Today there are 1.6 billion wireless subscribers in the world with the number anticipated to grow to 2.6 billion in the next 5 years. These numbers show that wireless subscriptions have already surpassed the number of internet users (expected to top 1 billion by mid-2005) and will represent a 37% penetration rate of the entire world population by 2010! To support this growth, wireless infrastructure deployments will also have to experience tremendous growth during the next few years.

Even with this growth, the wireless infrastructure industry can still be classified as entering a mature life cycle phase as we are beginning to see major industry consolidation. For example, Sprint recently bought Nextel to form a combined entity with revenues exceeding $40 billion and Cingular acquired AT&T wireless forming a combined entity with revenues of over $30 billion. These consolidations have positioned the cellular service providers to exercise a greater amount of purchasing power over the wireless infrastructure providers to force them to greatly decrease infrastructure equipment prices.

With this strong pressure to drive down infrastructure prices, next generation base station deployments are being designed to reduce costs, as measured by cost per channel, while still adding functionality to support new services, protocols and changing subscriber usage patterns. The cost reductions are targeting both CAPEX and OPEX, with the impact of each cost element on the wireless cost structure shown in Table 1. To begin addressing these cost challenges, the wireless base station designs are shifting away from using ASIC technology to a reliance on more readily available off-the-shelf programmable components such as FPGAs. This shift is driven both by FPGA technology improvements over previous generations of FPGAs that increase their processing power and enable a much lower cost per channel as well as the integrated building blocks such high-performance digital signal processing to implement specific baseband and radio algorithmic functionality. This migration to FPGAs is not just an attempt to reduce costs in pursuit of creating a common platform to achieve commoditization – this is also being driven by time-to-market pressures along with the need to make in-field upgrades of base station deployments.

Table 1: Cost Structure for US Mobile Operators (FCC)

The ability of programmable logic devices to perform remote programmable optimization can help improve wireless antenna efficiency by enabling remote radio tuning to compensate for local environmental changes or usage patterns. This ability allows infrastructure providers to take a huge step forward towards providing the “anytime, anywhere” nirvana service for the cellular subscribers. Nearly half of wireless subscribers rank clear and reliable communications as the most important evaluation criteria for wireless service while over one-third indicate that continuous extended area coverage is most important. Also worthy of note is that one prominent US-based cellular company has created a multi-million dollar advertising campaign around these issues with their ubiquitous “Can you hear me now?” catch phrase. In addition to antenna tuning, the ability of FPGA devices to be programmed in the field enables central site operators to perform remote servicing, which may eliminate the need for a technician to visit a site (cost of about $150 per visit) and help to reduce site down time. Solving these issues helps wireless service providers lower their customer churn and enables marketing expenditures to be focused on other aspects of customer acquisition and retention.

These in-field upgrades are also very important for wireless infrastructure providers to future-proof their systems being deployed in the field. New wireless technologies such as W-CDMA, TD-SCDMA, EDGE, 1xEV-DO and WiMAX are being introduced to support new services. These services, such as picture exchanges, internet searches, music downloads and streaming video, will greatly increase the bandwidth requirements per user over what is currently experienced today. In addition, to combat the cost-efficient and rapidly growing “Hot Spots” that are currently stealing premium data centric customers from the cellular operators, infrastructure providers are seeking ways to provide smaller, more cost-effective solutions such as Remote Radio Heads. These units are used to supplement base station macrocells with microcells and picocells which are much smaller in physical size and can be deployed faster and in more places to fill coverage gaps or quickly add additional capacity to meet requirements in high traffic areas. These units work in conjunction with the more costly base station towers to provide inexpensive voice, data and video services to the end users. These units should be built with programmable devices such as FPGAs due to the need to configure a remote unit to handle localized usage patterns in different geographies while overcoming obstructions in the cellular footprint.

As the wireless industry enters its maturation phase, infrastructure providers will have to rely more heavily on devices such as FPGAs to balance current requirements of providing cost-effective solutions with allowing for future in-field upgrades. Fortunately for the infrastructure provides, the types of FPGA devices are shipping now and can effectively be used to meet the design requirements for cost-effective flexibility.

About the Author David Gamba is Senior Marketing Manager for the Strategic Solutions Marketing Group at Xilinx. In this role, Gamba is responsible for outbound marketing for all vertical markets supported by Xilinx solutions. Gamba joined Xilinx in 2004 and brings over eight years of experience in the semiconductor industry where he served in a variety of marketing and sales roles including technical sales, product definition and technical marketing. Prior to Xilinx, Gamba held various positions at Aeluros, Conexant and Altera. Gamba holds a bachelor’s degree in electrical engineering from UCLA, a master’s degree in electrical engineering and computer science from UC Berkeley, and an MBA degree from Stanford University.