New List Sphere Decoding (LSD) and Iterative Synchronization Algorithms for MIMO-OFDM Detection With LDPC FEC (original) (raw)
Related papers
Implementation aspects of list sphere decoder algorithms for MIMO-OFDM systems
Signal Processing, 2010
A list sphere decoder (LSD) can be used to approximate the optimal maximum a posteriori (MAP) detector for the detection of multiple-input multiple-output (MIMO) signals. In this paper, we consider two LSD algorithms with different search methods and study some algorithm design choices which relate to the performance and computational complexity of the algorithm. We show that by limiting the dynamic range of log-likelihood ratio, the required LSD list size can be lowered, and, thus, the complexity of the LSD algorithm is decreased. We compare the real and the complexvalued signal models and their impact on the complexity of the algorithms. We show that the real-valued signal model is clearly the less complex choice and a better alternative for implementation. We also show the complexity of the sequential search LSD algorithm can be reduced by limiting the maximum number of checked nodes without sacrificing the performance of the system. Finally, we study the complexity and performance of an iterative receiver, analyze the tradeoff choices between complexity and performance, and show that the additional computational cost in LSD is justified to get better soft-output approximation.
2015
Recently, iterative processing has been widely considered to achieve near-capacity performance and reliable high data rate transmission, for future wireless communication systems. However, such an iterative processing poses significant challenges for efficient receiver design. In this thesis, iterative receiver combining multiple-input multiple-output (MIMO) detection with channel decoding is investigated for high data rate transmission. The convergence, the performance and the computational complexity of the iterative receiver for MIMO-OFDM system are considered. First, we review the most relevant hard-output and soft-output MIMO detection algorithms based on sphere decoding, K-Best decoding, and interference cancellation. Consequently, a low-complexity K-best (LCK- Best) based decoder is proposed in order to substantially reduce the computational complexity without significant performance degradation. We then analyze the convergence behaviors of combining these detection algorithm...
Comparison of Three List Detectors in Iterative Decoding and Channel Estimation in MIMO OFDM
Spread Spectrum Techniques and Applications, 2008
In this paper, the complexity and the performance of the list parallel interference cancellation (PIC) detection algorithm is compared to the ones of the K-best list sphere detector (LSD) and the increasing radius (IR)-LSD in a multipleinput multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. The detectors are used as a soft MIMO detector to approximate the a posteriori probability (APP) algorithm in an iterative receiver to jointly decode the transmitted bits and to estimate the channel state. According to the results, the list PIC algorithm with a proper initialization gives some performance gain over the K-best LSD and loses only slightly to the IR-LSD. The IR-LSD is found to be the least complex of the algorithms when the number of visited nodes is measured.
Design of Mimo–Ofdm Using Fixed Sphere Decoding Detection Method
Designing MIMO-OFDM using fixed sphere decoding detection method is implemented. The design includes OFDM-Transmitter and receiver sending 4 signals from transmitter to receiver with fixed sphere decoding detection method. In this paper OFDM-Transmitter process is implemented using xilinix software. In transmitter process, includes 16 QAM,IFFT . Four signals with 16 sample values are send for transmitter . In IFFT radix 4 _16 point is used, it reduces computational complexity. In the proposed system fixed sphere decoding detection method is used in receiver section ,we can achieve a fast detection approach for OFDM receiver-will detect the received signals quickly.FSD advantages is that no of visited nodes will be same for Hard and Soft output hence they have same throughput.
An Optimized-Hierarchy-Aided Maximum Likelihood Detector for MIMO-OFDM
2006 IEEE 63rd Vehicular Technology Conference, 2006
In this paper we propose a novel low-complexity Maximum Likelihood (ML) space-time detection method, which can be regarded as an advanced extension of the Complex Sphere Decoder (CSD). We demonstrate that as opposed to the previously published variants of the CSD, the proposed technique may be employed in the so-called "over-loaded" scenario, where the number of transmit antennas exceeds that of the receive antennas. The proposed method achieves the optimum performance of the ML detector even in heavily overloaded scenarios, while the associated computational complexity is only moderately increased.
OFDM symbol detection over time varying channels by using sphere decoding
2012
While being a major broadband wireless access technology, OFDM transmission over fast fading channels poses a significant challenge. Time variations in an OFDM channel destroy the subcarriers orthogonality and complicate the problem of symbol detection. This paper considers a Sphere Decoding (SD) algorithm for OFDM over such channels. This SD algorithm is designed for banded channel matrices to reduce complexity. Then this algorithm is used for OFDM symbol detection over doubly selective wireless channels. Computer simulations results show that performance gains can be achieved over such time varying wireless channels with this OFDM detection technique. Furthermore complexity analysis results show that such an algorithm could be attractive for practical applications.
Practical performance of MIMO-OFDM-LDPC with low complexity double iterative receiver
2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications, 2009
This paper considers MIMO-OFDM transmission with low density parity check (LDPC) codes. We employ a low complexity minimum mean-square-error (MMSE) softinterference-cancelation (SIC) based double iterative receiver (DIR). Results are presented for a real system implementation at 5.2 GHz. We achieve zero packet errors at 90% of the measured indoor locations, when transmitting at 600 Mbit/s, with 15 bit/s/Hz spectral efficiency and 26 dB signal-to-noise ratio. We show that the proposed receiver actually outperforms a list sphere detection (LSD) based single iterative receiver (SIR) at high coding rates, in practice. Investigations reveal that the LSD-SIR is adversely affected by the non-Gaussian noise present at the receiver, while at the same time the MMSE-SIC-DIR is better able to handle transmitter noise present in the practical system.
IEEE Journal on Selected Areas in Communications, 2000
Iterative soft detection and channel decoding for MIMO OFDM downlink receivers is studied in this work. Proposed inner soft sphere detection employs a variable upper bound for number of candidates per transmit antenna and utilizes the breath-first candidate-search algorithm. Upper bounds are based on probability distribution of the number of candidates found inside the spherical region formed around the received symbolvector. Detection accuracy of unbounded breadth-first candidatesearch is preserved while significant reduction of the search latency and area cost is achieved. This probabilistically bounded candidate-search algorithm improves error-rate performance of non-probabilistically bounded soft sphere detection algorithms, while providing smaller detection latency with same hardware resources. Prototype architecture of soft sphere detector is synthesized on Xilinx FPGA and for an ASIC design. Using area-cost of a single soft sphere detector, a level of processing parallelism required to achieve targeted high data rates for future wireless systems (for example, 1 Gbps data rate) is determined.
Adaptive radius sphere detection in MIMO OFDM systems
Digital communications of sensing symbol vectors has found abundant diverse uses. These symbols are determinate alphabet conducted over a multiple-input multiple-output (MIMO) channel having Gaussian noise. Proficient algorithms are reflected in exposure eg. Latches and have recognized well. The sphere decoder algorithm has optimal performance with reduced complexity. At high SNR the algorithm has a polynomial average complexity and is worst case complexity. The proficiency of the algorithm is the exponential rate cradle of growth. Complexity is affirmative for the numerous SNR and is small in the high SNR. To attain the sphere decoding solution, Schnorr-Euchner is applied through Maximum likelihood method, Depth-first Stack-based Sequential decoding. Thus this paper is focus on the receiver part of the transceiver system and provides a good look of optimal algorithm by vector symbol transmitted through MIMO channel.