QPSK and OFDM with MATLAB System Objects
This example shows how to simulate a basic communication system in which the signal is first QPSK modulated and then subjected to Orthogonal Frequency Division Multiplexing. The signal is then passed through an additive white Gaussian noise channel prior to being demultiplexed and demodulated. Lastly, the number of bit errors are calculated. The example showcases the use of MATLAB® System objects™.
MIMO-OFDM Wireless Communications with MATLAB® Book Abstract: MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE, Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE 802.11a, IEEE 802.11n), wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB).
Set the simulation parameters.
Construct System objects needed for the simulation: QPSK modulator, QPSK demodulator, OFDM modulator, OFDM demodulator, AWGN channel, and an error rate calculator. Use name-value pairs to set the object properties.
Set the QPSK modulator and demodulator so that they accept binary inputs.
Set the OFDM modulator and demodulator pair according to the simulation parameters.
![Mimo ofdm matlab code pdf pdf Mimo ofdm matlab code pdf pdf](/uploads/1/2/4/7/124728744/583051622.jpg)
Set the
NoiseMethod
property of the AWGN channel object to Variance
and define the VarianceSource
property so that the noise power can be set from an input port.Set the
ResetInputPort
property to true
to enable the error rate calculator to be reset during the simulation.Use the
info
function of the ofdmMod
object to determine the input and output dimensions of the OFDM modulator.Determine the number of data subcarriers from the
ofdmDims
structure variable.Download bauknecht gsf 4761 manual. Determine the OFDM frame size (in bits) from the number of data subcarriers and the number of bits per symbol.
Set the SNR vector based on the desired Eb/No range, the number of bits per symbol, and the ratio of the number of data subcarriers to the total number of subcarriers.
Initialize the BER and error statistics arrays.
Simulate the communication link over the range of Eb/No values. For each Eb/No value, the simulation runs until either
maxBitErrors
are recorded or the total number of transmitted bits exceeds maxNumBits
.Use the
berawgn
function to determine the theoretical BER for a QPSK system.Plot the theoretical and simulated data on the same graph to compare results.
Observe that there is good agreement between the simulated and theoretical data.
MIMO-OFDM Precoding with Phased Arrays
This example shows how phased arrays are used in a MIMO-OFDM communication system employing beamforming. Using components from Phased Array System Toolbox™, the example models the radiating elements that comprise a transmitter and the front-end receiver components, for a MIMO-OFDM communication system. With user-specified parameters, the example allows you to validate the performance of the system in terms of bit error rate and constellations for different spatial locations and array sizes.
Mimo Ofdm Matlab Code Pdf Pdf
The example uses functions and System objects™ from Communications Toolbox™ and requires
- Phased Array System Toolbox
- WINNER II Channel Model for Communications Toolbox
Introduction
MIMO-OFDM systems are the norm in current wireless systems (e.g. LTE, WLAN) due to their robustness to frequency-selective channels and high data rates enabled. With ever-increasing demands on data rates supported, these systems are getting more complex and larger in configurations with increasing number of antenna elements, and resources (subcarriers) allocated.
With antenna arrays and spatial multiplexing, efficient techniques to realize the transmissions are necessary [ 6 ]. Beamforming is one such technique, that is employed to improve the signal to noise ratio (SNR) which ultimately improves the system performance, as measured here in terms of bit error rate (BER) [ 1 ].
This example illustrates an asymmetric MIMO-OFDM single-user system where the maximum number of antenna elements on transmit and receive ends can be 1024 and 32 respectively, with up to 16 independent data streams. It models a spatial channel where the array locations and antenna patterns are incorporated into the overall system design. For simplicity, a single point-to-point link (one base station communicating with one mobile user) is modeled. The link uses channel sounding to provide the transmitter with the channel information it needs for beamforming.
The example offers the choice of a few spatially defined channel models, specifically a WINNER II Channel model and a scattering-based model, both of which account for the transmit/receive spatial locations and antenna patterns.
System Parameters
Define system parameters for the example. These parameters can be modified to explore their impact on the system.
Parameters to define the OFDM modulation employed for the system are specified below.
The processing for channel sounding, data transmission and reception modeled in the example are shown in the following block diagrams.
Using utilities from the Phased Array System Toolbox, the free space path loss is calculated based on the base station and mobile station positions for the spatially-aware system modeled.
Channel Sounding
For a spatially multiplexed system, availability of channel information at the transmitter allows for precoding to be applied to maximize the signal energy in the direction and channel of interest. Under the assumption of a slowly varying channel, this is facilitated by sounding the channel first, wherein for a reference transmission, the receiver estimates the channel and feeds this information back to the transmitter.
For the chosen system, a preamble signal is sent over all transmitting elements, and processed at the receiver accounting for the channel. The receiver elements perform pre-amplification, OFDM demodulation, frequency domain channel estimation, and calculation of the feedback weights based on channel diagonalization using singular value decomposition (SVD) per data subcarrier.
For conciseness in presentation, front-end synchronization including carrier and timing recovery are assumed. The weights computed using
diagbfweights
are hence fed back to the transmitter, for subsequent application for the actual data transmission.Data Transmission
Next, we configure the system's data transmitter. This processing includes channel coding, bit mapping to complex symbols, splitting of the individual data stream to multiple transmit streams, precoding of the transmit streams, OFDM modulation with pilot mapping and replication for the transmit antennas employed.
For precoding, the preamble signal is regenerated to enable proper channel estimation. It is prepended to the data portion to form the transmission packet which is then replicated over the transmit antennas.
Transmit Beam Steering
Phased Array System Toolbox offers components appropriate for the design and simulation of phased arrays used in wireless communications systems.
For the spatially aware system, the signal transmitted from the base station is steered towards the direction of the mobile, so as to focus the radiated energy in the desired direction. This is achieved by applying a phase shift to each antenna element to steer the transmission.
The example uses a linear or rectangular array at the transmitter, depending on the number of data streams and number of transmit antennas selected.
The plots indicate the array geometry and the transmit array response in multiple views. The response shows the transmission direction as specified by the steering angle.
The example assumes the steering angle known and close to the mobile angle. In actual systems, this would be estimated from angle-of-arrival estimation at the receiver as a part of the channel sounding or initial beam tracking procedures.
Signal Propagation
Mimo Ofdm Matlab
The example offers three options for spatial MIMO channels and a simpler static-flat MIMO channel for evaluation purposes.
The WINNER II channel model [ 5 ] is a spatially defined MIMO channel that allows you to specify the array geometry and location information. The example uses the typical urban microcell indoor scenario with very low mobile speeds.
The two scattering models use a single-bounce ray tracing approximation where the number of scatterers is user-specified. For this example, the number of scatterers is set to 100. The 'Scattering' option models the scatterers placed randomly within a circle in between the transmitter and receiver, while the 'ScatteringFcn' models their placement completely randomly.
The models allow path loss modeling and both line-of-sight (LOS) and non-LOS propagation conditions. The example assumes non-LOS propagation and isotropic antenna element patterns with linear geometry.
Ofdm Matlab Example
The same channel is used for both sounding and data transmission, with the data transmission having a longer duration controlled by the number of data symbols parameter,
prm.numDataSymbols
.Mimo Ofdm Matlab Code Pdf
Receive Beam Steering
The receiver steers the incident signals to align with the transmit end steering, per receive element. Thermal noise and receiver gain are applied. Uniform linear or rectangular arrays with isotropic responses are modeled to match the channel and transmitter arrays.
The receive antenna pattern mirrors the transmission steering.
Signal Recovery
The receive antenna array passes the propagated signal to the receiver to recover the original information embedded in the signal. Similar to the transmitter, the receiver used in a MIMO-OFDM system contains many stages, including OFDM demodulator, MIMO equalizer, QAM demodulator, and channel decoder.
For the MIMO system modeled, the displayed receive constellation of the equalized symbols offers a qualitative assessment of the reception. The actual bit error rate offers the quantitative figure by comparing the actual transmitted bits with the received decoded bits.
Conclusion and Further Exploration
The example highlighted the use of phased antenna arrays for a beamformed MIMO-OFDM system. It accounted for the spatial geometry and location of the arrays at the base station and mobile station for a single user system. Using channel sounding, the example illustrates how precoding is realized in current wireless systems and how steering of antenna arrays is modeled.
Within the set of configurable parameters, you can vary the number of data streams, transmit/receive antenna elements, station or array locations and geometry, channel models and their configurations to study the parameters' individual or combined effects on the system. As an example, vary just the number of transmit antennas to see the effect on the main lobe of the steered beam and the resulting system performance.
The example also made simplifying assumptions for front-end synchronization, channel feedback, user velocity and path loss models, which need to be further considered for a practical system. Individual systems also have their own procedures which must be folded in to the modeling [ 2, 3, 4 ].
Explore the following helper functions used by the example:
Selected Bibliography
- Perahia, Eldad, and Robert Stacey. Next Generation Wireless LANS: 802.11n and 802.11ac. Cambridge University Press, 2013.
- IEEE® Std 802.11™-2012 IEEE Standard for Information technology - Telecommunications and information exchange between systems - Local and metropolitan area networks - Specific requirements - Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications.
- 3GPP TS 36.213. How to use little snitch to block adobe hosting. 'Physical layer procedures.' 3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA). URL: http://www.3gpp.org.
- 3GPP TS 36.101. 'User Equipment (UE) Radio Transmission and Reception.' 3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA). URL: http://www.3gpp.org.
- Kyosti, Pekka, Juha Meinila, et al. WINNER II Channel Models. D1.1.2, V1.2. IST-4-027756 WINNER II, September 2007.
- George Tsoulos, Ed., 'MIMO System Technology for Wireless Communications', CRC Press, Boca Raton, FL, 2006.