Adaptive Transmit Antenna Selection Based on PCA for Millimeter Wave LOS MIMO Channel

Zhu, Linggang; Zhu, Jiang; Wang, Shilian; Zhang, Jiao

doi:10.1109/access.2019.2892869

Cited by 12 publications

(8 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In 2018, Li Zhu et al [8], conducted a study on the point to-point mm-Wave LOS MIMO channel on the basis of the URA. For URA, the deployment of the optimal antenna was derived to attain the utmost multiplexing gain in the mm-Wave LOS MIMO channel.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In addition,  t RK signifies the average rank of th t antenna configuration that is stated in eq. ( 6), whereas (8) The next objective function is the explicit objective function, which plays a key task in assigning ranks for antenna configuration on the basis of the error rate of the received and transmitted data. The subsequent objective function is stated in eq.…”

Section: Objective Functionmentioning

confidence: 99%

See 1 more Smart Citation

Self-adaptive Particle Swarm Optimization for Optimal Transmit Antenna Selection

2020

JNACS

View full text Add to dashboard Cite

Generally, Multiple-Input Multiple-Output (MIMO) improves radio communication with enhanced reliability and capacity. The transmitter and receiver side, since there is an occurrence of multiple antennas, the appropriate Transmit Antenna Selection (TAS) for obtaining effectual performance is still a difficult point. In this work, a TAS method in the LTE system by exploiting Self-Adaptive Particle Swarm Optimization (SAPSO) is proposed for enhancing the system performance. Moreover, it develops self adaptiveness in the PSO by deciding the ability enhancement attained by each candidate solution for the TAS issue goes after by updating the particle solution on the basis of the enhancement. The experimentation model considers both Rician and Rayleigh channel, for four antenna configurations such as 2×2, 3×2, 4×2 and 4×4. To the next of the experimentation, it evaluates the performance of SAPSO-TAS with conventional Genetic Algorithm (GA)-TAS, Artificial Bee Colony (ABC)-TAS, Firefly (FF)-TAS, PSO-TAS, and Grey Wolf Optimization (GWO)-TAS models.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Objective Functionmentioning

confidence: 99%

Self-adaptive Particle Swarm Optimization for Optimal Transmit Antenna Selection

2020

JNACS

View full text Add to dashboard Cite

show abstract

“…It satisfies to large data rates that require an effective and reliable digital transmission [2]. Multiple RF chains are required for multiple antennas with amplifiers, analog to digital converters, mixers, etc., but they are more expensive [3,4]. In MIMO system has two techniques, one kind of technique is spatial multiplexing and another kind of technique is Space Time Coding (STC).…”

Section: Introductionmentioning

confidence: 99%

“…For a transmission purpose in TAS-MIMO system, a single subset of antenna is selected with Maximal Ratio Combining (MRC) [10,11]. In TAS system for multiple fading channel is implemented the BER efficiency [12].…”

Section: Introductionmentioning

confidence: 99%

Performance of Transmit Antenna Selection in Multiple Input Multiple Output-Orthogonal Space Time Block Code (MIMO-OSTBC) System Joint with Bose-Chaudhuri-Hocquenghem (BCH)-Turbo Code (TC) in Rayleigh Fading Channel

Deotale

2021

IJIE

View full text Add to dashboard Cite

The Transmit antenna selection (TAS) technique is essential to increase the efficiency of spatial modulation (SM) systems. This TAS is an effective technique for reducing the Multiple Input Multiple Output (MIMO) systems, which can increase the computational difficulty and Bit error rate (BER) by various TAS algorithms. But these selection methods cannot provide code gain, so it is essential to join the external code in TAS to obtain code gain advantages in BER. In some existing work, the improved BER has been perceived by joining Forward Error Correction Code (FEC) and Space Time Block Code (STBC) for MIMO systems provided greater code gain. A multiple TAS-OSTBC technique with new integration of Bose–Chaudhuri–Hocquenghem (BCH)-Turbo code (TC) is proposed in this paper. The TAS-OSTBC system connects with the external BCH code in sequence of internal Turbo code. This combination can provide increasing code gain and the effective advantages of the TAS-OSTBC system. To perform the system analysis Rayleigh channel is utilized. In the case with multiple TAS-OSTBC systems, better performance can provide by this new combination of the BCH-Turbo compared to the conventional Turbo code for the Rayleigh fading.

show abstract

“…in spatial modulation and millimeter wave MIMO systems for performance enhancement [20], [21]. In an MU-STLC system, TAS is performed by finding the antenna subset minimizing the mean square error (MSE) (or equivalently maximizing the detection SINR), and the optimal TAS design requires O(M U +3 ) computational complexity which is prohibitively large especially when M and/or U is large.…”

Section: Introductionmentioning

confidence: 99%

Multiuser Space–Time Line Code With Transmit Antenna Selection

Joung

Choi

2020

IEEE Access

View full text Add to dashboard Cite

In this paper, a multiuser space-time line code (MU-STLC) scheme is newly designed that concurrently delivers multiple STLC signals to multiple users, and a preprocessing matrix for the MU-STLC is derived based on the minimum mean square error criterion. The novel MU-STLC method retains the conventional STLC receiver structure so that each user linearly combines the received signals without using the full channel state information to decode the STLC signals. With more transmit antennas than the number of users having two receive antennas, a transmit antenna selection (TAS) scheme is investigated in combination with the proposed MU-STLC method, and the detection signal-to-interferenceplus-noise ratio (SINR) is derived depending on a specific TAS pattern. The performance improvement obtained from the TAS is significant, yet finding the optimal TAS pattern is a combinatorial problem that requires prohibitively high computational complexity. To resolve this issue, a greedy TAS algorithm is also proposed that iteratively selects the transmit antenna maximizing the detection SINR in each greedy step. The numerical results verify the efficacy of the proposed MU-STLC system with the SINR-based greedy TAS algorithm in terms of the bit error rate performance and computational complexity. For example, comparing with a scheme that selects four antennas from eight antennas randomly to support four users, the proposed TAS scheme can reduce the required signal-to-noise ratio for achieving 10 −3 bit-error-rate by approximately 6 dB when quadrature phase-shift keying is employed. Furthermore, the proposed method can achieve comparable performance to the optimal antenna selection scheme with the reduced computational complexity by O(M 5 ) from O(M U +3 ), where M and U are the numbers of transmit antennas and selected antennas (or users), respectively.INDEX TERMS Space-time line code, multiuser, transmit antenna selection, greedy algorithm.

show abstract

Adaptive Transmit Antenna Selection Based on PCA for Millimeter Wave LOS MIMO Channel

Cited by 12 publications

References 34 publications

Self-adaptive Particle Swarm Optimization for Optimal Transmit Antenna Selection

Self-adaptive Particle Swarm Optimization for Optimal Transmit Antenna Selection

Performance of Transmit Antenna Selection in Multiple Input Multiple Output-Orthogonal Space Time Block Code (MIMO-OSTBC) System Joint with Bose-Chaudhuri-Hocquenghem (BCH)-Turbo Code (TC) in Rayleigh Fading Channel

Multiuser Space–Time Line Code With Transmit Antenna Selection

Contact Info

Product

Resources

About