Using a design-to-test capability for LTE MIMO (Part 2 of 2)

Transcription

1 Using a design-to-test capability for LTE MIMO (Part 2 of 2) System-level simulation helps engineers gain valuable insight into the design sensitivities of Long Term Evolution (LTE) Multiple-Input Multiple-Output (MIMO) systems By Greg Jue and Dingqing Lu, Agilent Technologies (Part 1 of this article looked at baseband design, and RF mixed-signal transmitter design.) Receiver RF/mixed-signal design While EVM is a typical system-level metric for transmitter MIMO performance, BER can be a useful metric for evaluating MIMO receiver performance. In particular, the closely spaced subcarriers used to achieve high data rates in OFDMA systems like LTE MIMO are susceptible to receiver design impairments such as phase noise and ADC jitter. Figure 6 depicts a dual RF receiver that was designed to downconvert two MIMO RF streams to IFs. Figure 6. This RF/mixed-signal receiver design utilizes ADI ADC converters. It consists of two RF-IF downconverters with bandpass filters, amplifiers and mixers, which are used to convert the MIMO RF to analog IFs. The MIMO IF outputs from the RF-IF downconverters are digitized by Analog Devices ADI ADC converter simulation models. The

2 resulting digitized MIMO signals are then fed into a baseband receiver to perform the baseband post-processing needed for coded-ber simulation measurements. Figure 7 shows the coded-ber simulation results for the swept jitter on the ADI ADC converter models versus swept SNR. Figure 7. Shown here are the results are the coded-ber simulation results for swept ADI ADC jitter. The simulations were performed for QPSK (left), 16QAM (middle) and 64QAM (right). BER is the y-axis on each plot and swept SNR is the x-axis. The BER curves for 2 percent, 4 percent and 6 percent jitter are depicted on the lower blue traces, the middle red traces and the top green traces, respectively. Here, jitter is defined as the inverse of the MHz system clock rate (simulation sampling rate). The ADC jitter impacts the 64QAM case more significantly than the 16QAM or QPSK cases because of the closer constellation states, illustrating that the system engineer may need to consider tighter design requirements to support higher LTE data rates when moving from QPSK to 64QAM. Although not shown, receiver BER simulations were also performed for swept LO downcoverter phase noise. R&D hardware DUT testing During prototype testing, it is often useful to fully characterize R&D device under test (DUT) hardware. This helps the engineer determine DUT sensitivities to various parameters such as

3 bias, RF power and fading. Combining simulation with test equipment provides flexibility in R&D DUT hardware testing. As an example, consider that the engineer wants to perform coded-ber hardware measurements on DUT hardware by combining the simulation baseband receiver discussed in the previous section with test equipment. Figure 8A and Figure 8B depict a MIMO BER test setup utilized for making coded-ber measurements. This configuration uses the following: Agilent SystemVue to generate the simulated MIMO test signals with or without simulated fading, A PXB receiver tester to generate the MIMO real-time multipath fading signals from the SystemVue simulated waveforms, Two ESG signal generators to convert the baseband signals to RF test signals that would be input into a receiver DUT, and Two MXA signal analyzers to capture the MIMO test signals for post-processing with SystemVue s baseband receiver. Note that real-time fading is applied with the PXB receiver tester to test receivers under various fading profiles. Time synchronization of the waveforms being captured by the signal analyzers is achieved with external triggering from the PXB to the two MXAs. Here, the PXB marker (MRK1) connects to the master MXA trigger 1 in, while the master MXA trigger 1 out connects to the slave MXA trigger 1 in. Figure 8A. Multiple instruments are required for this 2x2 MIMO hardware test setup.

4 Figure 8B. The actual hardware required for the test setup in Figure 8A is depicted here. SystemVue is installed manually in the PXB receiver tester as a custom application. This enables the simulated waveforms to be easily and conveniently downloaded to the PXB. Figure 9A through Figure 9D shows the measurement results. Figure 9A. The input LTE FDD signal is shown without multipath fading. Main time is depicted on the top traces, while spectrum is depicted on the bottom traces.

5 Figure 9B. This graphic shows the measured results for the LTE FDD signal with no fading. Figure 9C. The input LTE TDD signal, with multipath fading, is depicted by the traces in this image. Figure 9D. This graphic shows the measured results for the LTE TDD signal with fading. Summary

6 The complexities of LTE MIMO introduce a multitude of system design challenges for the system engineer, including system-level baseband/rf design requirements partitioning and baseband/rf system integration risks. Simulation helps the system engineer gain valuable insight into system-design sensitivities, ensuring that a design meets specifications without having to be over-designed. Visibility into baseband/rf system-integration risks helps the engineer achieve time-to-market and development cost goals by addressing potential issues early in the design cycle where they are easier and less costly to fix. The case studies presented in this article have highlighted the key benefits of system-level simulation. Transmitter EVM design sensitivity was investigated under various baseband and RF design impairments, including baseband design fixed-point precision, RF antenna crosstalk coupling and LO phase noise. Receiver BER performance was evaluated as a function of swept ADC jitter for QPSK, 16QAM and 64QAM modulation depths. Simulated baseband functionality was then combined with test equipment to enable coded-ber measurements to be performed on R&D DUT hardware. This integrated design-to-test capability helps the system engineer gain valuable insight into design sensitivities and evaluate what-if scenarios to help mitigate system design and integration risks throughout the LTE MIMO development lifecycle. References 1. Agilent Technologies (publisher), LTE and the Evolution to 4G Wireless: Design and Measurement Challenges, (2009). Edited by Moray Rumney,Table 1.4-1, ISBN Agilent Technologies, White Paper on LTE PHY Design, About the Authors \Greg Jue is an applications development engineer/scientist with Agilent EEsof Electronic Design Automation (EDA), specializing in SDR, LTE and WiMAX applications. Greg wrote the design simulation section in Agilent s new LTE book, and has authored numerous articles, presentations and application notes, including Agilent s new LTE algorithm reference whitepaper and Agilent s new Cognitive Radio whitepaper. Greg pioneered combining design and test solutions at Agilent Technologies, and authored the popular application notes 1394 and 1471 on combining simulation and test. Before joining Agilent in 1995, he worked on system design for the Deep Space Network at the Jet Propulsion Laboratory, Caltech University. Dingqing Lu has been with Agilent Technologies/Hewlett Packard Company since 1989 and is a scientist in Westlake Village, CA, USA. From 1981 to 1986 He was with University of Sichuan as Lecturer and Assistant Professor. He was a Research Associate in EE Department of UCLA, Los Angeles, USA from 1986 to He published about 20 papers in IEEE Trans, Journals and Conference proceedings. His research interests include modeling, simulation and measurement techniques for systems.