Efficient Transmit Antenna Selection for Receive Spatial Modulation-Based Massive MIMO

Kim, Sangchoon

doi:10.1109/access.2020.3017024

Cited by 14 publications

(17 citation statements)

References 25 publications

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“…The QPSK modulation is assumed. The performance gain obtained by TRAS selection is compared with those of only RAS selection of [23] as well as only TAS selection of [18] and [20].…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Then the decremental TAS selection algorithm is given in Table 2 and named as D-dec-TAS. For further complexity reduction, we adopt the incremental TAS selection algorithm given in Table 3, which is also introduced in [20], and called as Dinc-TAS. From Table 2 and 3, their computational complexity in terms of RMs and RSs, respectively, can be evaluated as…”

Section: S S N  mentioning

confidence: 99%

“…Previous works on antenna subset selection cover either transmit antenna subset (TAS) selection or receive antenna subset (RAS) selection. TAS selection has been considered for the SM systems [13]- [16] and for the PSM systems [17]- [20]. RAS selection has been studied for the PSM systems [21]- [23].…”

Section: Introductionmentioning

confidence: 99%

“…In [18], the effects of only TAS selection on the bit error rate (BER) performance of the zero-forcing (ZF)-based PSM systems have been investigated. In [20], two TAS selection schemes with lowcomplexity have been developed for the PSM systems. In [21], optimal and greedy algorithms are considered to select an RAS for the PSM systems.…”

Section: Introductionmentioning

confidence: 99%

“…It should be pointed out that the decremental and incremental TAS algorithms proposed in [18] and [20] are employed for the second step (i.e., TAS selection) in the decoupled TRAS selection scheme of this work. Note that [18] and [20] consider only TAS selection. By contrast, this work proposes an optimal joint TRAS selection scheme for the PSM systems as we have said above.…”

Section: Introductionmentioning

confidence: 99%

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Decoupled Transmit and Receive Antenna Selection for Precoding-Aided Spatial Modulation

Kim

2021

IEEE Access

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This paper proposes an optimal joint transmit and receive antenna subsets (TRASs) selection scheme for linear precoding-aided spatial modulation (PSM) systems. The optimal joint TRASs selection is performed by exhaustively searching, so that it is difficult to analyze an achievable diversity gain and it has a huge complexity. To tackle this problem, we propose a decoupled TRAS selection method which selects receive antenna subset (RAS) and transmit antenna subset (TAS) in a two-step serial manner. By computing a lower bound on the pairwise error probability and conducting extensive simulations, it is shown that the zero-forcing (ZF)-based PSM system with T N transmit antennas, S N selected transmit antennas, R N receive antennas, and D N selected receive antennas achieves diversity order of ( 1)( 1)

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“…The QPSK modulation is assumed. The performance gain obtained by TRAS selection is compared with those of only RAS selection of [23] as well as only TAS selection of [18] and [20].…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: S S N  mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Decoupled Transmit and Receive Antenna Selection for Precoding-Aided Spatial Modulation

Kim

2021

IEEE Access

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An energy efficient resource allocation and transmit antenna selection scheme in mm‐wave using massive multiple‐input multiple‐output technology

Singh

Kishoreraja

2022

Int J Communication

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Summary The massive multiple‐input multiple‐output (MIMO) improves the reliability of transmission and capacity of the channel. Resource allocation (RA) and transmit antenna selection (TAS) can minimize the complexity in implementation and hardware costs. In this research, both the RA and the TAS of wireless communication in millimeter‐wave (mm‐wave) with massive MIMO technology are considered. Two different solutions are developed for this research such as the deep learning method for efficient resource allocation process and optimization algorithm for TAS process. Here, the RA process is done with the help of attention‐based capsule auto‐encoder (ACAE) architecture which allocates the radio resources like power, space, time and frequency to all the available users in the system. Further, battle royale optimization (BRO) algorithm is utilized to select an efficient antenna from multiple antennas at BS. This optimization algorithm optimally selects an efficient antenna so that, user equipment (UEs) can create high quality links and achieves a reduced power consumption rate of the whole architecture. The overall system performance depends on the selection of optimal antenna which in terms enhances spectral efficiency (SE), energy efficiency (EE), reliability, and diversity gain of MIMO technology. In this way, both RA and optimal antenna selection schemes are performed to maximize the overall performance of wireless communication with massive MIMO technology for 5G wireless communication applications. The implementation of the proposed methodology is evaluated on MATLAB. Finally, the efficiency of the developed method is improved with respect to the capacity, EE, and SE.

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Efficient User Subset Selection for Multiuser Space-Time Line Code Systems

Kim

2022

IEEE Access

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This paper considers the problem of user subset (US) selection for minimizing the bit error rate (BER) of multi-user space-time line code (MU-STLC) multiple-input multiple-output systems with fairness-aware per-user power allocation. The optimal selection criterion suitable for MU-STLC transmissions based on zero forcing (ZF) precoding is given and two efficient algorithms are then proposed. First, an incremental search approach is presented for US selection in the MU-STLC systems. The proposed suboptimal solution to BER minimization starts an empty US and adds users one by one, where the lowcomplexity recursive computation of the block matrix inverse is further performed. Second, by avoiding recurring matrix computations in each incremental procedure of the first algorithm, a more efficient algorithm is developed. It is observed through simulation results that the proposed incremental-based algorithms achieve most US selection gains with very low complexity. In addition, it is demonstrated that when there are N T transmit antennas, U users (each user has 2 receive antennas), and K selected users, the achievable upper diversity order of the ZF precoding-based MU-STLC systems with optimal US selection is given as 2(N T − K + 1)(U − K + 1). The analytical diversity order is well-matched with simulation results.INDEX TERMS User selection, multiple input multiple output (MIMO), precoding, multiuser diversity, space-time line code.

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Efficient Transmit Antenna Selection for Receive Spatial Modulation-Based Massive MIMO

Cited by 14 publications

References 25 publications

Decoupled Transmit and Receive Antenna Selection for Precoding-Aided Spatial Modulation

Decoupled Transmit and Receive Antenna Selection for Precoding-Aided Spatial Modulation

An energy efficient resource allocation and transmit antenna selection scheme in mm‐wave using massive multiple‐input multiple‐output technology

Efficient User Subset Selection for Multiuser Space-Time Line Code Systems

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