The rich availability of Wi-Fi connectivity and the universal demand for constant access to voice and data communications are driving consumer and enterprise demand for converged Wi-Fi/cellular applications and services. Under the banner of fixed-mobile convergence (FMC), these applications promise better access to voice and data services as well as lower communications costs.
Successful delivery of converged services is based on the assumption that wireless IP networks and 802.11a/b/g/n devices can deliver the underlying quality of service necessary to guarantee a satisfying end-user experience. Critical FMC performance metrics that directly affect user experience are measured by voice quality, dropped calls, and battery life.
These user-experience metrics are directly influenced by Wi-Fi metrics such as data rate, error rate, packet loss, and roam time, which define mobility performances like range, roaming, and hand-in/hand-out. The increasing adoption and deployment of this technology have created the need for a reliable means to ensure the delivery of carrier-grade voice over Wi-Fi to end users.
As a result, extensive testing is required to guarantee that FMC devices and the networks on which they operate can deliver the necessary performance. For mobility performance testing to be effective from quality, coverage, and cost perspectives, test methodologies must accurately recreate the real world in an efficient, repeatable, cost-effective, and scalable manner.
What Is Fixed-Mobile Convergence?
FMC means different things to different groups. For end users, it is the promise of quality fixed services and applications of voice, video, and data being delivered seamlessly over mobile wireless networks to handsets or endpoint devices. For infrastructure vendors, FMC represents a large commercial opportunity to deliver back-end integration products and services, and for service providers, it is an opportunity to develop additional revenue from existing cellular and Wi-Fi network infrastructure investments. To drive increased adoption by end users, the industry must deliver compelling FMC applications and services beyond what are currently available.
One major benefit that FMC provides is the convenience of having one device and phone number for both the mobile network and the home network. With the voice call seamlessly transferred from the cellular network to the home or corporate network, users enjoy continuous communications and benefits from improved coverage of the Wi-Fi network while reducing cellular minute usage.
Location-independent access to data applications also represents a huge draw for potential users. Whether stationary or mobile in any location covered by a cellular or Wi-Fi network, users will have access to Internet-based applications such as e-mail, Web browsing, and online services like banking, news, and entertainment. This ability to use data applications where and when they want will enable significant improvements in personal and professional productivity.
In addition to seamless voice and data communications, sustainable consumer demand for FMC services also will be driven by the capability to provide cost savings not available from alternative Wi-Fi and cellular-only services. Existing cellular services have established user experience expectations that new converged services must meet or exceed. For service providers, this means FMC must deliver carrier-grade voice and data services characterized by:
• Optimal voice quality.
• Few or no dropped calls.
• Reliable and high throughput data connectivity.
• Long handset battery life in the standby and active states.
• Seamless voice and data roaming/handoff.
Wi-Fi Mobility Usage Scenarios
The growth in consumer demand for long-range cellular network services has been primarily driven by improvements in mobile voice services and value-added data services like text messaging and Web access. FMC broadens the range of these services indoors where cellular coverage may be less reliable. By moving coverage onto the Wi-Fi network, users have access to potentially much higher-speed services.
However, this Wi-Fi connectivity must at least sustain the mobility and quality of service that cellular users have come to expect. Additionally, converged Wi-Fi/cellular services must support the same or better quality voice and data services while the user is in motion and transferring among the networks. This mobility service requires adequate performance in three key usage scenarios: Wi-Fi range, Wi-Fi roaming, and hand-in/hand-out network handover.
Wi-Fi range, or coverage, is defined as quality voice and data services while the user moves closer to and away from a Wi-Fi Access Point (AP) and is a significant measure of Wi-Fi performance. In contrast to cellular technology, Wi-Fi technology varies the transmission data rate to minimize packet errors.
A Wi-Fi transmitter on the AP or client uses dynamic rate adaptation algorithms to control the transmission data rate on a packet-by-packet basis. These algorithms consider many different network and environmental variables including receive signal strength and packet error rate in deciding to increase or decrease the transmission rate.
If these algorithms are poorly implemented, movement within a Wi-Fi AP will significantly impact data throughput and voice quality. Proving that the rate adaptation algorithms have been implemented properly requires extensive range testing of the client and AP devices.
Wi-Fi roaming, the capability to provide quality voice and data services while moving between APs, is another critical measure of Wi-Fi device performance. Both cellular and Wi-Fi networks use algorithms to transfer connectivity from one infrastructure device, such as cellular base station or Wi-Fi AP, to another as connection conditions require.
Cellular networks utilize roaming algorithms that are implemented on the base station and managed by the network, which make roaming decisions dependent on real-time network conditions like base-station loading or base-station service outage. Wi-Fi networks, in contrast, use roaming algorithms implemented on the client, which make roam decisions without consideration of real-time network conditions.
This means that Wi-Fi clients could make decisions to roam to an AP that is overloaded or not functioning properly. This would result in significantly reduced data throughput and voice quality or the session being terminated completely.
In addition to the differences in the implementation of the roaming algorithm, cellular and Wi-Fi networks execute the roam differently. Cellular networks roam using a make-before-break approach. This establishes the connection between the handset and the base station being given control of the session prior to terminating the connection between the handset and the base station that is giving up control of the session.
In contrast, Wi-Fi clients use a break-before-make approach to roaming, in which the client terminates connectivity with one AP prior to establishing connectivity with a new AP. A poorly implemented roaming algorithm on the client can result in a significant amount of time to establish the connection with the new AP or even failure to make the connection entirely, which can severely impact data throughput, voice quality, and call continuity. Given the differences in the roaming algorithm implementation and execution, maintaining data throughput, voice quality, and satisfactory call continuity requires extensive testing.
Transferring session connectivity between Wi-Fi and cellular networks also is much more complex than a Wi-Fi-to-Wi-Fi roam or a cellular-to-cellular handover. With the differences between cellular and Wi-Fi handover algorithm implementations, engineering efficient Wi-Fi-to-cellular handovers requires complex changes to the back-end cellular network as well as significant changes to decision-making algorithms. With this increased complexity, extensive testing must be done to validate the impact of handover on throughput, voice quality, and call continuity.
Real-World Wi-Fi Mobility
When discussing the performance of Wi-Fi devices, the impact of the real-world environment in which the devices operate must be recognized. Unlike a cellular network, which is the sole occupier of the licensed RF spectrum in which it operates, a Wi-Fi network runs in an unlicensed spectrum that it shares not only with other Wi-Fi networks but also potentially with other RF networks like Bluetooth or even other RF devices such as cordless phones and microwave ovens.
The presence of RF devices and Wi-Fi networks competing for spectrum causes RF interference that can significantly impact the performance of a Wi-Fi network. In addition, solid obstacles such as walls and furniture as well as the movement of objects like vehicles can create RF signal conditions, known as multipath and fading, that impact the performance of Wi-Fi devices.
Most FMC solutions will use the Internet, a nondedicated IP network, as a primary carrier of the voice data, which can directly affect voice quality as the traffic load varies. To maintain the best possible FMC services, converged Wi-Fi/cellular handsets must deliver the best Wi-Fi mobility performance in all these different types of real-world conditions.
To determine the impact of Wi-Fi performance on user experience, it is important to first identify the critical mobile performance scenarios that directly impact the user experience. Table 1 identifies critical mobile performance scenarios.
Wi-Fi mobile scenarios establish the fundamental performance metrics including data rate, packet loss, error rate, and roam time that must be tested. A set of essential tests for the evaluation of the Wi-Fi mobility performance can be developed (Table 2).
Effective Test Methodologies
In over-the-air (OTA) testing, engineers replicate the actual conditions of the environments in which devices will operate. This is accomplished by renting or buying empty office buildings and homes or even testing on live networks. Mobility and roaming are tested by placing Wi-Fi devices on mobile carts, moving these carts to various locations in the test space, and manually configuring tests and recording test results at each location.
Due to the uncontrollable nature of OTA environmental conditions, the majority of testing is done manually. The effectiveness of Wi-Fi mobility performance testing using OTA methods also is limited by two critical factors:
• The time-consuming manual test setup and execution typical of OTA tests limit the capability of this testing method to scale.
• Consistent, repeatable test measurements are nearly impossible in open-air environments, limiting the capability to reliably repeat the tests in the future.
In addition, the RF interference may vary with each test iteration even at the same location, which could make reproducing results and issues nearly impossible.
The alternative to OTA testing is using a controlled RF environment such as a screen room that filters out external RF interference. This method is expensive because of the large installation and maintenance costs of the screen rooms. In addition, the size of the screen room severely limits the effectiveness of testing distance, roaming, and mobility.
A more advanced method of controlled RF testing involves device isolation. In device isolation, each test-bed device is placed in an individual isolated enclosure and connected via cables to programmable RF attenuators, combiners, and switches. This test methodology replicates the Wi-Fi network in a controlled, cabled environment that stabilizes the RF connection by removing the variability of open-air systems.
The device-isolation approach provides a completely controllable RF environment to conduct repeatable mobility testing. Test solutions that use a controlled, cabled RF environment eliminate the need to design, build, and maintain homegrown test beds and costly RF screen rooms.
Another benefit of this methodology comes from the programmable test bed and tools that enable automated test configuration and execution. To analyze the effect of mobility on both device and network performances, users can automatically configure any network device and dynamically position any network node. Automated test configuration also allows for repeatable test execution over time.
Using programming, scripts can be created which require little human intervention and automatically run multiple iterations of different configurations in a fraction of the time required for manual testing. This repeatability reduces the time spent on quality assurance and benchmark test processes as well as time to market and testing costs.
Test scalability is an additional important benefit of the device-isolation approach. If the controlled RF environment is properly architected, system designers can scale Wi-Fi testing from a single device to the entire network. Users can configure an entire Wi-Fi network and provide system-level testing of actual APs, clients, and other wireless devices. Networks can be tested under a variety of traffic and client load conditions. Client and traffic load emulations enable the development of test setups that recreate a busy network environment for the DUTs.
Lastly, this approach provides the capability to test Wi-Fi mobility performance. Engineers can assess the impact of one or a combination of real-world conditions, including RF multipath and fading, background Wi-Fi traffic, RF interference, and IP network delay, on the mobility performance of 802.11a/b/g/n devices.
Another critical test is conducted by systems engineering groups within service-provider organizations that will use these same test scenarios to validate interoperability of devices from different suppliers, benchmark performance of different configurations to make purchasing decisions, and certify devices for deployment. For the engineers tasked with selecting FMC handsets that will operate on service-provider networks, an effective performance benchmarking process provides a means of performing an apples-to-apples comparison of the Wi-Fi mobility performance delivered by FMC handsets from different manufacturers.
Converged Wi-Fi/cellular promises benefits ranging from continuous access to voice and data applications and services to reduced costs. Sustainable consumer demand will be dependent on carrier-grade FMC services that deliver reliable and fast data throughput, good voice quality, few dropped calls, and long handset battery life.
As cellular-only services provide voice and data services with carrier-grade quality, the capability to deliver FMC services of similar quality is expected. This will directly be impacted by the performance of Wi-Fi-enabled devices as users move within and between Wi-Fi networks as well as transfer between Wi-Fi and cellular networks.
Critical FMC performance metrics that directly affect user experience are functions of Wi-Fi data rate, error rate, packet loss, and roam time. Among the several test methodologies available today, the most effective method for testing the mobility performance of 802.11a/b/g/n devices uses a controlled, cabled RF environment. In addition to providing accurate and repeatable test results, such an approach can use programmable test tools and external test components to analyze mobility performance in controlled, real-world network conditions and leverage automation to reduce test time and overall costs.
About the Author
Richard Lu is the Wi-Fi product line manager at Azimuth Systems and has 10 years of experience in test and measurement for the telecommunications and networking industries. Before joining Azimuth Systems in 2003, Mr. Lu was at Coppercom, where he started the company's design verification lab, and was an applications engineer at Zarak Systems, which later was acquired by Spirent Communications. Mr. Lu graduated from the University of California with a B.S. Azimuth Systems, 31 Nagog Park, Acton, MA 01720, 978-263-6610, e-mail: [email protected]