Efficient Transmit Antenna Selection Research Articles

Energy efficient transmit antenna selection scheme for correlation relied beamspace mmWave MIMO system

mmWave communication system that offers high datarate are accompanied by massive number of antennas for high gain transmission. These large array of antennas requires special beamforming schemes and also requires large number of RF chains. Beamspace MIMO is a beamforming architecture that employs large antenna array and supports limited number of RF chains by converting conventional mmWave channel into sparse channel. Multiple antenna array system are susceptible to antenna correlation effect thereby reducing the system capacity. Transmit antenna selection methods considering the effect of antenna correlation provides feasible solution by maximising the system capacity and energy efficiency. In order to improve the energy efficiency of the transmitted signal three new transmit antenna selection schemes are proposed by considering the effects of antenna correlation. The simulation results demonstrate that the proposed methods improve energy efficiency and sum rate.

Efficient transmit antenna selection and resource allocation scheme for mmWave D2D networks

Employing switchable directional antennas in the user equipment (UE) is becoming a popular method to replace conventional beamforming methods. This approach is mainly applicable to mmWave networks due to the small size of directional microstrip antenna elements on corresponding frequencies, and requires exploiting proper transmit antenna selection (TAS) schemes to obtain the optimal directivity of selected active antennas. TAS is rather complex in the heterogeneous cellular networks with underlaid D2D communication. For each D2D user, selecting transmit antennas with maximum radiation gain does not necessarily lead to the optimal throughput due to the potential interference that might be imposed on other high priority users, thus, finding the optimal transmit antennas of users is generally a challenging issue in networks with multi-antenna D2D users. In this work, based on Lagrangian relaxation method, we propose a novel and efficient transmit antenna selection and resource (channel and power) allocation (ASRA) for D2D mmWave networks. In order to validate the performance of our proposed algorithm, we devise another efficient low-complexity greedy-based ASRA as well. Numerical results verify the performance of our proposed Lagrangian-based ASRA in comparison to other methods.

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

In this article, two efficient transmit antenna subset (TAS) selection schemes are proposed for receive spatial modulation (RSM)-based massive multiple-input multiple-output. First, an incremental TAS selection algorithm based on the maximization of the received signal-to-noise ratio is presented to select N S active transmit antennas effectively among the available Nτ transmit antennas. Then, to reduce complexity further, the modified TAS selection algorithm performs two consecutive selection stages. The pre-processing stage selects active transmit antennas whose number Np is less than the number of N S of the total transmit antennas to be selected and is equal to or greater than the number N R of the receive antennas. Then the post-processing stage chooses the remaining N S - Np active antennas. In the first stage, a simple norm-based algorithm is employed to reduce the complexity significantly. In the second stage, an incremental selection strategy is performed to find additional transmit antennas. It is demonstrated that the bit error rate and achievable rate of the proposed TAS selection algorithms are close to those of the decremental algorithm. Further, the simulation results show that the proposed TAS selection schemes offer significantly reduced complexity compared to the decremental TAS selection when the difference between the number of selected transmit antennas and the number of total available transmit antennas available is large. Furthermore, the impacts of the channel estimation error on the performance of TAS selection-based RSM systems are examined.

Secrecy analysis of alamouti scheme using feedback-rate efficient transmit antenna selection with robust error performance in the presence of feedback errors

This paper proposes a new feedback rate efficient transmit antenna selection (TAS) with Alamouti scheme (AS) with robust error performance which improves physical layer security (PLS) in multiple-input-multiple-output (MIMO) wiretap channel. The proposed scheme is accomplished in two steps (1) The transmitter fixes one antenna and then transmitter select the strongest antenna out of remaining NT-1 ones, depending on the feedback from receiver (2) The AS is applied at the fixed antennas for data transmission. Two different scenarios based on availability of channel state information of eavesdropper at the transmitter are examined. The proposed scheme achieves higher average secrecy capacity (ASC) and lower secrecy outage probability (SOP) by selecting two antennas. The result shows that ASC is higher for lower value of signal to noise (SNR) at eavesdropper.

Enhanced Transmit-Antenna Selection Schemes for Multiuser Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) systems are a core technology designed to achieve the performance objectives defined for 5G wireless communications. They achieve high spectral efficiency, reliability, and diversity gain. However, the many radio frequency chains required in base stations equipped with a high number of transmit antennas imply high hardware costs and computational complexity. Therefore, in this paper, we investigate the use of a transmit-antenna selection scheme, with which the number of required radio frequency chains in the base station can be reduced. This paper proposes two efficient transmit-antenna selection (TAS) schemes designed to consider a trade-off between performance and computational complexity in massive MIMO systems. The spectral efficiency and computational complexity of the proposed schemes are analyzed and compared with existing TAS schemes, showing that the proposed algorithms increase the TAS performance and can be used in practical systems. Additionally, the obtained results enable a better understanding of how TAS affects massive MIMO systems.

Multi-User Massive MIMO 네트워크에서 에너지 효율적인 전송 안테나 선택 기법

Multi-User Massive MIMO 네트워크에서 에너지 효율적인 전송 안테나 선택 기법

Novel transmit antenna selection strategy for massive MIMO downlink channel

In this paper, we deal with the problem of acquiring the channel state information (CSI) at the transmitter in large-scale multiple input multiple output (MIMO) systems, so-called massive MIMO systems. Clearly, obtaining CSI plays a central role to provide high system performance. Even though, in frequency-division duplexed systems, acquiring this information requires a prohibitive amount of feedback, since it increases with the number of transmit antenna. In this work, we design an efficient transmit antenna selection strategy aware of the amount of required CSI for a point-to-multipoint transmission in massive MIMO systems. The proposed strategy provides high sum-rate with limited CSI feedback and limited computational complexity. Innovatively, the antenna selection in our strategy is performed in a decentralized fashion successively at the receiving users. Two schemes are proposed in this work to perform the antenna selection at each user. Next, taking into consideration that the large-scale MIMO transmitter suffers from imperfect knowledge of CSI, we design a new performance criterion. Computer simulations validate that, when the CSI is perfectly known, the proposed strategy is able to achieve high performance in terms of system sum-rate while a significant reduction in both CSI feedback overhead and computational complexity is observed. Moreover, assuming imperfect CSI, the new proposed criterion achieves higher performance when the estimation accuracy is low and at high SNR regime.