Efficient Capacity-Based Antenna Selection for MIMO Systems

Jensen, M.A.; Morris, M.L.

doi:10.1109/tvt.2004.838886

Cited by 32 publications

(4 citation statements)

References 19 publications

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“…This is an advantage of the proposed capacity expression, especially in adaptive applications in fast fading environment in which transmission parameters are changed adaptively based on the varying channel capacity (e.g. capacity‐based antenna selection [15]).…”

Section: Simulation Resultsmentioning

confidence: 99%

Approximate ergodic capacity of multiuser massive multiple input multiple output in a Rayleigh fading uplink channel with variance profile

Kazemi

Aghaeinia

2015

IET Communications

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Massive MIMO has become a key technology to the next wireless communication generation for its improvement in data rate, link reliability and power consumption; however, these benefits come at the cost of enormous data quantity, especially in the data detection of Massive MIMO uplink. In this paper, we propose a novel matrix inversion to balance the computational complexity and performance by providing selection of the 2-terms Neumann series approximation and the LDL decomposition matrix inversion methods according to different dimensions of the channel matrix. To reduce the hardware resource for two inversion algorithms and execute tasks efficiently, we consider the reconfigurable implementation for its flexibility and high-power efficiency. The implementation results are given by using our Reconfigurable Computing System for various antenna configurations. With this reconfigurable implementation, the throughput can achieve 93.8Mb/s, 130.4Mb/s, 82.2Mb/s and 107.1Mb/s for a 14×4 , 32×4 , 64×8 and 128× 8 system respectively, which are chose to even better than few implementations for high dimension problems.

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Section: Simulation Resultsmentioning

confidence: 99%

Approximate ergodic capacity of multiuser massive multiple input multiple output in a Rayleigh fading uplink channel with variance profile

Kazemi

Aghaeinia

2015

IET Communications

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“…Since each antenna requires its respective RF (Radio Frequency) chain, the number of antenna that can be deployed is often limited, especially for mobile handset. Motivated to address this issue, antenna selection concept is introduced in [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Low Complexity Antenna Selection Scheme for Multicarrier MIMO Broadcast Communication

Kurniawan

Madhukumar

Chin

2009

J Sign Process Syst

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A low complexity antenna selection scheme for multicarrier MIMO (Multiple Input Multiple Output) broadcast systems is proposed in this paper. Under special condition of single user in the system or when the number of subcarrier is only one, the system reduces to conventional MIMO-OFDM (Orthogonal Frequency Division Multiplexing) system or MIMO-BC (Broadcast Channel) system respectively. By analysing sub-optimal antenna selection schemes developed earlier for single user MIMO-OFDM systems and single carrier MIMO-BC systems, one can see many similarities which can be extended to multicarrier MIMO broadcast systems. The proposed method exploits these similarities to obtain a low complexity system design with acceptable performance. The performance of the proposed scheme is studied via extensive simulation, and the computational complexity involved is compared to the conventional scheme. A selection gain of approximately 0.5 b/s/Hz is shown to be achievable using only two out of three antennas, and the proposed scheme is able to achieve up to 90% of the gain. This is

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“…Both analytical [2][3][4][5][6][7][8][9][10][11] and stochastic [12] algorithms for antenna selection have been proposed. However, when a limited number of frequency converters are available, antenna selection schemes suffer from severe performance degradations in most fading channels.…”

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confidence: 99%

Robustness of Weighting Receive Antenna Selection Algorithm

Wang

2010

Wireless Pers Commun

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The conventional antenna selection schemes suffer from severe performance degradations in most fading channels. This paper proposes a new receive antenna selection algorithm based on the theory of convex optimization that improve the system performance over Rayleigh fading multiple-input multiple-output (MIMO) channels. With this method, each Radio Frequency chain is not allocated to a single antenna element, but instead to the complex-weighted and combined response of a group array of elements. In this paper, we firstly get optimal solution under no constraints. Then, suboptimal algorithms are introduced based on minimised the squared error and convex optimization technique. The Monte-Carlo simulations show that the algorithm proposed can provide the performance very close to that of the optimal selection based on exhaustive search.

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Efficient Capacity-Based Antenna Selection for MIMO Systems

Cited by 32 publications

References 19 publications

Approximate ergodic capacity of multiuser massive multiple input multiple output in a Rayleigh fading uplink channel with variance profile

Approximate ergodic capacity of multiuser massive multiple input multiple output in a Rayleigh fading uplink channel with variance profile

Low Complexity Antenna Selection Scheme for Multicarrier MIMO Broadcast Communication

Robustness of Weighting Receive Antenna Selection Algorithm

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