Archive for May, 2015

Understanding Wi-Fi Signal Strength vs. Wi-Fi Speed

Wednesday, May 20th, 2015

The relationship between Wi-Fi signal strength and the speed at which data can be transferred over that signal is something that is essential to understand when it comes to Wi-Fi performance.

One question we constantly get is this:

When I connect my computer to a wireless network, does a stronger signal always imply faster webpage loading, downloads, etc?

The answer, like all answers to WI-Fi questions, can be difficult to get a grip on. So here’s a good, fairly simple explanation from one of Ruckus’ rocket-scientist founders, Bill Kish, that should help clarify things.

All other factors (of which there are many) being equal, stronger signal strength is correlated with higher data transfer speeds, with a couple exceptions and assuming an optimal physical layer data rate selection algorithm. The super detailed, professional and technical diagram below shows a typical relationship for any modern wireless system with adaptive modulation:

WiFi-Performance-Signal

The data transfer speed increases up to a point as signal strength increases since higher signal strengths enable the use of higher PHY (PHYsical layer data) rates, also known as MCS (Modulation and Coding Scheme) in modern WiFi. (One gross oversimplification is to think of different MCS as being somewhat like different gears on a bike or car.)

Once there is sufficient signal strength to operate reliably in the maximum supported MCS rate, additional signal strength does not produce additional throughput gains. In fact at some point (usually a few cm away from the AP) you can eventually run into a signal strength so high that the receiver’s front-end is unable to process it, at which point throughput will drop precipitously.

All of the details (especially the scale) of this graph are highly dependent on the capabilities of the transmitting radio, the receiving radio and the environment. Variability in the environment and in the radios themselves makes real-world wireless throughput a random variable that can only be assessed accurately via statistical methods.

The physical layer data rate selection algorithm is critical to achieving the monotonically increasing relationship shown here up to saturation. There have been many examples of poor rate control algorithms loose in the wild (in both popular AP’s and common client devices) that do not actually achieve this monotonic performance, especially when subject to unexpected environmental inputs or certain radio degradations.

So What To Do? Get Smart.

Finding the right balance between optimum performance and reliability with adaptive data rate algorithms is what separates the great Wi-Fi systems from those that are good enough. This previous post from Ruckus awhile back helps explain some of the details.

Rate adaptation is the function that determines how and when to dynamically change to a new data rate. When it’s tuned properly, a good adaptation algorithm finds the right data rate that delivers peak AP output in current RF conditions –unstable as they are. Though often ignored, rate adaptation is a critical component to any high performance system.

Wi-Fi engineers have been led to believe, and—for better or worse—site survey software validates the belief, that data rates can be reliably predicted based on a metric like RSSI or SNR. And some product manufacturers use simple metrics like these to determine the right rate.

Ruckus approaches rate selection with a unique focus. Instead of using unreliable signal measurements to hope for the best data rate, we focus on the math. Our rate selection algorithms are statistically optimized, which is our engineer-chic way of saying that we pick the best data rate based on historical, statistical models of performance for each client.

Without the right algorithm, the optimal rate for any client at any given moment in time is a crapshoot. And when you’re guessing, the safest guess is to err on the side of reliability, which sacrifices throughput and capacity and causes other unwanted problems.

At Ruckus, they believe in the importance of stable client connections in an unstable RF environment. In fact, our algorithms jointly adapt both the data rate and antenna pattern together to maximize reliability and throughput.

But don’t take our word for it; test it for yourselves! You’ll definitely see a big difference and create a Ruckus (a good one) with your users.

For more information, get in touch with Net-Ctrl. You can call us on 01473 281 211. Email us at sales@net-ctrl.com or go via our contact form.

This blog post has been taken from www.ruckusroom.net.

Ruckus Takes Top Marks in Recent Wi-Fi Testing Performed by the Croatian Academic and Research Network (CARNet)

Tuesday, May 5th, 2015

Nineteen Different Wi-Fi Access Points Stressed to their Limits in a Variety of Different Scenarios, Revealing Dramatic Differences Between Competitive Suppliers.

Download the report.

Ruckus Wireless, Inc. (NYSE: RKUS) announced today that its ZoneFlex™ Smart Wi-Fi technology outperformed Aerohive, Aruba, Cisco, Cisco/Meraki, HP, Ubiquiti and Xirrus in an exhaustive head-to-head enterprise performance and capacity testing of 802.11ac and 802.11n indoor access points (APs) conducted recently by the Croatian Academic and Research Network (CARNet).

A widely respected public institution established in 1991 and based in Croatia, CARNet operates under the Ministry of Science, Education and Sport, working in the fields of information and communication technologies and their application in education, from network and Internet infrastructure and e-services, to security and user support. CARNet is chartered with facilitating the progress of individuals, as well as society as a whole, through the use of new information technologies.

Using industry standard test tools, access points in the tests were stressed in progressive testing scenarios that included 12, 23, 36 and 60 clients, using an increasing number of clients for each test that measured aggregate Transmission Control Protocol (TCP) throughput.

Nineteen different Wi-Fi access points from the world’s leading suppliers including Ruckus Wireless, Aerohive, Aruba, Cisco (including Cisco/Meraki), HP, Ubiquiti, and Xirrus were tested at the CARNet headquarters in Zagreb. To maintain testing integrity, no vendor was allowed to pay for, subsidize or influence the Wi-Fi testing by CARNet.

Suppliers were allowed to bring in their choice of APs without limitation in what model and how many as long as they could be tested in a single day. Each company was also permitted to send an engineer to the test site. Aerohive, Cisco, HP and Ruckus Wireless each sent a representative to CARNet for the tests.

The Ruckus ZoneFlex R700 dual-band 3×3:3 802.11ac and ZoneFlex R500 dual-band 2×2:2 802.11ac indoor APs with Ruckus-patented BeamFlex™ adaptive antenna technology outperformed all competitive 11ac APs in the tests. CARNet also accepted and included 802.11n access points from all invited vendors, including Ruckus, Ubiquiti, Xirrus and others. Test results of these products showed that the performance of the Ruckus ZoneFlex 7982 and ZoneFlex 7372 802.11n indoor access points not only outperformed the 802.11n models tested from Ubiquiti and Xirrus, they also beat other vendors’ 802.11ac Wave 1 access points, including those from Aerohive, Aruba, Cisco (including Cisco/Meraki) and HP, in various test scenarios.

The results of the CARNet testing conclusively showed that Ruckus Smart Wi-Fi APs consistently delivered the highest levels of performance in all five different real-world test scenarios created by CARNet.

“The test results from CARNet speak for themselves,” said Selina Lo, president and CEO of Ruckus Wireless. “As a pioneer in adaptive radio technologies that deliver optimum throughput from unlicensed spectrum, Ruckus has continued to raise the bar in wireless performance across generations of Wi-Fi technologies, from 11g to 11ac. These tests are further testament to the strength and longevity of our innovations and differentiations.”

CARNet Wi-Fi Testing Methodology

802.11ac Wave 1 APs from Aerohive, Aruba, Cisco (including Cisco/Meraki) and HP were tested by CARNet using a wide variety of client mobile devices, both 802.11ac and 802.11n compatible, in order to closely simulate real-world environments. All APs tested were placed outside of a classroom at CARNet, separated from the client devices by 5dB (measured thickness) drywall. A real-world mix (60 total) of various mobile devices, including smartphones, tablets and laptops from different manufacturers, each with varying Wi-Fi specifications and operating systems, were used. An increasing number of clients were added for each new throughput test (measured in downstream Mbps), and each AP tested had to perform in the presence of known radio frequency (RF) interference. CARNet observed and documented the maximum throughput to all of the test client devices.

Each vendor in attendance was given an opportunity to test each of their APs themselves, to ensure they were operating as desired, and had the opportunity to optimize configurations of each AP for the best possible performance. No effort was made by CARNet to “clean up” the RF environment, as real-world deployments have to deal with random, and often uncontrollable, levels of modulated and unmodulated interference. CARNet then tested each AP three times, with the highest throughput number recorded.

In four testing scenarios in both the 2.4 and 5 GHz frequencies (one using 13 client devices; another using 23; a third using 36; and a fourth using all 60 client devices), the Ruckus ZoneFlex R700 and R500 APs consistently showed the best performance, coming out on top every time. In a fifth and final test scenario, where client devices were spread around in a 270 degree arc shape (i.e., a distributed test scenario) so that the APs would have to alternate communicating to client devices in various directions, the Ruckus ZoneFlex R700 access point was again the winner as the top performing 802.11ac Wave 1 AP.

To review the CARNet test results and detailed methodology, you can download the full report.