MATLAB Examples

HDL Optimized QPSK Transmitter

This example shows how to optimize the QPSK transmitter modeled in commqpsktxrx.slx for HDL code generation and hardware implementation.

Contents

Introduction

The HDL Optimized QPSK Transmitter example shows how Simulink blocks that support HDL code generation can be used to implement the baseband processing of a digital communications transmitter. The HDLTx subsystem can be cascaded with the HDLRx subsystem given in the HDL Optimized QPSK Receiver Example, in order to form a complete QPSK transmitter-receiver chain from which HDL code can be generated. At the top level of hierarchy, there are two components, HDLTx and Signal Quality Measurement. The HDLTx subsystem has been optimized for HDL code generation by using hardware friendly blocks and design practices. The Signal Quality Measurement subsystem is intended for software based validation of the design and is therefore not supported for HDL code generation. The HDLTx subsystem generates the In-phase (I) and Quadrature (Q) channels representing a QPSK (Quaternary-Phase-Shift-Keying) symbol mapping. This is input as a complex valued vector to the Root Raised Cosine (RRC) transmit pulse shaping filter. The output of the HDLTx subsystem therefore consists of the pulse shaped and upsampled symbols. The Signal Quality Measurement component consists of the matching RRC receive filter and a Constellation Diagram scope. The purpose of the scope is twofold. It both displays the output data, and calculates the Error Vector Magnitude (EVM) and Modulation Error Ratio (MER) values. This allows the designer to investigate the noise introduced into the system from the RRC filter design. This will arise from two sources - (a) the quantization of the coefficient values in the RRC filter and (b) the truncated impulse response of the RRC filter (roll-off factor 0.5). The EVM can therefore be improved by either increasing the number of fractional bits for the coefficient values or by redesigning the RRC filter to give an improved response.

Overview of HDL Optimized QPSK Tx

The HDLTx component is composed of three subsystems -

  • Data Generation & Packetization
  • Symbol Mapping
  • Pulse Shaping

Pipeline registers are inserted between the subsystems in order to minimize the combinatorial path delay between components and therefore maximize the achievable clock frequency (i.e. minimizing the critical path delay). The Data Generation & Packetization subsystem contains several sub-components, which are also pipelined. There is, therefore, a fixed latency before valid data appears at the input to the Pulse Shaping component. To ensure that only valid data is transmitted, valid out and valid in ports are included which are used to control a 2:1 Multiplexer (Input Mux).

The Data Generation & Packetization, Symbol Mapping, and Pulse Shaping subsystems are further described in the following sections.

1 - Data Generation & Packetization

The following figure illustrates the top level hierarchy of the component. The Packetizer FSM and Data Source generate both the preamble and data bits, and perform scrambling and packetization. The packets consist of a 26 bit Barker code preamble and 174 bits of scrambled data. The Barker code preamble is used in the HDL Optimized QPSK Receiver Example for autocorrelation based packet detection via the use of a matched filter. The Bit Pairing subsystem converts the single bit serial data input into a two bit output of half the sampling rate, providing the correct data format for the symbol mapper. Internally, the data source block has a pipeline delay of 2 samples. In addition, there is a pipeline delay between the data source and the bit pairing subsystem. The valid signal is therefore delayed to match the pipeline delay of the data path. The Bit Pairing subsystem reduces the sample rate by a factor of 2. Placing a downsample by two in the valid control path ensures that the sample rate of the valid control path matches that of the signal path.

  • Packetizer FSM - The Packetizer FSM component consists of a Moore machine, created using a MATLAB™ function block. The FSM has two states - Pack_Preamble, and Append_Data. The Pack_Preamble state serves to enable the preamble counter via the load_preamble output. The preamble counter generates the address signal for the preamble Lookup Table (LUT), incrementing from 0 --> 25. Following this, the FSM moves into the Append_Data state, asserting the load_data signal, where it shall remain for 174 cycles. During this time, the reset_preamble output is held high, while the load_preamble output is held low. The FSM shall sequentially switch between the two states in turn.
  • Data Source - As shown in the following figure, the Data Source component contains two LUTs, containing the preamble and data bits. The preamble bits are invariant between packets, and so the counter used to address the preamble LUT is reset after the loading of each preamble. The counter used to address the data LUT is allowed to wrap around after reaching the maximum address value, which corresponds to the final character of the packet body string "Hello World 099". Each of the LUTs is zero padded in order to ensure that the number of data entries is of a power of two length. In addition to enabling the counter for the data LUT, the load data input is used to control when the data scrambler component should be enabled, and to control whether the preamble or data bits should be passed to the output via the 2:1 Preamble Data Mux.
  • Data Scrambler - The data scrambler is detailed in the following figure. The scrambler is built from first principles using XOR gates (for modulo 2 addition) and registers. By using an enabled subsystem, it is ensured that the scrambler is only enabled when there is new input data to be processed.
  • Bit Pairing- The purpose of the Bit Pairing subsystem is to group pairs of bits into an unsigned two bit output - the input format expected by the symbol mapping component. To achieve this, a pair of downsamplers are used to reduce the sample rate by a factor of two, with the first downsampler selecting the second phase and the second downsampler selecting the first phase. The Bit Concat block concatenates the single bit inputs into an unsigned two bit output.

2 - Symbol Mapper

The Symbol Mapper uses the QPSK Modulator Baseband block from the Communications System Toolbox™ in order to map the integer input value [0,1,2,3] onto the appropriate complex valued symbol [1 + 1i, -1 + 1i, 1 - 1i, -1 - 1i]. Mapping the symbols in this manner allows for a 2 bit value to be used to represent each symbol. This allows the wordlengths in the RRC transmit filter for the product and accumulator datapaths to be optimized. The block uses a Gray Mapping scheme.

3 - Pulse Shaping

The Pulse Shaping component uses an FIR Interpolation filter, featuring an upsampling factor of four, and a Root Raised Cosine impulse response. The receive filter in the HDL optimized QPSK Receiver demo forms a matched filter to this transmit filter. The filter is pipelined (see HDL Block Properties) in order to ensure that the combinatorial delay is minimized throughout the design.

Results and Displays

During simulation, the constellation obtained after passing the signal through the transmit and receive filter chain is displayed via the Constellation Diagram Scope (contained within the Signal Quality Measurement component). In addition, the scope displays the calculated EVM and MER via the Tools --> Measurements --> Signal Quality option.

The EVM is the calculated magnitude of the error vector between the ideal constellation point (given by the immediate symbol mapper output) and the constellation point obtained after transmit and receive pulse shape filtering has been performed. The EVM gives a figure of merit regarding the distortion introduced by the transmit and receive filtering. In this case, the EVM allows the system designer to determine if the distortion introduced by the pulse shaping filters due to the effects of fixed point quantization and non-ideal (truncated) impulse responses is acceptable or otherwise. For further information, please refer to the EVM Measurement block documentation.

The MER is a measure of the signal-to-noise ratio in digital modulation applications. It is the ratio of the average reference signal power to the mean square error. For further information, please refer to the MER Measurement block documentation.

Shown below is a snapshot from the Constellation Diagram scope output.

HDL Code Generation

The HDL code generated from the HDLTx subsystem has been synthesized using Xilinx® ISE on a Virtex6 (XC6VLX240T) FPGA, and ran at around 300 MHz. When operating the RRC transmit filter at maximum rate, the QPSK input symbols are generated at 75M symbols/second. The resulting theoretical maximum data rate is therefore 150M samples/second, taking into account the data transmitted over both the I and the Q channels.

You can use the commands makehdl and makehdltb to generate HDL code and testbench for subsystems in HDLTx. To generate the HDL code, use the following command:

   makehdl('commqpsktxhdl/HDLTx')

To generate a testbench, use the following command:

   makehdltb('commqpsktxhdl/HDLTx')

When generating the testbench, a validation model will be created which includes the internal pipeline delay of the RRC transmit filter. The second constellation diagram which is invoked illustrates the output of the validation model.