Intel researches wireless antenna technology

As the popularity of wireless devices at businesses (Wi-Fi, PDAs and RFID) and in homes (PCs, Bluetooth devices, home entertainment and so on) accelerates, the need for high-quality, high-throughput wireless bandwidth is emerging as a key constraint on growth.

To address this demand, new innovations are needed. Emerging specifications, such as 802.11n and 802.16, open new areas in which Intel has performed extensive research: the use of smart antennas, which can improve signal quality and the distances over which wireless signals operate. Depending on their specific design, smart antennas can also increase the point-to-point or network throughput of wireless devices.

What Are Smart Antennas?

Television and radio broadcasts as we know them use a traditional system of communication:Oone antenna transmits a signal and a second antenna receives it. This configuration is called single-input, single-output (SISO). Many wireless systems today use the same basic design: one antenna at the access point transmits and another, in a notebook computer or other device, receives the data.

New radio technologies are increasingly examining designs in which transmission and reception use multiple antennas at both ends of the communication. This approach is called multiple-input, multiple-output (MIMO), and it is shown in Figure 1. To handle multiple signals, these MIMO systems need greater smarts than simple SISO configurations. As a result, these multiple antenna systems are referred to as smart antenna systems.

antennas_figure.jpg
The basic principle of smart antennas is that each antenna receives a separate and distinct signal. Depending on how the wireless system is set up, the receiver might combine the signals from multiple signals to improve the quality of data reception; or it might extract multiple data streams to increase bandwidth.

Extending Range by Improving Signal Quality

Technologies that compare the quality of signals from two antennas and choose the stronger one can substantially increase signal quality. Let's examine a common scenario in which a user is working across a Wi-Fi connection in a busy public place. When the Wi-Fi access point transmits data, the signal is subject to fading if an object (such as a person walking by or standing between the two devices) appears between the access point and the receiving device. If both signals were received by a device with two antennas, the device would switch to the better signal if the one it was using began to fade, a technique called switched diversity.

This simple approach monitors the two antennas and switches back and forth as signals gain strength or fade in relation to each other. Signal fade is the gating factor on the transmission distance for wireless signals. Switched diversity can benefit users by increasing the distance over which they can enjoy reliable wireless connectivity.

In addition to fade, signals can also be corrupted by noise. This is especially true on Wi-Fi frequencies because many wireless devices (including mobile phones and even microwave ovens) share the unlicensed spectrum. Smart antennas can aid in reducing noise by combining signals from both antennas. When these signals are combined, the transmitted signals reinforce each other, while the noise either remains at a constant power level or can be effectively canceled.

This concept of combining signals can be enhanced further through techniques that mathematically compare signal quality in real time and combine them based on weights assigned to signal quality. In analog combining, the radio frequency signals are synced and then weighted according to signal strength and noise levels. The signals are then combined to produce an optimal radio frequency in terms of the ratio of signal power to noise. This optimized signal is then sent to the digital circuits to be digitized.

A similar, more advanced technique uses digital combining and is especially effective for radios using orthogonal frequency division multiplexing. With OFDM, transmission is done using many frequencies. This allows the radio signal transmission to be split into multiple smaller subsignals that are then transmitted simultaneously at different frequencies to the receiver.

The subsignals from each antenna are routed to the receiver's digital circuitry where they are weighted and combined to produce the optimal signal. Because the subsignals arrive at numerous different frequencies simultaneously, the weighting process is complex and requires advanced processing capabilities. In return, it generates a near-optimal signal.

Tests show that digital combining generates the highest-quality signal, followed by analog combining, and finally, switched diversity. When working at near-optimum levels, the results can extend distances by 1.4x for every 2x increase in the number of antennas at both ends of the transmission.

Another option that involves both the transmitter and receiver is space-time (or space-frequency) coding, where signals are transformed and delegated to specific antennas, frequencies or symbols in time. This is a mechanism for lessening the effects of multipath signal fading at the transmitter as well as the receiver.

Increasing Throughput by Transmitting Multiple Streams

The techniques discussed in the previous section increase signal range by improving the signal quality. However, smart antennas can also be employed to dramatically increase throughput.

One way of increasing aggregate network bandwidth is to equip the access point with multiple antennas and simultaneously service multiple users. In this way, each endpoint derives the benefit either through its own connection to the access point or at a minimum in a reduction in the number of other devices contending for the connection.

In this approach, called spatial division multiple access (SDMA), only the access point needs multiple antennas. However, protocol and scheduling changes need to be made to take full advantage of the increase in network throughput, which is nearly linear with the number of antennas at the access point. Double the number of antennas and the aggregate throughput nearly doubles.

MIMO systems can improve throughput on a point-to-point link. In MIMO configurations, data streams are broadcast across multiple antennas simultaneously. The receiving device then combines the received signals to reconstruct the multiple transmitted data streams.

The throughput of this approach scales in a linear manner with the number of antennas at both ends of the transmission: If the number of antennas is doubled at both ends, the resulting throughput doubles. Because MIMO requires symmetric antenna counts to improve throughput, if one point has four antennas and the other has three, the total improvement is 3x -- the extra antenna does not add throughput (although it can be used to improve signal quality). MIMO is being considered by the IEEE as a technique for the next generation of WLANs.

Summary

Smart antennas have been shown to deliver 1.4x gains in signal range and 2x gains in data throughput, for a 1x2 (one transmit antenna and two receive antennas) and 2x2 system, respectively. As a result, they are likely to begin appearing in wireless devices during the next few years.

The IEEE 802.11n and 802.16d/e committees are actively working on the best way to implement smart antennas. Intel Corp. has been an active participant in both committees, based in large part on the research it performed on antenna systems and on the best use of silicon processors to support signal processing.

Once these standards have been formalized, Intel expects to work with original equipment manufacturers and other hardware manufacturers to implement smart antenna systems, so that such systems will soon be considered a standard part of all wireless devices.

Minnie Ho co-manages a group for physical-layer research in Intel's Radio Communications Lab, part of the Corporate Technology Group. She holds master's and Ph.D. degrees from Stanford University in electrical engineering, and a bachelor's degree in electrical engineering from Princeton University.

Larry Swanson is a technical marketing engineer and manages the technical marketing group for Intel's Communications Technology Lab, part of the Corporate Technology Group. He is currently working on obtaining his MBA from Concordia University in Portland, Ore.

Copyright © 2005 IDG Communications, Inc.

It’s time to break the ChatGPT habit
Shop Tech Products at Amazon