Laura Luzzi, Ghaya Rekaya-Ben Othman, Jean‐Claude Belfiore · 2010
Lattice reduction algorithms, such as the LLL algorithm, have been proposed as preprocessing tools in order to enhance the performance of suboptimal receivers in MIMO communications. In this paper we introduce a new kind of lattice reduction-aided decoding technique, called augmented lattice reduction, which recovers the transmitted vector directly from the change of basis matrix, and therefore doesn't entail the computation of the pseudo-inverse of the channel matrix or its QR decomposition. We prove that augmented lattice reduction attains the maximum receive diversity order of the channel; simulation results evidence that it significantly outperforms LLL-SIC detection without entailing any additional complexity.
Cited by 3
Luay Azzam, et al. · 2009
In this paper, we discuss three applications of the QR decomposition algorithm to decoding in a number of Multi-Input Multi-Output (MIMO) systems. In the first application, we propose a new structure for MIMO Sphere Decoding (SD). We show that the new approach achieves 80 % reduction in the overall complexity compared to conventional SD for a 2 × 2 system, and almost 50 % reduction for the 4 × 4 and 6 × 6 cases. In the second application, we propose a low complexity Maximum Likelihood Decoding (MLD) algorithm for quasiorthogonal space-time block codes (QOSTBCs). We show that for N = 8 transmit antennas and 16-QAM modulation scheme, the new approach achieves> 97 % reduction in the overall complexity compared to conventional MLD, and> 89 % reduction compared to the most competitive reported algorithms in the literature. This complexity gain becomes greater when the number of transmit antennas (N) or the constellation size (L) becomes larger. In the third application, we propose a low complexity Maximum Likelihood Decoding (MLD) algorithm for orthogonal spacetime block codes (OSTBCs) based on the real-valued lattice representation and QR decomposition. For a system employing the well-known Alamouti OSTBC and 16-QAM modulation scheme, the new approach achieves> 87 % reduction in the overall complexity compared to conventional MLD. Moreover, we show that for square L-QAM constellations, the proposed algorithm reduces the decoding computational complexity from O(L N/2) for conventional MLD to O(L) for systems employing QOSTBCs and from O(L) for conventional MLD to O (√L) for those employing OSTBCs without sacrificing the performance.
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Ender Ayanoğlu, Luay Azzam · 2008
In this dissertation, the problem of decoding complexity for sphere decoding, quasi-orthogonal space-time block codes, and orthogonal space-time block codes is considered. First, the thesis investigates the complexity reduction of sphere decoding by reducing the number of computational operations required by the receiver to retrieve the transmitted signal. We show that this reduction in the complexity is made possible by a simple reordering of the real-valued representation of the channel matrix. Making use of the new structure; decoding the real and imaginary parts of each jointly detected symbol can be performed independently and in parallel. A significant complexity gain is achieved while providing the optimal performance.
Next, we look at sphere decoding from an implementation perspective. We propose a proper tree search traversal technique that reduces the overall SD computational complexity. We exploit the similarity among the complex symbols in a square QAM lattice representation and rewrite the squared norm ML metric in a simpler form allowing significant reduction of the number of operations required to decode the transmitted symbols. We also show that this approach achieves > 45% complexity gain for systems employing 4-QAM, and that this gain becomes bigger as the constellation size gets larger.
Then, the thesis focuses on the decoding complexity of quasi-orthogonal space-time block codes and orthogonal space-time block codes. We propose a reduced-complexity Maximum Likelihood detection algorithm based on the real-valued lattice representation of the channel and QR decomposition. We show that for square L-QAM constellations and N transmit antennas, the proposed algorithm reduces the decoding computational complexity from O(LN /2) for conventional ML to O(L) for systems employing QOSTBCs and from O(L) for conventional ML to O( L ) for those employing OSTBCs without sacrificing the performance.
We also show that for QOSTBC systems with rate r = ns/T, where ns is the number of transmitted symbols per T time slots;, the proposed algorithm decomposes the original complex-valued system into a parallel system represented by ns 2 × 2 real-valued components, thus allowing for a simple joint decoding of two real symbols. For OSTBC systems, the channel, as seen by the real and imaginary parts of every transmitted complex symbol, is 1 × 1 real-valued simple channel. This makes the detection of the real and imaginary parts be carried out simply and independently.
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Rare & Special e-Zone (The Hong Kong University of Science and Technology) · 2002
Efficient complexity reduction methods for short-frame iterative decoding by Kei Chun-Ling thesis 2002 xiii, 91 leaves : ill. ; 30 cm Turbo coding has already become a prominent error correction technique for wireless communications, especially after its adaptation in the…Read more ›
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Loskot, Pavel · Cronfa (Swansea University) · 2012
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Loskot Pavel · Cronfa (Swansea University) · 2012
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Katsutoshi Kusume · 2008
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Chun-Ling Kei · 2002
Efficient complexity reduction methods for short-frame iterative decoding by Kei Chun-Ling thesis 2002 xiii, 91 leaves : ill. ; 30 cm Turbo coding has already become a prominent error correction technique for wireless communications, especially after its adaptation in the…Read more ›
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Salim Haddad, Oscar Sanchez, Amer Baghdadi et al. · 2012
High throughput and complexity reduction remain major requirements of future wireless communication system implementations. On the Other hand, iterative processing is being widely investigated and proposed nowadays to cope with the increasing transmission quality requirement. Howerver, these advanced techniques pose a real challenge in terms of achieving high throughput and reduced complexity implementations. A typical example in this domain is the significant performance improvement offered by the use of iterative demodulation with turbo decoding in severe channel conditions. For this iterative system, and targeting a highly parallel architecture for high throughput feature, we analyze the impact of computation scheduling on the complexity. We demonstrate that the adoption of advanced shuffled scheduling can lead to significant complexity reduction. Simulations show that applying the Butterfly-Replica schedule in the turbo decoder reduces the overall number of iterations by at least one iteration in the waterfall region with respect to the Butterfly schedule. This gain in number of iterations comes without any overhead in terms of area and without any lose is communication performance. Howerver, it results in a throughput improvement around 33% and a complexity reduction up to 22% in arithmetic operations, 14.6% in read access memory, and −39.3% in write access memory for the considered configurations.
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Haotian Zheng, Bin Chen, Luis F. Abanto‐Leon et al. · arXiv (Cornell University) · 2019
This paper proposes an enhanced list-aided successive cancellation stack (ELSCS) decoding algorithm with adjustable decoding complexity. In addition, a logarithmic likelihood ratio (LLR)-threshold based path extension scheme is designed to further reduce the memory consumption of stack decoding. Numerical simulation results show that without affecting the error correction performance, the proposed ELSCS decoding algorithm provides a flexible tradeoff between time complexity and computational complexity, while reducing storage space up to $70\%$. Based on the fact that most mobile devices operate in environments with stringent energy budget to support diverse applications, the proposed scheme is a promising candidate for meeting requirements of different applications while maintaining a low computational complexity and computing resource utilization.
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Haotian Zheng, Bin Chen, Luis F. Abanto‐Leon et al. · IET Communications · 2019
This study proposes an enhanced list‐aided successive cancellation stack (ELSCS) decoding algorithm with adjustable decoding complexity. Also, a logarithmic likelihood ratio‐threshold based path extension scheme is designed to further reduce the memory consumption of stack decoding. Numerical simulation results show that without affecting the error correction performance, the proposed ELSCS decoding algorithm provides a flexible trade‐off between time complexity and computational complexity, while reducing storage space up to 70%. Based on the fact that most mobile devices operate in environments with stringent energy budget to support diverse applications, the proposed scheme is a promising candidate for meeting requirements of different applications while maintaining a low computational complexity and computing resource utilisation.
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Erwan Raffin, Erwan Nogues, Maxime Pelcat et al. · HAL (Le Centre pour la Communication Scientifique Directe) · 2015
Contribution to MPEG 111th meeting for GreenMetadata ad hoc group
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IEEE Transactions on Communications · 2005
Multistage Iterative Decoding With Complexity Reduction for Concatenated Space–Time Codes Space–time encoders exploiting concatenated coding structures are efficient in attaining the high rates available to large-dimensional multiple-transmitter, multiple-receiver wireless systems under fading conditions, while also providing maximal diversity benefits. We present a multistage iterative decoding structure that takes full advantage of the concatenated nature of the transmission path, treating the modulator and channel stages as an additional encoder in serial concatenation. This iterative decoder architecture allows an encoder employing decoupled coding and modulation to reach the performance of coded modulation systems. It also admits reduced-complexity decoding with a computational load that is nonexponential in the number of antennas or the transmission bit rate, and makes practical decoding for large transmitter arrays possible. The performance curves for these methods follow the shape of the Fano bound, with only a modest power penalty.
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V. Ahirwar, B. Sundar Rajan · 2005
It is known that in an OFDM system using Hadamard transform or phase alteration before the IDFT operation can reduce the peak-to-average power ratio (PAPR). Both these techniques can be viewed as constellation preceding for PAPR reduction. In general, using non-diagonal transforms, like Hadamard transform, increases the ML decoding complexity. In this paper we propose the use of block-IDFT matrices and show that appropriate block-IDFT matrices give lower PAPR as well as lower decoding complexity compared to using Hadamard transform. Moreover, we present a detailed study of the tradeoff between PAPR reduction and the ML decoding complexity when using block-IDFT matrices with various sizes of the blocks
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Jiongyue Xing, Li Chen, Martin Bossert · 2020
This paper proposes the low-complexity Chase (LCC) decoding using basis reduction (BR) interpolation for Reed-Solomon (RS) codes, namely the LCC-BR algorithm. With received soft information, a number of decoding test-vectors are formulated. The LCC-BR algorithm first constructs a common basis which will be utilized by the following individual basis constructions of all test-vectors. This eliminates the redundant computation in BR interpolation, resulting in a low decoding complexity. Moreover, the LCC-BR algorithm can decode each test-vector in parallel, lowering the decoding latency. This paper further proposes the progressive LCC-BR (PLCC-BR) algorithm that decodes the test-vectors sequentially and terminates once the intended message is found. This progressive decoding is realized without additional memory cost. Simulation results show the complexity and latency advantages of the proposed algorithms over the other benchmark algorithms.
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Luís Otávio Mataveli, Celso de Almeida · Wireless Personal Communications · 2015
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Tariq Nanji · UWSpace (University of Waterloo) · 2010
This dissertation documents alternative designs of the Zero Forcing decoding algorithm with Successive Interference Cancellation (ZF-SIC) for use in Vertical Bell Laboratories Layered Space Time Architecture (V-BLAST) Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems, in an effort to reduce the computational complexity of the receiver. The development of a wireless platform utilizing this architecture intended for use in an indoor wireless multipath environment was created to analyze the multipath environment. This implementation is the result of efforts from several individuals within the CST group. My contributions are documented in this dissertation. \n \nIn order to obtain channel state information (CSI), a training sequence is sent with each incoming frame. A pseudo-inverse operation is performed on the channel matrix and applied to each OFDM symbol that was received. Performing this operation on each tone and across each OFDM symbol is computationally inefficient in a MIMO configuration. If the number of pseudo-inverses can be reduced while maintaining acceptable levels of bit error, the processing time of each frame can be decreased. \n \nTraditionally, tests of the performance of ZF-SIC have been conducted with simulations modelling a multipath channel. In this thesis, CSI is observed using an open loop platform developed for MIMO-OFDM communications. The rate of change of the channel is observed for different multipath environments. The proposed methods of decoding require modifications to ZF-SIC. The suggested changes are only applicable to a MIMO OFDM based method of data transmission. The most effective method of reducing decoding complexity and maintaining an acceptable number of bit errors was observed to occur in the time domain rather than in the frequency domain. For selecting frames and averaging frames in the time domain it was determined that the optimal number of OFDM symbols per frame is 1932 and 174, respectively.
Cited by 1Open access
Shuai Hu, Kaining Han, Jianhao Hu · IEEE Transactions on Circuits & Systems II Express Briefs · 2023
The size of the state metrics cache (SMC) has a predominant impact on the overall hardware consumption of the Turbo decoder. This brief presents a low complexity SMC reduction algorithm based on the proposed stochastic quantization (SQ) technique, which reduces the size of the SMC by randomly quantizing the state metrics to different small bit-width numbers. The selection of the random source and the updating method of the extrinsic information are further explored to minimize the performance loss caused by bit-width reduction. The simulation and synthesis results show that the proposed algorithm can achieve the best bit error rate (BER) performance with the lowest hardware consumption among the compared SMC reduction algorithms.
Cited by 2
Rare & Special e-Zone (The Hong Kong University of Science and Technology) · 2007
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Mohsen Moradi, Amir Mozammel · IEEE Transactions on Communications · 2023
Sorting operation is one of the main bottlenecks for the successive-cancellation list (SCL) decoding. This paper introduces an improvement to the SCL decoding for polar and pre-transformed polar codes that reduces the number of sorting operations without visible degradation in the code’s error-correction performance. In an SCL decoding with an optimum metric function we show that, on average, the correct branch’s bit-metric value must be equal to the bit-channel capacity, and on the other hand, the average bit-metric value of a wrong branch can be at most zero. This implies that a wrong path’s partial path metric value deviates from the bit-channel capacity’s partial summation. For relatively reliable bit-channels, the bit metric for a wrong branch becomes very large negative number, which enables us to detect and prune such paths. We prove that, for a threshold lower than the bit-channel cutoff rate, the probability of pruning the correct path decreases exponentially by the given threshold. Based on these findings, we presented a pruning technique, and the experimental results demonstrate a substantial decrease in the amount of sorting procedures required for SCL decoding. In the stack algorithm, a similar technique is used to significantly reduce the average number of paths in the stack.
Cited by 18