little or no expertise in Radio Frequency (RF) design. The difficulty is not so much in optimizing the RF performance of the receiver, since many available GNSS receivers feature a high level of integration, low BOM, and comprehensive support collateral with good results obtained by following the recommendations for the reference design. Rather, when implementing the GNSS baseband processing in pure software there are numerous architectural and detail decisions that have a huge impact (positive or negative) on sensitivity, performance, accuracy, and power consumption.

If software engineers understand certain key RF principles and how these can be optimized in a system, they become much better able to maximize signal integrity and positioning accuracy to build successful GNSS systems for the highly competitive consumer electronics market. It is possible to take advantage of the inherent flexibility of software architectures to achieve a higher level of system capability (e.g., improved positioning accuracy with fewer satellites) at a lower cost than hardware-based modules.

Baseband GNSS processing is far from trivial. For performance and cost reasons, the GNSS baseband has traditionally implemented a GNSS Correlator function in hardware, either using real correlator fingers or employing a digital-signal-processing (DSP) core to emulate the function of a massively parallel correlator [i.e., for enhanced time-to-first-fix (TTFF) performance]. The drive to bring GNSS to consumer electronics devices such as handsets has changed the returnon- investment (ROI) equation for determining the most efficient method for implementing GNSS. Specifically, what matters is the incremental cost to introduce GNSS to an already existing architecture. For example, if GNSS is implemented using a hardware-based module costing $6, this adds $6 to the system BOM.

Figure 1 shows a traditional standalone GPS module architecture, with RF radio and hardware-based baseband. Figure 2 shows how the same stand-alone GPS module is connected to an applications processor in a product such as a PND. In a softwarebased architecture, baseband processing is implemented on a host processor (Figure 3) in a way that resembles the software modems ubiquitous in modern personal computers (PCs).

Baseband processing of GNSS signals has not traditionally been implemented on a host processor in GNSSonly applications because the cost of processor cycles has been significantly more than the cost of the equivalent number of gates using an applicationspecific integrated circuit (ASIC) for the GNSS processing. In a handset, however, a powerful applications host processor is already a necessary part of the overall architecture since, in order to meet the recent increase in demand for multimedia services, this processor must have enough capacity to decode streaming music and video files. Furthermore, when these services are not in use, the application processor may be underutilized and sitting idle, making it available to perform other tasks.

Until recently, the processing capability of this applications host processor could not deliver the processing power to implement software-based GNSS. However, it is now possible to have this processor perform GNSS baseband processing, substantially reducing the incremental expense and barriers to entry of introducing GNSS into a wide range of consumer electronics devices. From a price perspective, software-based GNSS will add approximately $3 (or about one-half that of a hardware-based module) to the system BOM while extending full GNSS capabilities.

It is important to note that this is only the starting cost for a softwarebased GNSS subsystem and therefore its peak price. Software has a very different pricing model than hardware based on the widespread perception that there is no manufacturing cost to software once it has been developed. The market traditionally has viewed software as a means for selling hardware and, as a consequence, software is often bundled with hardware. As market pressures drive down GNSS radio cost and adoption into higher volume applications takes off, this price is anticipated to quickly reach $1. At this cost, GNSS becomes a function that can be implemented in almost any consumer electronics application. In time, it will also facilitate the convergence of diverse wireless technologies, including GNSS, Bluetooth, and wireless local area networks (WLANs), onto a single, software-defined radio (SDR) platform.

Since the cost savings behind software-based GNSS come from making use of otherwise unutilized processor cycles on an applications host processor that is already part of the architecture, this transfers some of the responsibility of optimizing RF processing to software developers, whereas this used to be the domain of RF designers. Note that optimization by software developers does not involve development and refinement of RF baseband processing algorithms; there are already several RF market leaders developing off-the-shelf GNSS baseband processing software. Rather, optimization is achieved by how well developers integrate software-based GNSS technology into existing designs. Primarily, optimization is focused on maintaining performance and accuracy under worst-case operating conditions, minimizing power consumption, and preserving architectural flexibility.

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