A New GFDM Receiver with Tabu Search

Jeong, Ji-Suk; Jung, Insik; Kim, Jintae; Hong, Daesik

doi:10.1109/vtcspring.2019.8746322

Cited by 4 publications

(5 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The TS algorithm is also applied to various systems N. T. Nguyen to improve performance. In [8], the advantage of TS is used to find the initial solution with low complexity to mitigate the interference in generalized frequency-division multiplexing systems. In [9], Kayal et al propose a TS-based dynamic thresholding approach to detect hard exudates in retinal images.…”

Section: Introductionmentioning

confidence: 99%

Groupwise Neighbor Examination for Tabu Search Detection in Large MIMO Systems

Nguyen

Lee

2020

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

In the conventional tabu search (TS) detection algorithm for multiple-input multiple-output (MIMO) systems, the metrics of all neighboring vectors are computed to determine the best one to move to. This strategy requires high computational complexity, especially in large MIMO systems with high-order modulation schemes such as 16-and 64-QAM signaling. This paper proposes a novel reduced-complexity TS detection algorithm called neighbor-grouped TS (NG-TS), which divides the neighbors into groups and finds the best neighbor by using a simplified cost function. Furthermore, based on the complexity analysis of NG-TS, we propose a channel ordering scheme that further reduces its complexity. Simulation results show that the proposed NG-TS with channel ordering can achieve up to 85% complexity reduction with respect to the conventional TS algorithm with no performance loss in both low-and higher-order modulation schemes.

show abstract

Section: Introductionmentioning

confidence: 99%

Groupwise Neighbor Examination for Tabu Search Detection in Large MIMO Systems

Nguyen

Lee

2020

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…[17] and [18] reduce the receiver complexity by employing frequency domain processing. In addition, different techniques have been adopted to achieve low-complexity receiver implementation, such as sparsification and block diagonalization [19], Taylor series and conjugate gradient [20], and tabu search [21]. Differently, some works focus on the transmitter side, such as [22] reducing the transmitter complexity with the technique of subcarrier-wise DFT.…”

Section: B Low-complexity Transceiver Implementationmentioning

confidence: 99%

An Overview of Generalized Frequency Division Multiplexing (GFDM)

Tai¹,

Wang²,

Huang³

2021

Preprint

View full text Add to dashboard Cite

<div>As a candidate waveform for next-generation wireless communications, generalized frequency division multiplexing (GFDM) features several decent properties which make it promising. In this paper, we systematically overview the research about GFDM. We start with GFDM transceivers with their main components, which consist of prototype ﬁlter design, low-complexity transceiver implementation, and symbol detection algorithms. Then, we investigate a couple of non-ideal issues of GFDM, including synchronization issues, channel estimation, and in-phase/quadrature (I/Q) imbalance compensation. Lastly, we study the applications of GFDM-based cognitive radio and full-duplex radio which boast of a high spectral efﬁciency.</div>

show abstract

“…The tabu search (TS) is a kind of heuristic algorithm, which is used in combinatorial optimization problems to obtain the optimum solution. TS is required in many applications to solve optimization problems, including quadratic assignment problems (QAP) [12], detection problems [13], and GFBM systems [14], etc., for their efficiency. The TS algorithm relies on the concept of 'tabu', which prohibits the search of previous searched results to avoid falling into local maximum solution.…”

Section: Related Work and Motivationmentioning

confidence: 99%

“…When the tabu period S of the tabu object is non-zero, the corresponding tabu object is prohibited [14].…”

Section: Tabu Tablementioning

confidence: 99%

“…With the neighborhood definition in (14), the neighborhood may lay beyond the index interval near the boundary, i.e., v t−1 < 1 or v t+1 > V t and h t−1 < 1 or h t+1 > H t . To remedy the boundary problem of the neighborhood, we suppose the vertical direction in the neighborhood as v * and the horizontal direction in the neighborhood as h * , when v * < 1 or v * > V, we have…”

Section: Neighborhood Boundary Descriptionmentioning

confidence: 99%

See 1 more Smart Citation

Beam Training for Millimeter-Wave Communication Based on Tabu Table Enhanced Rosenbrock Algorithm

Sun

Jiang

2019

Future Internet

View full text Add to dashboard Cite

The codebook-based beamforming for millimeter-wave (mm Wave) communication systems is usually used to compensate the severe attenuation of the mm Wave region. The beam training process based on pre-specified beam codebooks is considered a global optimization problem in 2-D planes formed by the potential beam index. The Rosenbrock algorithm (RA) is adopted to implement optimum beam searching whereas the simulated annealing (SA) algorithm is used to solve the problem of falling into the local optimum, due to the unavailable gradient information of the objective function. However, the RA implements rounding to the integer which leads to the problem of repeated search and beam space discontinuity caused by beam index will impair the powerful local search ability. Thus, in this paper, an enhanced RA based on tabu search and combined with SA algorithm is proposed as an alternative solution for beam search success rate. The proposed algorithm reduces the search times by forbidding the repeat search with tabu table and design of neighbor region. Moreover, to prevent the search failure, the search candidate index is defined to keep the local search ability of the original algorithm and wrap around of beam index is applied to maintain continuity of the search direction. Experimental simulations show that the proposed technique can improve the search efficiency in terms of reduced steps and increase search success rate during the beam training procedure compared to existing techniques.

show abstract

A New GFDM Receiver with Tabu Search

Cited by 4 publications

References 17 publications

Groupwise Neighbor Examination for Tabu Search Detection in Large MIMO Systems

Groupwise Neighbor Examination for Tabu Search Detection in Large MIMO Systems

An Overview of Generalized Frequency Division Multiplexing (GFDM)

Beam Training for Millimeter-Wave Communication Based on Tabu Table Enhanced Rosenbrock Algorithm

Contact Info

Product

Resources

About