the measurement requirements posed by MIMO as well as a thorough discussion of MIMO itself. BROADBAND SIGNAL CHALLENGES

the measurement requirements posed by MIMO as well as a thorough discussion of MIMO itself. BROADBAND SIGNAL CHALLENGES Any signal with a broad bandwidth is susceptible to the potentially destructive effects of fading, a problem which WiMAX effectively deals with through use of OFDM. However, these signals have a very high crest factor, which means that power amplifiers must be extremely linear under every anticipated operating condition, a challenge faced by both amplifiers and the RF power transistors that empower them. OFDMA also has a complex physical layer, which makes interoperability tests a challenge. The large bandwidth of WiMAX signals also requires power amplifiers and I/Q modulators to have flat frequency response. Transmitting signals that employ higher-order modulation schemes requires very good modulation accuracy along with a receiver that can distinguish between constellation points even when noise, fading, and interference are present. So in addition to generating multiple signals, receiver tests for MIMO systems require multiple fading channels to be simulated. The end result is that testing WiMAX equipment requires high-performance instruments that can generate and analyze standards-based signals and simulate interference effects, while making the process as simple as possible for the user. The wide bandwidth of WiMAX also requires special testing of transceiver components. In a transmitter, a low-frequency or I/Q signal from the baseband chip modulates an RF carrier, which is then amplified. To optimize the performance of the transmitter, it is necessary to distinguish the performance of the baseband chip, I/Q modulator, and amplifier. This means that high-performance signal generators and signal analyzers be used to generate, demodulate, and analyze broadband RF signals, as well as their corresponding baseband signals. Figure 1. Measurement results of output burst power in tabular format. 2

AMPLIFIER TESTING The large WiMAX bandwidth signals are also a challenge for designers of power amplifiers and I/Q modulators, which are typically characterized by providing an extremely pure signal at their input and analyzing the resulting output signal to see if (or by how much) it has deteriorated. In-band deterioration is measured in terms of spectral flatness and flatness difference, which is the difference in level between adjacent subcarriers. The modulated OFDM subcarriers add up to produce an RF signal with high dynamic range, typically quantified as the difference between peak and average power (crest factor). WiMAX signals have high crest factors of about 12 db. To avoid modulation errors, the power amplifier must remain linear under these conditions, which requires simulation of two correlated fading channels and radio frequency signals. Test parameters are those recommended by amplifier manufacturers and are evaluated by changing different input parameters such as frequency, power level etc. The test parameters include output burst power, frequency error, symbol clock error, crest factor, Error Vector Modulation (EVM), Adjacent Channel Power Ratio (ACPR), spectrum flatness, spectrum difference, and spectrum mask. Output Burst Power The measurement of output power versus input power for an amplifier is one of evaluating linearity. Output power of an amplifier is typically linear until reaching a point at which it begins to cause compression. The region in which output power increases linearly with increases in input power is regarded as the linear amplification region, and is where the amplifier will perform at its best. Power measurements allow the 1 db compression point with reference to the linear region to be determined, after which further increases of the input power will cause the amplifier to work in the saturation region. For WiMAX measurements, the signal is not continuous and has a burst structure. Using the R&S FSQ, R&S FSL and R&S FSP spectrum analyzers as an example along with Option R&S FSx-K93 burst power can be measured directly as shown in Figure 1. The burst power measurements are obtained in terms of minimum RMS burst power, average RMS burst power and maximum RMS burst power. Frequency Error It is essential in a WiMAX system that the receiver accurately track the transmitter s frequency. Frequency error measurement is the carrier frequency error relative to the spectrum analyzer s center frequency. A frequency error between the transmitter and the receiver will cause shifts in the spectrum of each subcarrier relative to the FFT receiver frequencies to the point that the spectral nulls are no longer aligned with the FFT frequencies. This results in intercarrier interference (ICI). This measurement allows the frequency error to be determined when the guard period is changed. Symbol Clock Error Symbol clock error is the difference between measured and reference symbol clock relative to the system sampling rate. A symbol clock that is lower than the reference symbol clock will make the OFDM signal longer than required and cause the subcarrier spacing to decrease. A symbol clock that is greater than the reference clock will make the OFDM signal shorter and cause the subcarrier spacing to increase. This will create intercarrier interference and is detrimental to the signal s EVM performance. EVM EVM is one of the most important test parameters for ensuring that an amplifier can produce more power and yet maintain signal quality. EVM is a measurement of the quality of the modulated signal and measurement results can be used to ensure that the receiver signal-to-noise ratio (SNR) does not degrade more than a specified minimum value because of the transmitter s SNR. An amplifier may distort the input signal and therefore worsen the EVM performance because of compression effects or nonlinearities. Measurement of EVM allows amplifier quality to be evaluated with different modulation schemes. ACPR ACPR is used to characterize the distortion of amplifiers causing interference to adjacent channels. It is specified as the ratio of power measured in the adjacent 3

Figure 2. ACPR measurement display. channel to the amount of power in the main channel. The R&S FSQ spectrum analyzer allows the user to measure this test parameter easily as shown in Figure 2. The measurement results include adjacent, alternate, and second alternate channels and are taken from the lower and upper frequency bands. A measurement result is shown in Figure 3. The plot makes it possible to analyze variations in ACPR performance when the input power is varied. Spectrum flatness and spectrum difference Spectral flatness is a measurement of power variations in subcarriers of a WiMAX signal and of deviation in average power in each subcarrier from the average power over all subcarriers. Spectrum difference shows the adjacent subcarrier power difference in the preamble part of the burst. The spectrum mask evaluates the spectral profile of the transmitter to ensure that no excessive power is transmitted outside the main channel (Figure 4). The analyzer shows a limit line representing the spectrum mask for the selected frequency band. OFDMA testing OFDMA combines frequency division duplex (FDD) and time division duplex (TDD), which means that a specific amount of spectrum and time are allocated to each subscriber. Varying bandwidths and transmission times Figure 3. Measurement of worst case ACPR versus frequency for adjacent and alternate channels. 4

Featured Solution Rohde & Schwarz Test Solutions for WiMAX R&D Only Rohde & Schwarz gives you all the tools to streamline product development and speed your products to market From signal generation through signal analysis, Rohde & Schwarz offers the industry s most comprehensive test solution for development of WiMAX user equipment and base stations. Our common architecture allows baseband and RF teams to work in parallel to speed development efforts with confidence that each module tested will meet a consistent set of requirements. When wasted time can mean an opportunity lost, Rohde & Schwarz ensures you ll stay ahead of the pack. Signal Generation The R&S SMU200A signal generator Two signal generators in a single instrument for simplified MIMO development Up to 4 fading channels correlated for WiMAX channel simulation Extremely high spectral purity for highly accurate measurements For baseband generation and fading simulation R&S AMU200A baseband generator and fading simulator Same baseband architecture as the SMU200A Up to two baseband sources in a single instrument for simplified MIMO development Up to 4 fading channels correlated for WiMAX channel simulation 40 fading paths and predefined static and dynamic fading profiles For signal analysis R&S FSQ spectrum and signal analyzer A high-performance, full-featured spectrum and signal analyzer in a single instrument 120 MHz demodulation bandwidth Fixed and mobile WiMAX compliant spectrum and modulation measurements For baseband analysis R&S FMU36 baseband signal analyzer Unique combination of baseband vector signal analyzer and spectrum analyzer 72 MHz of bandwidth (36 MHz each for I and Q) FFT-based system delivers much higher sensitivity at low frequencies than superheterodyne-based designs Performs frequency-selective zero-span measurements RF RF and Baseband R&S SMU200A DUT R&S FSQ I Q Baseband Only R&S AMU200A DUT R&S FMU36 RF I Q 5

Figure 4. Spectrum mask measurement display. are allocated to users based on their needs and level of service. OFDMA offers considerable flexibility in the efficient use of resources, but accomplishes it with a complex physical layer. From the test and measurement perspective, this complexity poses a challenge for the user interface of test equipment because many parameters must be set and the impact of the parameter must be displayed both graphically and in text form. It also poses the risk that transceiver manufacturers will have configuration problems. Fortunately, emulating transmitters and receivers with signal generators and signal analyzers that have flexible parameters helps solve these configuration problems. Test equipment must not only be fast but allow changes to be easily made to WiMAX parameters. This flexibility in changing WiMAX parameters is extremely useful during interoperability testing with a signal analyzer between subscriber and base station equipment. For example, the contents of the DL-Map and UL-Map can automatically be demodulated down to the bit level, which allows the bits demodulated by the signal analyzer to be compared with those demodulated by the mobile station. During troubleshooting of an interoperability test, this is one of the first required steps because the subscriber station must demodulate the DL-Map in order to know what subcarriers to demodulate and when. Once the DL-Map is demodulated correctly, the next step is to verify the contents of the UL-Map, which tells each subscriber station how to configure its transmitter in terms of which sub-carriers to use and when to use them. The base station can only demodulate the signal correctly if the mobile station transmits its information at the requested subcarriers with the correct timing. This highlights that timing is a parameter that may cause interoperability problems. Signal analyzers can increase the speed of the troubleshooting process because they can record and display the signal in both link directions. MIMO MEASUREMENT CHALLENGES Signal generators provide standard-specific baseband or RF signals for use in MIMO receiver tests and allow flexible configuration and parameterization of the signals. For a description of MIMO, please see Appendix A. In addition to setting the usual RF parameters such as frequency, bandwidth, and power of the test signal, it is necessary to select different data and control channel combinations, modulation/coding schemes, and data sources, as well as adding impairments to the signal. Additive White Gaussian Noise (AWGN) and simulation of different propagation channels are important to stress receiver algorithms under more realistic conditions. 6

Interferer scenarios provide another challenge, requiring the coexistence of the test stimulus with other technologies. The signal analyzers required for transmitter tests and for verification of RF components analyze signals in terms of power, spectrum characteristics, and modulation quality. In the case of MIMO, it includes analysis of signals from more than one transmit antenna. While many RF tests can be performed with a single instrument, scenarios and RF performance testing require RF test systems that combine signal generators and signal analyzers. These complex test scenarios include receiver tests with specific interferer scenarios such as multiple interferers on different technologies. The instruments allow tests to be automated, which is imperative in the case of WiMAX and MIMO measurements that have very long test times. It also is useful in R&D for pre-compliance tests and to verify the RF performance of prototypes. Both non-signaling and signaling test systems are required depending on test requirements, and the RF test systems employed in R&D can be upgraded to become complete conformance test systems for use later in the development process (during the validation and certification, for example). For testing the signaling aspects of MIMO, standard-compliant protocol testers are used that act as network simulators for terminal testing. To enable MIMO operation, signaling messages (to set up bearers on the air interface, for example) must include MIMO-specific information elements. The combination of MIMO with other procedures like adaptive modulation and coding, hybrid ARQ (Automatic Repeat Request) retransmission protocols, and scheduling is another important test element. All of these tests rely on fast feedback from the terminal to the network to adapt to the conditions of the radio channel, so the latency between uplink and downlink interaction is crucial. Since one of the primary benefits of MIMO is its ability to increase throughput, verification of the end-to-end connection between terminal and network is necessary to ensure that all protocol layers can Figure 5. The user interface of the R&S SMU200A signal generator for transmit diversity tests (MISO). The signal flow is shown from the generation of the two baseband WiMAX signals on the left via the two fading channels to the RF output on the right. 7

Featured Solution Rohde & Schwarz Test Solutions for WiMAX Radio Conformance Tests Rohde & Schwarz, with its R&S TS8970, has been selected by the WiMAX Forum as the official supplier of radio conformance test equipment The TS8970 was developed in cooperation with chipset and device developers worldwide and was chosen over all others as the test and measurement partner for the respected M (Mobile)-Taiwan Program. R&S WiMAX RCTT Wave 1 MS Test Setup R&S ISSCU In-band Switching Signal Conditioning Unit Now in its third generation, the TS8970 has been finely tuned to provide fast, repeatable, highly-accurate results, while remaining remarkably easy to use. The TS8970 is the choice of end users and infrastructure equipment manufacturers throughout the world. R&S TS8970 Key Features Fully-automated test system for Wave 1 transmitter and receiver tests R&S NRP Power Sensor USB R&S Controller R&S FSQ Signal Analysis BB faded R&S SMU 2x Interferer/ sync BB faded 802.3 (Ethernet) BB faded BB faded R&S SMU TX want sig/ Interferer/ R&S FSL RX Wanted Signal SISO WiMAX BSE/MSE Based on best-in-class Rohde & Schwarz vector signal analyzers and generators and industry proven software Comprehensive yet easy-to-use user interface reduces operator training R&S WiMAX RCT Test System R&S Signal Generation Provides true performance margin evaluation rather than just simple pass/fail results Dedicated debugging features for quick solutions to tough problems R&S BB Fading/ Interferer Future-proof design for seamless upgrades as standards evolve Hardware and software-ready for Wave 2 WiMAX BSSE R&S RF SSCU R&S Controller R&S Power Sensor R&S FSQ Signal Analysis 8

Figure 6. The signal flow is shown from the generation of the baseband WiMAX signal on the left via the two fading channels to the two RF outputs on the right. handle the high data rates required for high quality of service. Both downlink and uplink MIMO testing is important and of the two, downlink MIMO testing is the most challenging. Downlink MIMO testing refers to verification of MIMO functionality and performance in base station transmitters and mobile station receivers. For terminal receiver testing, a base station MIMO transmitter must be provided as the stimulus for different test scenarios. For a 2x2 MIMO system, two baseband signals and two RF signals must be generated for two different transmit antennas. For higher-order scenarios like 4x4, even more signals are needed. As should be obvious, measurement solutions for MIMO testing can easily become quite complex, so it is essential to limit the testing efforts whenever possible. MIMO receiver tests and fading channel simulation Receiver performance tests require a fading channel simulation in order to reflect realistic radio channel conditions. WiMAX conformance tests specify the propagation conditions for different test scenarios. Fading simulation is especially important for MIMO, because its performance is significantly influenced by propagation conditions. Fortunately, complex models are able to simulate realistic radio channel conditions in different environments by incorporating stochastic modeling of parameters. However, they require long simulation or test times and are not necessarily the best choice for mobile radio R&D and conformance testing. Less complex models may still provide sufficiently good performance with reproducible results in these environments. Fading channel models for Single Input Single Output (SISO) systems have been in use for many years, and reflect the propagation conditions in different environments by modeling the positions of base station and terminal as well as the expected impact of the environment on the propagation. These channel models can also be used to simulate Multiple Input Single Output (MISO) and Single Input Multiple Output (SIMO) setups for transmit and receiver diversity. Figure 5 shows an example setup of a signal generator for a transmit diversity receiver test. In the scenario depicted in Figure 5, the signal generator provides two baseband signals (baseband A and 9

Figure 7. User interface of the R&S SMU200A signal generator for 2x2 MIMO tests. The signal flow is shown from the generation of the two baseband LTE signals on the left via the four fading channels to the two RF outputs on the right. baseband B) corresponding to two different transmit antennas. The baseband signal can be selected according to a certain standard and can be parameterized flexibly in terms of bandwidth, power, resource allocations, and data sources. In order to reflect spacetime coding for transmit diversity, a different coding type can be selected for each of the two antennas. Two baseband fading simulators make it possible to add propagation effects to the transmit signals of each antenna. Different propagation models can be selected. For SIMO or receiver diversity testing, a set-up like that shown in Figure 6 would be employed. The signal generator provides one baseband signal according to one transmit antenna. The transmit signal is input into two fading simulators with correlated or uncorrelated fading. Afterward the signals are converted to RF and provided to two RF outputs to connect to the dual antenna terminal. The channel models for the SIMO and MISO case must be extended for MIMO systems in order to reflect the spatial dimension. The broader bandwidths of WiMAX must also be considered. In a MIMO system, the channels between each of the transmit antennas and each of the receive antennas must be modeled separately. In a 2x2 system, four channels can be modeled independently. Assuming uncorrelated fading processes on the different channels is likely to be too optimistic, so correlation parameters must be reflected as well. Extension of the ITU models employed for traditional wireless networks is one approach for a WiMAX MIMO channel model that has a reasonable level of complexity and good performance. However, for WiMAX, pedestrian and vehicular channel models are extended to incorporate spatial correlation matrices for each multipath component. A test set-up for 2x2 MIMO receiver tests is shown in Figure 7. Here the signal generator provides the baseband signals for two transmit antennas. Besides space time coding for the two antennas, selection of precoding matrices may be desired to create typical MIMO signals. Four baseband fading simulators provide the fading characteristics for the channels between each transmit and each receive antenna and correlation 10

properties can be individually set. For full flexibility, it is possible to specify the full complex correlation matrix for each multipath component, but it is also possible to use a simplified model and specify only complex correlation coefficients between the transmit and receive antennas. The faded signals are then summed before RF conversion and provided to the two RF outputs that can be connected to the dual antenna terminal. MIMO transmitter tests Signal analyzers are employed for MIMO base station transmitters in the downlink case. The typical transmitter measurements are performed to ensure that the transmit chain fulfills the requirements of output power, frequency error, RF spectrum emissions, and modulation accuracy. These measurements can be made separately with the signal analyzer for each antenna. Each MIMO antenna port usually transmits a different pilot pattern so that the receiver is able to distinguish the antenna signals and do the channel estimation. MIMO conformance tests MIMO is also important in conformance testing for both RF and signaling parameters. The WiMAX Forum evaluates a number of MIMO-specific mobile radio conformance tests for terminals and base stations in the context of its Wave 2 radio certification tests. The tests address pure RF requirements as well as verification of MIMO operation in combination with other procedures. Both receiver and transmitter tests for base stations and terminals are included. For mobile station receivers, MIMO may be tested based on the demodulation and decoding performance for Matrix A and Matrix B (See Appendix A for information about these two matrices), with block error rate (BLER) as the performance measure. The test includes different modulation and coding schemes and various fading channel conditions. The feedback mechanism from the terminal to the base station must also be verified to determine if the mobile is recommending the correct MIMO mode Matrix A or B based on a certain pre-defined channel condition. On the base station side, transmit MIMO processing must be verified, including pilot formatting for Matrix A and Matrix B and evaluation of modulation quality (error vector magnitude, EVM) for each transmit chain. Beamforming WiMAX systems can employ transmit and receive beamforming, which adds to the measurement challenge. Transmit beamforming, for example, requires verification of whether the mobile receiver can handle the reception of dedicated pilots. Receiver sensitivity for different modulation and coding schemes and test channel conditions including AWGN and fading must also be tested. There should not be any degradation in receiver performance caused by the higher power generated by beamforming. The base station performance for transmit beamforming must also be tested, and correct signaling of dedicated pilots verified. Test scenarios for uplink MIMO are also important to see if the mobile can use the correct uplink subchannels and uplink pilot patterns. This is important in the WiMAX uplink, because different terminals may simultaneously access the same radio resource (transmit collaborative MIMO) and correct operation of the scheme is essential to avoid uplink interference. Verification of power boosting on the uplink pilots is also desirable. On the base station side, verification of uplink MIMO is strongly recommended. The base station receiver must support the collaborative MIMO features. That is, it must be able to correctly demodulate and decode Matrix B MIMO transmissions from two terminals. Base station receiver sensitivity must be good enough to cope with mixed modulation and coding schemes and different transmit power values from the two different terminals. Appendix A MIMO and its meaning for WiMAX Much has been made over the years of using multiple antennas in wireless communications systems as a way to allow network operators to increase the capacity of their networks while maintaining a high quality of service. More than likely, the first time consumers experienced the Multiple Input Multiple Output (MIMO) technique was in their cars, where receive diversity is used to provide better reception under widely varying mobile signal conditions. However, it is also employed in professional wireless microphones and wireless guitar systems. Based on the needs of coming generations of extremely-high-speed wireless networks, of which WiMAX is one, MIMO will become a standard feature 11

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in these systems in the future. MIMO is a fundamental part of the WiMAX IEEE 802.16-2004 and IEEE 802.16e-2005 standards that are based on OFDM and OFDMA respectively. While IEEE 802.16-2004 is primarily focusing on transmit diversity, spatial multiplexing has additionally become an essential part of IEEE 802.16e-2005 standard. WiMAX MIMO modes are referred to as Matrix A and Matrix B. Matrix A is the WiMAX downlink transmit diversity scheme based on space-time coding according to Alamouti. Each information symbol of the data stream is sent out of the two transmit antennas, but interleaved over time and with a predefined coding applied. This provides the benefit of making the link more robust and increasing reception probability. Matrix B refers to spatial multiplexing, which can use either single or multiple code word transmission, called vertical or horizontal encoding respectively. Feedback signaling from the terminal to the base station for MIMO mode selection and channel quality reporting is also likely to be employed in WiMAX. Switching between Matrices A and B is possible based on channel conditions, and the network informs the terminal how long a certain MIMO mode is active. The WiMAX specifications go even further, to include transmit and receive beamforming based on detailed signals, with up to eight antennas. On the uplink side, WiMAX proposes a Transmit Collaborative MIMO principle similar to the uplink MU-MIMO scheme proposed for LTE. Different mobile stations are assigned to the same sub-channel and simultaneously transmit over the same radio resource using a different pilot pattern. Only one transmit antenna is needed on terminal side. The base station determines uplink resource allocation. N t antennas The meaning of MIMO The term MIMO is a very broad term, since in its most elemental form simply refers to the use of more than one antenna for transmitting signals, receiving them, or both, along with multiple input and output signals. The basic MIMO concept is shown in figure 8. MIMO exploits the spatial dimension of the radio channel. Systems with one transmit and one receive antenna are called SISO (Single Input Single Output) systems, and systems with one transmit antenna and two receive antennas are called SIMO (Single Input Multiple Output) systems. A SISO system can exploit the benefits of receive diversity. A system with two transmit antennas and one receive antenna can also be referred to as MISO system (Multiple Input Single Output), which can exploit transmit diversity. The most likely scenario for MIMO in WiMAX applications is the 2 x 2 MIMO approach, in which two transmit and two receive antennas are employed. MIMO technology can be applied to either the downlink or uplink of a system, the downlink being the base station transmitter, and the mobile (or fixed) terminal being the receiver. The uplink is just the reverse of this. From the perspective of user equipment, cost as well as available real estate constrains the incorporation of MIMO, so it is more common for base stations to have more antennas than user equipment. How MIMO benefits performance Extensive research has shown that MIMO can significantly enhance the performance of data transmission. Diversity gains can increase the quality of data transmission, and spatial multiplexing gains can increase the throughput of data transmission. In practical application however, these two benefits can conflict, so that N r antennas Transmitter Receiver Figure 8 The basic principle of a MIMO system, showing Nt transmit and Nr receive antennas. 13

MIMO algorithms either provide diversity or multiplexing gains but not both, the result being determined by the type of signal processing employed by the system. Diversity gain is accomplished by receiving the same data stream over multiple (ideally independent) propagation paths. In a transmit diversity or MISO system, multiple transmit antennas simultaneously send the same data stream. In a receive diversity or SIMO system, multiple receive antennas receive the data stream sent by one transmit antenna. In either case, the receiver captures multiple copies of the same signal. The effects of fading can be minimized because all received signals are not likely to be affected by fading in the same way. While the presence of multipath fading channels is important to exploit diversity gains, the proximity of the antennas at the transmitter and receiver require that the fading channels are correlated in amplitude and phase. The higher the correlation of the fading channels, the lower the diversity gain. The job of the receiver is to combine versions of the same signal by maximum ratio combining or selective combining. Diversity gain can improve the quality of the received signal and also increase coverage area provided by a base station, reducing the number of sites required by a network. There is however, a number of antennas above which diversity gain saturates and no further gains are possible. Spatial multiplexing gain is accomplished by simultaneously sending different data streams over the same radio resource, which can dramatically increase throughput and bandwidth efficiency. The streams are only discriminated by the spatial dimension each stream is sent on a different layer of the radio channel together with a specific pilot or reference signal sequence. The receiver can distinguish the data streams sent from the different transmit antennas by their pilot sequence and can perform channel estimation for each stream separately. While it is theoretically possible to increase the channel capacity of a MIMO system linearly with the addition of antennas, in reality the actual number of antennas is limited by the complexity of signal processing algorithms and RF subsystems. It is also a challenge to optimally array multiple antenna elements, especially on end user equipment. Radio channel characteristics do not always allow optimum capacity gains, and spatial multiplexing requires a minimum channel quality so it is not applicable anywhere at any time. It is important to understand the difference between single-user and multi-user MIMO systems (SU- and MU-MIMO). In SU-MIMO, the data streams transmitted simultaneously belong to one user, so the data rate this user can achieve can be dramatically increased. The information symbols transmitted to this user are split into independent data streams that are emitted by the different antennas. Conversely, in MU-MIMO systems, the data streams transmitted simultaneously belong to different users, so the total capacity of the system is increased because of spatial multiplexing gain. Generally speaking, spatial multiplexing gain can only be fully exploited if data streams can be detected and recovered correctly in the receiver, which must solve a linear system of equations (for 2x2 MIMO two equations with two unknowns). This is possible if the channel matrix H has full rank, which is achieved if each antenna receives a different channel as is true in strong multipath environments with spatially uncorrelated fading. In summary, MIMO systems can exploit the multipath characteristics of the radio channel, which makes them a good choice for WiMAX and other wireless communication systems. The maximum number of data streams that can be transmitted over a radio channel is equal to the rank of the channel matrix. Since the radio channel is time-varying, the characteristics of the channel matrix must be evaluated continuously and when the channel matrix does not have full rank, the full spatial multiplexing gain will not be achievable, so transmit diversity may provide a good alternative to a MIMO scheme like transmit diversity. MIMO and protocol layers While MIMO falls into the discipline of RF technology, its implementation also affects protocol layers and their interaction with the physical layer. It is interesting to note that WiMAX and the future paths of traditional wireless services such as UMTS Long Term Evolution (LTE) have many features in common. Like WiMAX, these systems must also be optimized for packet data services with high data rates. So instead of conventional dedicated channel operation (like circuit switched voice services), shared-channel operation will be employed. In the dedicated channel approach, 14

Featured Solution Rohde & Schwarz Test Solutions for WiMAX MIMO Rohde & Schwarz gives you all the tools you need to ride Wave 2. The complexity of implementing Multiple Input Multiple Output (MIMO) capability in WiMAX presents unique measurement challenges but Rohde & Schwarz makes it simple. In fact, our R&S AMU200A baseband signal generator and R&S SMU200A RF signal generator are the only instruments that integrate two signal sources and four independent fading channels in a single unit. Combine them with our R&S FSQ RF signal analyzer and R&S FMU36 baseband signal analyzer and you ll see why the Rohde & Schwarz WiMAX Wave 2 MIMO Solution is the only sensible choice for both baseband and RF 2x2 MIMO receiver testing with dramatically reduced test complexity. R&S AMU200A 2x2 Mimo Baseband Only I Q I Q 2x2 Mimo RF Only RF DUT I Q I Q RF R&S FMU36 R&S FMU36 R&S FSQ RF RF R&S SMU200A DUT R&S FSQ 2x2 MIMO Solution with SMU200A 15