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Space Division Multiple Access SDMA for Wireless Local Area Network LAN

Fernando Gregorio. Page 2. Outline. IntroductionSpectrally Efficient WLANBandwidth reuse.Pico-cellular WLAN vs. Intra-cell bandwidth reuse.SDMASDMA-OFDMModelReceiver structuresAdvanced Receiver structuresSingle-Carrier SDMAAdvantages over OFDMPractical SDMA systemConclusionsReferences. Fernando Gregorio.

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Space Division Multiple Access SDMA for Wireless Local Area Network LAN

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    1. Space Division Multiple Access (SDMA) for Wireless Local Area Network (LAN) Fernando Gregorio Signal Processing Laboratory HUT

    2. Fernando Gregorio Page 2 Outline Introduction Spectrally Efficient WLAN Bandwidth reuse. Pico-cellular WLAN vs. Intra-cell bandwidth reuse. SDMA SDMA-OFDM Model Receiver structures Advanced Receiver structures Single-Carrier SDMA Advantages over OFDM Practical SDMA system Conclusions References

    3. Fernando Gregorio Page 3 1-Introduction The internet traffic double every 100 days. Digital mobile phones must be cheap, small and power efficient. Laptops has become widely available. Future users will expect universal wireless internet access from their laptops in order to obtain a wide range of services and multimedia contents.

    4. Fernando Gregorio Page 4 2-Spectrally efficient WLAN In the second generation WLAN (IEEE 802.11a) high spectral efficiency can be obtained using high-order constellation size. The implementation of high-order constellation is reduced to good quality channels or small coverage area. Is it possible to increase spectral efficiency? By reusing the bandwidth in adjacent cells (Pico-cellularization) By reusing the bandwidth within one cell by array processing (SDMA)

    5. Fernando Gregorio Page 5 2-Spectrally efficient WLAN Pico-cellular WLAN Each cell is partitioned in multiple smaller cells and to reuse the same frequency bands in some of these smaller cells. Millimeter wave length carrier frequency is needed. Low penetration through obstacles. High path loss.

    6. Fernando Gregorio Page 6 2-Spectrally efficient WLAN Pico-cellular WLAN Disadvantages Cell size vs. network reinstallation cost Cell size vs. cell planning effort Cell size vs. total system capacity Cell size vs. hand-over and routing

    7. Fernando Gregorio Page 7 2-Spectrally efficient WLAN SDMA WLAN In this structure the bandwidth can be reused within each cell. The base station is equipped with an antenna array and with digital signal processing that allows to separate the signals from multiple users sharing the same frequency band and time slot. The users have only a single antenna giving a reduced impact over the system cost. Spatial diversity exploitation is preferred over beamforming because of the strong multipath propagation.

    8. Fernando Gregorio Page 8 2-Spectrally efficient WLAN SDMA WLAN L different users User-specific spatial signature The signal signature generated by the channel over the transmitted signal acts like spreading code in a CDMA system. Multiuser detection techniques known from CDMA can be applied in SDMA-OFDM

    9. Fernando Gregorio Page 9 2-Spectrally efficient WLAN SDMA WLAN vs. Pico-cell

    10. Fernando Gregorio Page 10 3-SDMA-OFDM Model

    11. Fernando Gregorio Page 11 3-SDMA-OFDM Model per-carrier basis

    12. Fernando Gregorio Page 12 4-Receiver structures Multiuser detection Cellular telephony , satellite communication, high-speed data transmission lines, digital TV, fixed wireless local loops are subject to multi-access interference Several transmitters share a common channel. The receiver obtains a superposition of the signals sent by active transmitters. Multiuser detection exploits the considerable structure of the multiuser interference in order to increase the efficiency with which channel resources are employed.

    13. Fernando Gregorio Page 13 4-Receiver structures Linear receivers Different users transmitted signals are estimated with the aid of a linear combiner. The residual interference caused by remaining users is neglected.

    14. Fernando Gregorio Page 14 4-Receiver structures

    15. Fernando Gregorio Page 15 4-Receiver structures Linear Receivers Least Squares: LS Combiner combiner attempts to recover the signals transmitted by the different users regardless of the signal quality quantified in terms of the signal to noise ratio (SNR) at the reception antennas. The linear combiner for user l is designed to fully suppress the contribution of all users other than user l.

    16. Fernando Gregorio Page 16 4-Receiver structures Linear Receivers Minimum Mean Squared Error: Exploits the available statistical knowledge concerning the signals transmitted. MMSE combiner is designed to minimize the expected variance of the error on the combined signal, reducing the noise amplification. Balance between the recovery signals transmitted and the suppression of the AWGN.

    17. Fernando Gregorio Page 17 4-Receiver structures Linear Receivers – Implementation Complexity

    18. Fernando Gregorio Page 18 4-Receiver structures Linear Receivers – Implementation Complexity

    19. Fernando Gregorio Page 19 5-Advanced receiver structures Nonlinear receivers Linear detector assumes that the different users’ associated linear combiner output are corrupted only by AWGN Linear combiner output signal contain residual interference which is not Gaussian distributed. LS and MMSE have sequential structure. The operation of classification can be included into the linear combination process. The residual multi-user interference observed at the classifier’s input is reduced Successive Interference Cancellation (SIC) Parallel Interference Cancellation (PIC)

    20. Fernando Gregorio Page 20 5-Advanced receiver structures Successive Interference Cancellation (SIC) If a decision has been made about an interfering user’s bit, then that interfering signal can be recreated at the receiver and subtracted from the receiver waveform. This will cancel the interfering signal provided that the decision is correct, otherwise it will double the contribution of the interferer. Users with high received power will be demodulated in first order best performance

    21. Fernando Gregorio Page 21 Successive Interference Cancellation (SIC) Only the specific user having the highest SINR (or SIR or SNR) in each iteration at the output of the LS or MMSE combiner is detected. Having detected this user’s signal, the corresponding demodulated signal is subtracted from the composite signal received by the different antenna elements. With this reduced set of received signal a new iteration is executed. 5-Advanced receiver structures

    22. Fernando Gregorio Page 22 Successive Interference Cancellation (SIC) Initialization Detection Calculation of remaining user’s weight matrix Selection of the most dominant user Detection of the most dominant user Demodulation of the most dominant user. Removing of the most important user contribution. New iteration 5-Advanced receiver structures

    23. Fernando Gregorio Page 23 Parallel Interference Cancellation (PIC) The order in which users are canceled affects the performance of SIC receivers. The basic idea of PIC is to estimate the transmitted symbols of each user using a conventional MMSE method in the first stage. In the second stage, the interfering signals can be reproduced and removed from the received signal. Assuming that the symbols had been estimated correctly, a new symbol estimation is carried out using the free of interference signal. This process can be repeated several times to obtain a satisfactory result. 5-Advanced receiver structures

    24. Fernando Gregorio Page 24 Parallel Interference Cancellation (PIC) 5-Advanced receiver structures

    25. Fernando Gregorio Page 25 Parallel Interference Cancellation (PIC) 5-Advanced receiver structures

    26. Fernando Gregorio Page 26 Maximum Likelihood detection Optimum from a statistical point of view. Potentially excessive computational complexity. Join detection of the L different users. McL possible combinations of symbols transmitted by the L different users are considered by evaluating their Euclidean distance from the received signal, upon taking into account the effects of the channel. 5-Advanced receiver structures

    27. Fernando Gregorio Page 27 ML estimation The estimation procedure can be expressed as The estimation of a ML symbol requires comparing the Euclidean distance between the vector x of the received signals by the different antenna elements for all the different vector of symbol combinations. 5-Advanced receiver structures

    28. Fernando Gregorio Page 28 Simulation Results

    29. Fernando Gregorio Page 29 Implementation Complexity

    30. Fernando Gregorio Page 30

    31. Fernando Gregorio Page 31

    32. Fernando Gregorio Page 32 6-Single-Carrier SDMA Multicarrier systems requires a more linear power amplifier and more accurate carrier frequency oscillator than single –carrier systems. Low cost terminals are required in commercial applications. Single-carrier with cyclic prefix (SC-CP)

    33. Fernando Gregorio Page 33 6-Single-Carrier SDMA

    34. Fernando Gregorio Page 34 6-Single-Carrier SDMA Linear multiuser detection receivers can be applied in the same way than OFDM-SDMA. Per-carrier implementation of Non-linear detection can not be implemented. SIC and PIC can be implemented in the time domain. Requires back and forward Fourier transform during each iteration step. High latency. Non-linear detection is not a promising technique for SC-SDMA

    35. Fernando Gregorio Page 35 7-Practical SDMA implementations Real world problems in WLAN implementations Channel estimation Symbol timing Carrier frequency synchronization Power control (imbalance in the received power from different users) Implementation complexity Low cost terminals

    36. Fernando Gregorio Page 36 6-Single-Carrier SDMA An implementation case of study Functional specification

    37. Fernando Gregorio Page 37 6-Single-Carrier SDMA An implementation case of study

    38. Fernando Gregorio Page 38 6-Single-Carrier SDMA An implementation case of study Complexity Results

    39. Fernando Gregorio Page 39 The total area of the SC-SDMA is amounts to 5 mm2 A SDMA-OFDM modem with similar characteristics requires a chip area of 16 mm2

    40. Fernando Gregorio Page 40 8-Conclusions SDMA-OFDM is a good alternative for WLAN systems. SC-SDMA shows interesting properties in order to be considered as a candidate for future WLAN implementations. Nonlinear detection techniques are not suitable for SC-SDMA Multiuser channel estimation and frequency synchronization are open topics to be considered in SDMA-OFDM . Nonlinear detection structures provide diversity gain. Diversity gain vs. Implementation complexity.

    41. Fernando Gregorio Page 41 9-References   1)  Sergio Verdu ,  Multiuser Detection, 1998  2)  L.Hanzo, M. Munster, B.J. Choi, and T.Keller, OFDM and MC-CDMA for broadband Multi-User Communication , WLANs   and Broadcasting, John Wiley Sons, 2003 3) P. Vandenameele, et. al,   ”A combined OFDM-SDMA approach”, IEEE Journal on  Selected Area on Communications , Nov. 2000

    42. Fernando Gregorio Page 42 Homework LS detector reaches similar performance than MMSE in high SNR levels. Explain The order in which users are canceled affects the performance of SIC receivers. Explain

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