The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
Gordon L. Stuber - One of the best experts on this subject based on the ideXlab platform.
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Error probability for maximum likelihood sequence estimation of trellis-coded modulation on ISI channels
IEEE Transactions on Communications, 1994Co-Authors: Wern-ho Sheen, Gordon L. StuberAbstract:A method is presented for upper bounding the error probability of trellis-coded modulation on multipath-fading ISI channels that uses one-directional Stack Algorithm. The method provides a tighter upper bound than transfer function bounding techniques, and is useful for large-state systems, because the transfer function is not required. The Stack Algorithm exploits the symmetry properties of the trellis code to reduce computing time. >
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Error probability of reduced-state sequence estimation for trellis-coded modulation on intersymbol interference channels
IEEE Transactions on Communications, 1993Co-Authors: Wern-ho Sheen, Gordon L. StuberAbstract:The error probability of reduced-state sequence estimation (RSSE) for trellis-coded modulation (TCM) on intersymbol interference channels is evaluated. A method based on a Stack Algorithm is proposed to evaluate the union bound on the error probability for ideal RSSE, which is a good approximation to the error probability of real RSSE. The Stack Algorithm is employed because it provides a good tradeoff between computer memory and computing time. >
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Error probability for reduced-state sequence estimation
IEEE Journal on Selected Areas in Communications, 1992Co-Authors: Wern-ho Sheen, Gordon L. StuberAbstract:The performance of ideal reduced-state sequence estimation (RSSE) (without error propagation) is known as a good approximation to the performance of real RSSE. In the literature, the minimum distance of ideal RSSE has been employed for approximating the error probability of real RSSE. However, this approximation can be very poor, even though the system has a large signal-to-noise ratio. In this work, a union upper bound on the error probability for ideal RSSE is used to approximate the true error probability. This union bound provides a better approximation than the minimum distance. A new method based on a Stack Algorithm and a subset-error state diagram is proposed for calculating this union bound. The Stack Algorithm is employed because it provides a good tradeoff between computer memory and computing time. >
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Error probability for reduced-state sequence estimation
ICC 91 International Conference on Communications Conference Record, 1Co-Authors: Wern-ho Sheen, Gordon L. StuberAbstract:A union bound on the error probability for ideal RSSE (reduced-state sequence estimation) is used to approximate the error probability of RSSE. A method based on a Stack Algorithm and a subset-error state diagram is proposed for obtaining the union bound. >
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Error probability of reduced-state sequence estimation for trellis-coded modulation on intersymbol interference channels
IEEE Global Telecommunications Conference GLOBECOM '91: Countdown to the New Millennium. Conference Record, 1Co-Authors: Wern-ho Sheen, Gordon L. StuberAbstract:The error probability of reduced-state sequence estimation (RSSE) for trellis-coded modulation on intersymbol interference channels is evaluated. In the literature, the minimum distance of ideal RSSE (without error propagation) has been used for approximating the error probability of real RSSE, but this approximation can be very poor. A union bound on the error probability for ideal RSSE is shown to provide a much better approximation than the minimum distance. A method based on an error super-state diagram and a Stack Algorithm is proposed for calculating the union bound. >
Wern-ho Sheen - One of the best experts on this subject based on the ideXlab platform.
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Error probability for maximum likelihood sequence estimation of trellis-coded modulation on ISI channels
IEEE Transactions on Communications, 1994Co-Authors: Wern-ho Sheen, Gordon L. StuberAbstract:A method is presented for upper bounding the error probability of trellis-coded modulation on multipath-fading ISI channels that uses one-directional Stack Algorithm. The method provides a tighter upper bound than transfer function bounding techniques, and is useful for large-state systems, because the transfer function is not required. The Stack Algorithm exploits the symmetry properties of the trellis code to reduce computing time. >
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Error probability of reduced-state sequence estimation for trellis-coded modulation on intersymbol interference channels
IEEE Transactions on Communications, 1993Co-Authors: Wern-ho Sheen, Gordon L. StuberAbstract:The error probability of reduced-state sequence estimation (RSSE) for trellis-coded modulation (TCM) on intersymbol interference channels is evaluated. A method based on a Stack Algorithm is proposed to evaluate the union bound on the error probability for ideal RSSE, which is a good approximation to the error probability of real RSSE. The Stack Algorithm is employed because it provides a good tradeoff between computer memory and computing time. >
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Error probability for reduced-state sequence estimation
IEEE Journal on Selected Areas in Communications, 1992Co-Authors: Wern-ho Sheen, Gordon L. StuberAbstract:The performance of ideal reduced-state sequence estimation (RSSE) (without error propagation) is known as a good approximation to the performance of real RSSE. In the literature, the minimum distance of ideal RSSE has been employed for approximating the error probability of real RSSE. However, this approximation can be very poor, even though the system has a large signal-to-noise ratio. In this work, a union upper bound on the error probability for ideal RSSE is used to approximate the true error probability. This union bound provides a better approximation than the minimum distance. A new method based on a Stack Algorithm and a subset-error state diagram is proposed for calculating this union bound. The Stack Algorithm is employed because it provides a good tradeoff between computer memory and computing time. >
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Error probability for reduced-state sequence estimation
ICC 91 International Conference on Communications Conference Record, 1Co-Authors: Wern-ho Sheen, Gordon L. StuberAbstract:A union bound on the error probability for ideal RSSE (reduced-state sequence estimation) is used to approximate the error probability of RSSE. A method based on a Stack Algorithm and a subset-error state diagram is proposed for obtaining the union bound. >
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Error probability of reduced-state sequence estimation for trellis-coded modulation on intersymbol interference channels
IEEE Global Telecommunications Conference GLOBECOM '91: Countdown to the New Millennium. Conference Record, 1Co-Authors: Wern-ho Sheen, Gordon L. StuberAbstract:The error probability of reduced-state sequence estimation (RSSE) for trellis-coded modulation on intersymbol interference channels is evaluated. In the literature, the minimum distance of ideal RSSE (without error propagation) has been used for approximating the error probability of real RSSE, but this approximation can be very poor. A union bound on the error probability for ideal RSSE is shown to provide a much better approximation than the minimum distance. A method based on an error super-state diagram and a Stack Algorithm is proposed for calculating the union bound. >
Zhigang Mao - One of the best experts on this subject based on the ideXlab platform.
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Soft-Input Soft-Output Parallel Stack Algorithm for MIMO Detection
Communications in Computer and Information Science, 2015Co-Authors: Fan Luo, Zhiting Yan, Zhigang MaoAbstract:This paper presents a reduced-complexity soft-input soft-output parallel Stack Algorithm (SISO-PSA) for multiple-input multiple-output (MIMO) wireless communication systems employing Turbo iterative processing at the receiver. The proposed Algorithm incorporates hybrid enumeration and a modified tree pruning criterion to support soft-inputs, which results in significant computational complexity saving. Moreover, a leaf enumeration scheme is proposed to reduce the number of expanded leaf nodes. In addition, the parallelism at Algorithm level provides high throughput while reduces area compared to hardware level parallelism, which is very suitable for VLSI implementation. The simulation results show that the proposed Algorithm can achieve better performance than SISO K-Best Algorithm (K=50) and SISO-FSD with 60% memory saving and significantly reduced computational complexity in terms of the number of visited nodes in a 4(4 64QAM MIMO system.
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a soft output parallel Stack Algorithm for mimo detection
Signal Processing Systems, 2013Co-Authors: Zhi Yue, Zhigang MaoAbstract:In this paper, we propose a parallel Stack Algorithm for MIMO detection to reduce memory and achieve high throughput. Through partitioning the global Stack into multiple local Stacks and assigning them to each non-leaf layer of the tree, the proposed Algorithm performs the best-first strategy on all Stacks in parallel. The parallel processing reduces the iteration loops per detection, and the node pruning rule and the leaf enumeration method help decrease the total Stack size. Moreover, a Dual-term APP approach is designed for the proposed Algorithm to improve BER performance without extra iteration loops. The simulation results demonstrate that the proposed Algorithm reduces the minimum required Stack size and the average number of iteration loops per detection of advanced Stack Algorithm by 50% and 30% respectively to achieve the same BER performance with STS-SD for a 4×4 64QAM MIMO system.
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A memory reduced Stack Algorithm for MIMO detection
2013 IEEE International Conference on Signal Processing Communication and Computing (ICSPCC 2013), 2013Co-Authors: Zhi Yue, Zhigang MaoAbstract:Multiple-input multiple-output (MIMO) technology can enhance the spectral efficiency significantly at the cost of high detection complexity. The Stack Algorithm can minimize the average complexity and achieve the optimal performance, but it suffers from the large memory size to store the candidate nodes. In this paper, we propose a memory reduced Stack Algorithm for soft-output MIMO detection. With the leaf enumeration scheme and parallel hypotheses update method, the proposed Algorithm only stores non-leaf nodes in the Stack and the leaf nodes are used for updating the soft-output. The proposed node pruning rule can simplify the search process and reduce the memory size further. The simulation results show that the proposed Algorithm can reduce the demanded memory size of the advanced Stack Algorithm by 50% to achieve the same BER performance with the STS-SD for a 4 × 4 64QAM MIMO system.
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SiPS - A soft-output parallel Stack Algorithm for MIMO detection
SiPS 2013 Proceedings, 2013Co-Authors: Zhi Yue, Zhigang MaoAbstract:In this paper, we propose a parallel Stack Algorithm for MIMO detection to reduce memory and achieve high throughput. Through partitioning the global Stack into multiple local Stacks and assigning them to each non-leaf layer of the tree, the proposed Algorithm performs the best-first strategy on all Stacks in parallel. The parallel processing reduces the iteration loops per detection, and the node pruning rule and the leaf enumeration method help decrease the total Stack size. Moreover, a Dual-term APP approach is designed for the proposed Algorithm to improve BER performance without extra iteration loops. The simulation results demonstrate that the proposed Algorithm reduces the minimum required Stack size and the average number of iteration loops per detection of advanced Stack Algorithm by 50% and 30% respectively to achieve the same BER performance with STS-SD for a 4×4 64QAM MIMO system.
W.h. Chin - One of the best experts on this subject based on the ideXlab platform.
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VTC Spring - List Stack Detection with Reduced Search Space for MIMO Communication Systems
2006 IEEE 63rd Vehicular Technology Conference, 1Co-Authors: W.h. Chin, S. SunAbstract:The interest in near-ML detection Algorithms for Multiple-Input/ lMultiple-Output (MIMO) systems have always been high due to their drastic performance gain over suboptimal Algorithms. Algorithms such as the M Algorithm and the Stack Algorithm yields near-ML performance while only requiring a fraction of the computational complexity of an ML receiver. While the Stack Algorithm is computationally less intensive than the M Algorithm for uncoded systems and hard decision decoding, the reverse is true for soft decision decoding as a candidate list is required to compute the soft metric. The M Algorithm can easily generate a candidate list at no extra cost, the Stack Algorithm, on the other hand, would require more iterations to generate the list. In this paper, we propose a modified Stack Algorithm which have a lower computational complexity than a conventional one without sacrificing much of the performance of the Algorithm.
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QRD based tree search data detection for MIMO communication systems
2005 IEEE 61st Vehicular Technology Conference, 1Co-Authors: W.h. ChinAbstract:Due to the capacity achievable, multiple-input/multiple-output (MIMO) systems has gained popularity in recent years. While several data detection Algorithms are available for MIMO systems, simple Algorithms usually perform unsatisfactorily, while more complex ones are infeasible for hardware implementation. In this paper, we compare two QRD based tree search Algorithms which can be likely candidates for implementation purposes due to their relatively low computational complexity. The QRD-M Algorithm proposed in (J Yue, et al, 2003) yields near-M L performance while only requiring a fraction of the computational complexity of an ML receiver. The QRD-Stack Algorithm displays similar performance. The performance of both QRD-M and QRD-Stack Algorithms are compared and while both Algorithms achieve near-ML performance, the QRD-Stack Algorithm is shown to be more efficient and has a much lower computational complexity as compared to QRD-M.
Jibo Wei - One of the best experts on this subject based on the ideXlab platform.
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PIMRC - A near-ML sphere constraint Stack detection Algorithm with very low complexity in VBLAST systems
2008 IEEE 19th International Symposium on Personal Indoor and Mobile Radio Communications, 2008Co-Authors: Chun-lin Xiong, De-gang Wang, Jibo WeiAbstract:The Stack Algorithm is a promising tree-search Algorithm with relatively low computation complexity for multi-input multi-output (MIMO) systems. Recent researches show that it obtains low detection complexity at the price of performance degradation. To achieve a better compromise between computational complexity and detection performance, a sphere constraint Stack detection Algorithm (SC-Stack) is proposed in this paper. With the aid of sorted QR decomposition based on the MMSE criterion (MMSE-SQRD), the proposed Algorithm constrains conventional Stack Algorithm by a sphere radius obtained from partial serial interference cancellation (PSIC) Algorithm. The SC-Stack Algorithm avoids abundant metric computation by excluding a large number of nodes from the Stack according to the sphere radius. The simulation results of computational complexity and detection performance presented in this paper show that the SC-Stack Algorithm improves detection performance with lower complexity than the conventional Stack Algorithm. Moreover, the proposed Algorithm achieves almost the same performance as sphere decoding Algorithm while expanding far fewer nodes. So it is more feasible in practical systems.
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ISIT - Multiple Symbol Differential Stack Algorithm for Unitary Space-Frequency Modulation
2007 IEEE International Symposium on Information Theory, 2007Co-Authors: Xin Wang, Jibo WeiAbstract:Differential unitary space-frequency modulation reduces the complexity of multiple-input multiple-output-orthogonal frequency division multiplexing (MIMO-OFDM) systems significantly. But the conventional single symbol differential detection (SSDD) results in a high error floor over a severe multipath spreading channel. To overcome this limitation, a multiple symbol differential Stack Algorithm is proposed by embedding a recursion of maximum-likelihood metric in the Stack Algorithm. The proposed Algorithm is suitable for arbitrary nondiagonal unitary space-frequency constellations and enhances the flexibility to multipath spread compared with SSDD.
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Pruning Stack Algorithm and Complexity Analysis
2007 International Symposium on Signals Systems and Electronics, 2007Co-Authors: Xin Wang, Jibo WeiAbstract:Stuck Algorithm (SA) has been proved to be the most efficient one among the existing sphere decoding Algorithms, although it needs a large amount of time-consuming comparisons. In this paper, a pruning Stack Algorithm (PSA) is proposed to decrease the size of the border node list in SA by statistical pruning. With a proper configuration, a good tradeoff is achieved between the performance and complexity. For high order modulations, PSA is able to reduce the number of comparisons by at least 30% as compared to SA without much penalty of the performance.
