MIMO the Future of Wireless

8/10/2019 MIMO the Future of Wireless

1/5

As seen in the July 1, 2008 edition of the RF Globalnet (www.rfglobalnet.com ) newsletter.

MIMO: The Future Of Wireless

Test Challenges For WiMAX, HSPA+, And LTE

This article is part of a series of quarterly guestcolumns by Mark Elo, RF Marketing Director,

Keithley Instruments, Inc.

Introduction

Mobile communications, along with the underlying technology that provides voice anddata service, is evolving to provide higher data rates in the same frequency spectrum toan ever-growing user base. New communications standards are using multiple-inputmultiple-output (MIMO) techniques to maximize throughput and coverage whilepreserving bandwidth.

MIMO takes spectral efficiency to a new level, but with better spectral efficiency comesa higher level of complexity. MIMO employs more radio carriers to transmit moreinformation, improving spectral efficiency by transmitting all the signals on the samechannel occupying the same bandwidth.

This increased complexity poses new testing challenges for design and test engineers.

MIMO Concepts

MIMO is based on the principle of accurately modeling the transmission channel todecompose the multiple received symbols back into single data streams. As shown inFigure 1 , for instance, an 802.11n WLAN transmitter transmits a known signal in theform of a header. The receivers then use this to build a model of the channel, representedby H. When the data is transmitted, the receiver divides through by the channel model(H) to get as close to the original vectors given the transmission error represented by thenoise vector (n).


2/5

Guest Column


Figure 1: Understanding the transmission channel

The concept of modeling the channel applies to all MIMO systems. However, the methodvaries from standard to standard. For example, 802.11n WLAN transmits the headerinformation on both TX1 and TX2, while WiMAX 802.16e Wave 2 transmits the headeronly on the first transmitter. The resolved transmission path, h11 and h22, are called thespatial streams.

Measurement System Time Alignment

The channel distorts the signal in many ways. For example, reflections off of surroundingobjects can cause multiple instances of the signal to arrive at the transmitter at differenttimes. This multi-path phenomenon introduces amplitude degradation and time and phasedelays. The more channel distortion added to the signal, the more likely the receiveralgorithms can solve for the originally transmitted signals. If the transmitter or thereceiver further adds amplitude, time, and phase errors, the channel will not be accuratelymodeled, and the symbols will not be effectively resolved.

There are a few key measurement parameters that help determine the quality of the signaland signal channel in MIMO systems.

Modulation Quality Metrics : As with most traditional digital transmission systems, thekey modulation quality measurement is the actual received symbols vector (or symbolphase and amplitude distortion) compared to what the receiver expected. The mostcommon measure is error vector magnitude (EVM), but other variants exist such as therelative constellation error (RCE). For a MIMO system, overall EVM is still a good


3/5

Guest Column


measurement, although an RMS EVM can be calculated to give an overall indication ofmodulation quality across transmitters.

Constellation Diagram : This gives a pictorial representation of the quality of the receivedsignals. Depending on the configuration of the MIMO system, there will be multiple

constellation diagrams. A 2 x 2 system will have two constellations representing bothresolved spatial streams, h11 and h22. A 4 x 4 system would have four constellations, andso on. As with traditional digital systems, the same qualitative measures, such as phaseerror, noise, and IQ balance, can be derived from the constellation diagram.

Channel Response : This is a key indicator of spatial stream behavior, as shown in Figure2.

Figure 2: Channel response

Using antennas or, for a more quantitative measure, a channel emulator, an accuratemodel of the channel can be derived. This helps the transmitter designer understand howrobust the transmission is under varying channel conditions using the calibrated receiveras the reference. The receiver can also be tested in the same way using different channelmodels to stress the receiver. These signals can be generated by applying the appropriatechannel distortion to a standard waveform using an arbitrary waveform generator or by

using a real-time channel emulator.

The performance of a MIMO system is dependant on the behavior of the channel. So, thetransmitter and receiver must be tested using a multitude of channel models, both frompre-defined standards and by user-defined models, to ensure the design maintainsperformance across a multitude of environments .


4/5

Guest Column


Matrix Condition and Singular Values : Like EVM, the matrix condition number is a goodindicator of transmitter performance. It is essentially a measure of how orthogonaleach spatial stream is. For example, a VSA (vector signal analyzer) connected to thetransmitter using cables should yield a matrix condition close to unity or 0dB. If not, thenthe transmitter may be creating some inter-stream interference. This could be due to a

mathematical error in the DSP (digital signal processor), or a problem in the RF section,as the matrix condition is the ratio of the largest singular value to the smallest. Acommon measurement approach is to monitor the matrix condition number until there isan unusually large value and then switch to monitoring the actual singular values tounderstand the matrix solution.

Stream Performance

Individual transmitted stream performance can be analyzed in a number of ways. Forinstance, the instantaneous value, the power or EVM of each stream, and using a time or

frequency domain display, i.e. EVM over frequency or time.Measuring EVM, amplitude, or frequency error over a time period helps identifyproblems associated with each radios behavior over time. For example, a glitch in one ofthe radios transmitter FPGAs (field-programmable gate arrays) may cause a periodicerror in the EVM.

With a parallel symbol transmission scheme based on orthogonal frequency divisionmultiplexing (OFDM), the time increments are usually referred to as the OFDM symbolperiod, as each increment can contain many thousands of symbols. For example,WiMAX can transmit between 128 to 2048 symbols per OFDM symbol period. A typicalOFDM symbol map will have a vertical axis labeled subchannel logical number. Thesubchannels are not actually physical channels, but groupings of parallel symbols that aretransmitted every OFDM symbol period. How the WiMAX signal is constructed andbehaves over time is defined in the symbol map. The symbol map is essentially a 2 x 2matrix of symbols, the vertical being the parallel symbols, and the horizontal representingsymbol behavior over time.

Measuring EVM, or amplitude over frequency, will help identify in-band problems suchas low-level spurious interference that may be generated by a clock within the radio.

Beam Forming

One of the key benefits, and in fact one of the original uses of MIMO, is the ability toalign RF energy to specific users through the process known as beam forming. Many ofthe standards for commercial systems have provisions for MIMO beam forming, alsoknown as closed-loop MIMO. Beam forming has the benefit of delivering more capacityto users. However, it does increase the complexity of the device, as an array oftransmitters, receivers, and antennas are required to control the direction and shape of the


5/5

Guest Column


radiated signal. The direction and shape are a function on the channel environment.Techniques such as channel sounding are used to model the channel and to establish thecorrect phase and amplitude of the beam.

Beam forming research today is based upon developing higher configurations of radios

within devices to truly maximize the amount of services that can be delivered to acustomer. 8 x 8 and even 16 x 16 radio configurations are leading the way in commercialbroadband radio research.

Test equipment needs to have the ability to control the phase and amplitude of eachsource to be able to build the required RF radiated patterns based on the calculatedknowledge of the channel.

For effective, accurate MIMO measurements, test equipment, such as signal sources andanalyzers, need to phase align their local oscillators and time align frequency references,and D/A (digital-to-analog) and A/D (analog-to-digital) sample rates in order minimize

their contribution to the channel. Ideally, phase errors of less than a degree and ananosecond of timing alignment will yield an accurate result.

Conclusion

MIMO is one of the most important shifts in commercial radio technology since the movefrom analog to digital transmission techniques. Next-generation standards such asWiMAX, HSPA+ (Evolved HSPA), and LTE (Long Term Evolution) are all MIMO-based systems, presenting many new challenges for commercial communicationequipment designers. As users demand more and more services and more reliableconnections, MIMO systems will evolve to encompass techniques such as beam forming,increasing the amount of transmitters, receivers, and antennas in a device.

About The Author

Mark Elo ( [email protected] ) is RF marketing director for Keithley Instruments. He joined the company in 2006 after working for Agilent Technologies in marketing andR&D management positions. Elo holds a bachelor's degree in engineering with honorsfrom the University of Salford, Lancashire, England, and an MBA from Heriot WattUniversity in Edinburgh, Scotland.

MIMO the Future of Wireless

Documents

Transcript of MIMO the Future of Wireless