Heterogeneous pipelined square-root Kalman Filter algorithm for the MMSE-OSIC problem

The final publication is available at Springer via http://dx.doi.org/10.1007/s11227-009-0354-x[EN] This paper describes a pipelined parallel algorithm for the MMSE-OSIC decoding procedure proposed in V-BLAST wireless MIMO systems, for heterogeneous networks of processors. It is based on a block version of the square-root Kalman Filter algorithm that was initially devised to solve the RLS problem. It has been parallelized in a pipelined way obtaining a good efficiency and scalability. The optimum load balancing for this parallel algorithm is dynamic, but we derive a static load balancing scheme with good performance. © 2009 Springer Science+Business Media, LLC.This work has been supported by the Generalitat Valenciana, project 20080811, by the Universidad Politecnica de Valencia, project 20080009, by the Conserjería de Educacion de la Región de Murcia (Fundacion Séneca, 08763/PI/08), and by the Ministerio de Ciencia e Innovacion (TIN2008-06570-C04-02).Martínez Zaldívar, FJ.; Vidal Maciá, AM.; Giménez Cánovas, D. (2011). Heterogeneous pipelined square-root Kalman Filter algorithm for the MMSE-OSIC problem. Journal of Supercomputing. 58(2):235-243. https://doi.org/10.1007/s11227-009-0354-xS235243582Foschini GJ (1996) Layered space-time architecture for wireless communications in a fading environment when using multiple antennas. Bell Labs Techn J 1:41–59Hassibi B (2000) An efficient square-root algorithm for BLAST. In: IEEE international conference on acoustics, speech and signal processing 2000, vol 2, pp II737–II740Zhu H, Lei Z, Chin FPS (2004) An improved square-root algorithm for BLAST. IEEE Signal Process Lett 11(9)Choi Y-S, Voltz PJ, Cassara FA (2001) On channel estimation and detection for multicarrier signals in fast and selective Rayleigh fading channels. IEEE Trans Commun 49(8)Burg A, Haene S, Perels D, Luethi P, Felber N, Fichtner W (2006) Algorithm and VLSI architecture for linear MMSE detection in MIMO-OFDM systems. In: Proceedings of the IEEE int symp on circuits and systems, May 2006Martínez Zaldívar FJ (2007) Algoritmos paralelos segmentados para los problemas de Mínimos Cuadrados Recursivos (RLS) y de Detección por Cancelación Ordenada y Sucesiva de Interferencia (OSIC). PhD thesis, Facultad de Informática, Universidad Politécnica de Valencia, SpainSayed AH, Kailath T (1994) A state-space approach to adaptive RLS filtering. IEEE Signal Process Mag 11(3):18–60Kumar V, Gram A, Gupta A, Karypis G (2003) An introduction to parallel computing: design and analysis of algorithms, Chap 4, 2nd edn. Addison-Wesley, Harlow

A Robust QR based detector for V Blast and its efficient hardware implementation

The use of multiple antennas at both transmitting and receiving sides of a communication channel has increased the spectral efficiency to near the Shannon bound. However algorithmic complexity in the realization of the receiver is a major problem for its hardware implementation. In this paper we investigate a near optimal algorithm for V-BLAST detection in MIMO wireless communication systems based on QR factorization, offering remarkable reduction in the hardware complexity. Specifically, we analyze some hardware implementation aspects of the selected algorithm through MATLAB simulations and demonstrate its robustness. This technique can be used in an efficient fixed point VLSI implementation of the algorith

Efficient Algorithmic and Architectural Optimization of QR-based Detector for V-BLAST

The use of multiple antennas at both transmitting and receiving sides of a rich scattering communication channel improves the spectral efficiency and capacity of digital transmission systems compared with the single antenna communication systems. However algorithmic complexity in the realization of the receiver is a major problem for its implementation in hardware. This paper investigates a near optimal algorithm for V-BLAST detection in MIMO wireless communication systems based on the QR factorization technique, offering remarkable reduction in the hardware complexity. Specifically, we analyze some hardware implementation aspects of the selected algorithm through MATLAB simulations and demonstrate its robustness. This technique can be used in an efficient fixed point VLSI implementation of the algorithm. We also provide the VLSI architecture that implements the algorithm

Generalized feedback detection for spatial multiplexing multi-antenna systems

We present a unified detection framework for spatial multiplexing multiple-input multiple-output (MIMO) systems by generalizing Heller’s classical feedback decoding algorithm for convolutional codes. The resulting generalized feedback detector (GFD) is characterized by three parameters: window size, step size and branch factor. Many existing MIMO detectors are turned out to be special cases of the GFD. Moreover, different parameter choices can provide various performance-complexity tradeoffs. The connection between MIMO detectors and tree search algorithms is also established. To reduce redundant computations in the GFD, a shared computation technique is proposed by using a tree data structure. Using a union bound based analysis of the symbol error rates, the diversity order and signal-to-noise ratio (SNR) gain are derived analytically as functions of the three parameters; for example, the diversity order of the GFD varies between 1 and N. The complexity of the GFD varies between those of the maximum-likelihood (ML) detector and the zero-forcing decision feedback detector (ZFDFD). Extensive computer simulation results are also provided

MIMO Detection for High-Order QAM Based on a Gaussian Tree Approximation

This paper proposes a new detection algorithm for MIMO communication systems employing high order QAM constellations. The factor graph that corresponds to this problem is very loopy; in fact, it is a complete graph. Hence, a straightforward application of the Belief Propagation (BP) algorithm yields very poor results. Our algorithm is based on an optimal tree approximation of the Gaussian density of the unconstrained linear system. The finite-set constraint is then applied to obtain a loop-free discrete distribution. It is shown that even though the approximation is not directly applied to the exact discrete distribution, applying the BP algorithm to the loop-free factor graph outperforms current methods in terms of both performance and complexity. The improved performance of the proposed algorithm is demonstrated on the problem of MIMO detection

An Iterative Soft Decision Based LR-Aided MIMO Detector

The demand for wireless and high-rate communication system is increasing gradually and multiple-input-multiple-output (MIMO) is one of the feasible solutions to accommodate the growing demand for its spatial multiplexing and diversity gain. However, with high number of antennas, the computational and hardware complexity of MIMO increases exponentially. This accumulating complexity is a paramount problem in MIMO detection system directly leading to large power consumption. Hence, the major focus of this dissertation is algorithmic and hardware development of MIMO decoder with reduced complexity for both real and complex domain, which can be a beneficial solution with power efficiency and high throughput. Both hard and soft domain MIMO detectors are considered. The use of lattice reduction (LR) algorithm and on-demand-child-expansion for the reduction of noise propagation and node calculation respectively are the two of the key features of our developed architecture, presented in this literature. The real domain iterative soft MIMO decoding algorithm, simulated for 4 × 4 MIMO with different modulation scheme, achieves 1.1 to 2.7 dB improvement over Lease Sphere Decoder (LSD) and more than 8x reduction in list size, K as well as complexity of the detector. Next, the iterative real domain K-Best decoder is expanded to the complex domain with new detection scheme. It attains 6.9 to 8.0 dB improvement over real domain K-Best decoder and 1.4 to 2.5 dB better performance over conventional complex decoder for 8 × 8 MIMO with 64 QAM modulation scheme. Besides K, a new adjustable parameter, Rlimit has been introduced in order to append re-configurability trading-off between complexity and performance. After that, a novel low-power hardware architecture of complex decoder is developed for 8 × 8 MIMO and 64 QAM modulation scheme. The total word length of only 16 bits has been adopted limiting the bit error rate (BER) degradation to 0.3 dB with K and Rlimit equal to 4. The proposed VLSI architecture is modeled in Verilog HDL using Xilinx and synthesized using Synopsys Design Vision in 45 nm CMOS technology. According to the synthesize result, it achieves 1090.8 Mbps throughput with power consumption of 580 mW and latency of 0.33 us. The maximum frequency the design proposed is 181.8 MHz. All of the proposed decoders mentioned above are bounded by the fixed K. Hence, an adaptive real domain K-Best decoder is further developed to achieve the similar performance with less K, thereby reducing the computational complexity of the decoder. It does not require accurate SNR measurement to perform the initial estimation of list size, K. Instead, the difference between the first two minimal distances is considered, which inherently eliminates complexity. In summary, a novel iterative K-Best detector for both real and complex domain with efficient VLSI design is proposed in this dissertation. The results from extensive simulation and VHDL with analysis using Synopsys tool are also presented for justification and validation of the proposed works

An Iterative Soft Decision Based LR-Aided MIMO Detector

The demand for wireless and high-rate communication system is increasing gradually and multiple-input-multiple-output (MIMO) is one of the feasible solutions to accommodate the growing demand for its spatial multiplexing and diversity gain. However, with high number of antennas, the computational and hardware complexity of MIMO increases exponentially. This accumulating complexity is a paramount problem in MIMO detection system directly leading to large power consumption. Hence, the major focus of this dissertation is algorithmic and hardware development of MIMO decoder with reduced complexity for both real and complex domain, which can be a beneficial solution with power efficiency and high throughput. Both hard and soft domain MIMO detectors are considered. The use of lattice reduction (LR) algorithm and on-demand-child-expansion for the reduction of noise propagation and node calculation respectively are the two of the key features of our developed architecture, presented in this literature. The real domain iterative soft MIMO decoding algorithm, simulated for 4 × 4 MIMO with different modulation scheme, achieves 1.1 to 2.7 dB improvement over Lease Sphere Decoder (LSD) and more than 8x reduction in list size, K as well as complexity of the detector. Next, the iterative real domain K-Best decoder is expanded to the complex domain with new detection scheme. It attains 6.9 to 8.0 dB improvement over real domain K-Best decoder and 1.4 to 2.5 dB better performance over conventional complex decoder for 8 × 8 MIMO with 64 QAM modulation scheme. Besides K, a new adjustable parameter, Rlimit has been introduced in order to append re-configurability trading-off between complexity and performance. After that, a novel low-power hardware architecture of complex decoder is developed for 8 × 8 MIMO and 64 QAM modulation scheme. The total word length of only 16 bits has been adopted limiting the bit error rate (BER) degradation to 0.3 dB with K and Rlimit equal to 4. The proposed VLSI architecture is modeled in Verilog HDL using Xilinx and synthesized using Synopsys Design Vision in 45 nm CMOS technology. According to the synthesize result, it achieves 1090.8 Mbps throughput with power consumption of 580 mW and latency of 0.33 us. The maximum frequency the design proposed is 181.8 MHz. All of the proposed decoders mentioned above are bounded by the fixed K. Hence, an adaptive real domain K-Best decoder is further developed to achieve the similar performance with less K, thereby reducing the computational complexity of the decoder. It does not require accurate SNR measurement to perform the initial estimation of list size, K. Instead, the difference between the first two minimal distances is considered, which inherently eliminates complexity. In summary, a novel iterative K-Best detector for both real and complex domain with efficient VLSI design is proposed in this dissertation. The results from extensive simulation and VHDL with analysis using Synopsys tool are also presented for justification and validation of the proposed works

Signal detection for 3GPP LTE downlink: algorithm and implementation.

In this paper, we investigate an efficient signal detection algorithm, which combines lattice reduction (LR) and list decoding (LD) techniques for the 3rd generation long term evolution (LTE) downlink systems. The resulting detector, called LRLD based detector, is carried out within the framework of successive interference cancellation (SIC), which takes full advantages of the reliable LR detection. We then extend our studies to the implementation possibility of the LRLD based detector and provide reference for the possible real silicon implementation. Simulation results show that the proposed detector provides a near maximum likelihood (ML) performance with a significantly reduced complexity