FPGA Implementation of Mimo E-SDM for future communications wireless networks •

Multiple-input multiple-output (MIMO) systems applying the Eigenbeam-Space Division Multiplexing (E-SDM) technique can be considered as optimal MIMO systems because of providing the highest channel capacity and good communications reliability. In the systems, orthogonal transmission beams are formed between transmit and receive sides; and also optimal transmit input data are adaptively allocated. In addition, a simple detection can be used at receiver to totally eliminate sub-stream interference. Therefore, MIMO E-SDM systems have been considered as a good potential technology for future high speed data transmission networks. Although there have been a lot of technical papers evaluated the systems based on theory analyses and/or computer-based simulation, just few ones have been considered the MIMO E-SDM systems based on hardware design. The main contribution of this paper is to present our own design and implementation of 2x2 and 2x3 MIMO E-SDM systems on FPGA Altera Stratix DSP Development KIT using Verilog HDL, an important step before going to make integrated circuits. The biterror rate performance the consumption for our design of these systems have shown that our design is successful.

FPGA Implementation of Mimo E-SDM for future communications wireless networks

ABSTRACT:
Multiple-input multiple-output (MIMO) systems applying the Eigenbeam-Space Division Multiplexing (E-SDM) technique can be considered as optimal MIMO systems because of providing the highest channel capacity and good communications reliability.In the systems, orthogonal transmission beams are formed between transmit and receive sides; and also optimal transmit input data are adaptively allocated.In addition, a simple detection can be used at receiver to totally eliminate sub-stream interference.Therefore, MIMO E-SDM systems have been considered as a good potential technology for future high speed data transmission networks.Although there have been a lot of technical papers evaluated the systems based on theory analyses and/or computer-based simulation, just few ones have been considered the MIMO E-SDM systems based on hardware design.The main contribution of this paper is to present our own design and implementation of 2x2 and The main contribution of the paper is to present our own detailed design and implementation of the MIMO E-SDM systems on FPGA Altera Stratix DSP Development KIT using Verilog HDL.We use HDL description in the whole system because we want an executable functional specification.
Besides, the executable models can be tested and refined during implementation process.In addition, HDL description is the first step to build an implementation directly from a behavioral model in an automated process.Based on the design, we evaluate bit-error rate (BER) of the systems and also compare the consumption of FPGA elements for our design of the systems.A part of the paper has been presented in [14].The paper is organized as follows.In the next section, an overview of MIMO E-SDM systems is presented.In section III, we will show our design and hardware implementation of the MIMO E-SDM system.The results and discussion of our implementations are shown in section IV.Finally, conclusions are drawn in Section V. ,

OVERVIEW OF MIMO E-SDM SYSTEMS
At the TX side, an input stream is divided where U is obtained by the eigenvalue decomposition as

DESIGN AND IMPLEMENTATION OF MIMO E-SDM SYSTEMS
The block diagram of our design and implementation of a 2x2 MIMO E-SDM system on FPGA hardware is shown in Fig. 2. For the case of 2x3 system, it will be designed and implemented similarly.

IMPLEMENTED RESULTS AND DISCUSSION
Based on the design and implementation of the MIMO E-SDM systems, in the section, we will evaluate the bit-error rate (BER) of the systems, and compare it with simulation results in Matlab.
In the section, we also consider about the hardware consumptions for our system design.

BER performance of designed systems
The

Hardware Cost
In the section, we want to evaluate hardware consumption in our system design and compare it between MIMO E-SDM and MIMO SDM systems.
Table 1 shows the detail hardware consumption of the design of 2x2 MIMO E-SDM system with channel coding.The FPGA device used is Stratix III 3SL150F1152C2.It can be seen from Table 1 that hardware resource can be free approximately 30%.Maximum speed of the system is 145.37 MHz.
The detail hardware consumption of 2x3 MIMO E-SDM system is shown in
multiple-out (MIMO) systems have been considered as a high speed data transmission technology.The channel capacity of the systems can increase significantly and is proportionally to the number of transmit (TX) and receive (RX) antennas without additional power and bandwidth compared with single-input singleout systems.The systems have been standardized to be used in modern networks such as IEEE 802.11, 3GPP Long Term Evolution, and WiMAX [1-3].When channel state information (CSI) is not available at transmitter, spatial division multiplexing (SDM) technique is used for data transmission.In the technique, data resources, power level and modulation scheme, are allocated equally to all transmit sub-streams [4-6].However, when CSI is available, an eigenbeamspace division multiplexing (E-SDM) is used [7-Trang 80 9].The MIMO E-SDM systems are also called singular value decomposition MIMO (SVD MIMO) systems [10] or MIMO eigenmode transmission systems [11].In E-SDM techniques, an orthogonal beamforming is formed based on the eigenvectors obtained from eigenvalue decomposition using a MIMO channel matrix.To increase quality of the systems, the E-SDM technique has an innovation in transmitting.A new feature of this algorithm is the calculation of the bit error probability of each flow with many cases of demodulation.In the systems, a simple receive weight method can demultiplex received signals without intersubstream interference, and maximum channel capacity is obtained.These advantages make the MIMO E-SDM technology a promising candidate for future high-rate wireless applications.There have been a lot of technical papers studied and evaluated about the MIMO E-SDM systems based on theory analyses and/or computer-based simulation [7-11].However, just few ones have considered the systems based on hardware implementation [12,13].
Moreover, we have also extended our study of single carrier MIMO E-SDM systems (presented in the paper) to multi-carrier MIMO E-SDM systems [15].In the multi-carrier systems, Othogonal Frequency Division Multiplexing (OFDM) technique is used to improve frequency efficiency and eliminate inter-symbol interference.

Fig. 1 .
Fig. 1.Block diagram of MIMO E-SDM system Consider a MIMO E-SDM system with NTX antennas at TX and NRX antennas at RX, as shown in Fig. 1.When MIMO CSI is available at the TX, orthogonal transmit eigenbeams can be formed between the TX and the RX.Eigenbeams are obtained from eigenvalue decomposition of into K substreams (K ≤ min(NRX, NTX)).Then, signals before transmission are driven by a transmit weight matrix WTX to form orthogonal transmit beams and control power allocation.At the RX side, received signals are detected by a receive weight matrix WRX.The optimal WTX and WRX are determined according to [7, 8] as ...≥ λK>0 are positive eigenvalues of H H H. The columns of U are the eigenvectors corresponding to those positive eigenvalues, and 12

Fig. 2 .
Fig. 2. Design of a 2x2 MIMO E-SDM system 3.1.Transmitter side In the TX side, we need to estimate CSI matrix H fedback from the RX, and then determine the eigenvalue and eigenvector.Based on these values, transmit data resources and power allocation are calculated.The TX also consists of other modules such as data generator, digital modulations, adding sending choice, adding training symbols, normalizing and transmitting, as shown in Fig. 3.

Fig. 3 .
Fig. 3. Transmitter block diagram The Modulation module shown in Fig.4 uses 4QAM or 16QAM modulation which depends on the input 'choice'.It will be one block 16QAM if the value of 'choice' is zero, and be two blocks 4QAM if the value is one.

Fig. 4 .
Fig. 4. Modulation module Each of the signals Out1 and Out2 includes two parts: in-phase (I) and Quadrature (Q) components and is stored in a Look-up table (LUT).Supposing CSI matrix H is already known, we calculate matrix H H H and then determine eigenvalues and eigenvectors of the matrix, as shown in Fig. 5.In this module, we use fix-point 10.22 to do all the calculations.Obtained eigenvalues will be converted to single floatingpoint by module fixed-point to floating-point.

Fig 7 .
Fig 7. Sending choice and training symbol module

Fig. 9 .
Fig. 9. Equalization module At Fig.10, we can see the receiving choice module.After decoding, the first data symbol which is modulated with BPSK method contains exactly the choice value we need.So that the receiving choice module will start to demodulate this symbol and get the choice back.

Fig. 10 .
Fig. 10.Getting choice and demodulating module After getting the choice value, based on it, received signals will be demodulated correctly and get transmitted data.