## What is/are Mimo Scheme?

Mimo Scheme - The OFDM precoding makes the waveforms near-complex orthogonal, which enables a straightforward adaptation to channel estimation techniques and MIMO scheme design.^{[1]}QSM is a recently proposed propitious MIMO technique that promises significant advantages over conventional MIMO schemes including high spectral efficiency with single RF-chain transmitter and very low receiver complexity.

^{[2]}In this paper we consider MIMO schemes with strong nonlinear effects at the transmitter side and we propose an iterative receiver that is able to cope with nonlinear effects, allowing excellent performance even with strong nonlinear distortion effects.

^{[3]}A non-regenerative MIMO scheme with transmit antenna selection strategy is considered where a single transmit antenna maximizing the total received signal power is selected for transmission.

^{[4]}Two MIMO schemes on Nakagami-m fading channel are considered, which are: selective transmit /selective receive and selective transmit /maximum ratio combining receive.

^{[5]}In this paper, Robust transmit beamforming method for interference mitigation in MIMO scheme is studied in the presence of array amplitude and phase error.

^{[6]}The simulation results show that the SNR performance enhancement for the UEP- MIMO scheme is approximately 9.

^{[7]}We show experimentally that in the case of no or low oversampling of 1 or 2 samples per symbol (Sps), the MIMO scheme can only be applied if all channels are fully symbol aligned, whereas by oversampling at 3 Sps or higher, operation is possible without symbol alignment.

^{[8]}In the following, we start with the SISO channel capacity for a real-valued signal, extend it to complex signals, and finally derive the channel capacity of a MIMO scheme.

^{[9]}The performance of the underwater virtual MIMO scheme has been examined in computer simulations, where the vehicle-specific mission tracks, simulated acoustic communication channels from BELLHOP, and time reversal communication receivers were used.

^{[10]}Cooperative MIMO scheme is one of the techniques where more nodes present near to the sink suffers traffic burden to forward the data from other cluster head in the network that causes hot spot problem.

^{[11]}2 % higher BER performance compared to the traditional MIMO scheme with an increase in the BER using MMSE and ZF respectively in both two and four antennas.

^{[12]}However, current solvers either get stuck in a local minimum or have much computational complexity of GenSM-aided mm-wave MIMO schemes because the non-convex nature of the hybrid precoding design incurs significant performance degradation.

^{[13]}Numerical simulation results demonstrate that the proposed scheme outperforms the conventional MIMO scheme.

^{[14]}The proposed method offers a good match with the simulated results in terms of the downlink SIR as well as mean and outage spectral efficiency for various MIMO schemes such as transmit and receive diversity, closed- and open-loop spatial diversity, and closed-loop multiuser MIMO.

^{[15]}Our information-theoretic results demonstrate that, unlike in the previous studies, single-RF SM schemes do not exhibit any substantial advantages over the conventional full-RF MIMO schemes for a low number of transmit antennas, while for a large-scale antenna array, single-RF SM schemes outperform the conventional full-RF MIMO schemes.

^{[16]}We have investigated the theory and carried out detailed analysis pertaining to encoding/decoding of chaotic modulation schemes, the use of suitable LDPC coded MIMO schemes for providing secure and reliable communication.

^{[17]}Moreover, for further comparison we integrate deep neural networks (DNN) with these adaptive SM-MIMO schemes, and propose a novel DNN-based multi-label classifier for TAS and PA parameter evaluation.

^{[18]}However, the CMIMO scheme introduces extra energy overhead to cooperative devices and further reduces the lifetime of these devices.

^{[19]}Numerical results show that distributed MIMO schemes with zero-forcing (ZF) beamforming and MPA have the potential of providing SINR gains in the order of tens of dB with respect to a centralized MIMO deployment, as well as that the impulsive noise can strongly degrade the system performance and thus requires specific detection and mitigation techniques.

^{[20]}The performance degradation effect of atmospheric turbulence and pointing errors can be reduced by using MIMO scheme, that is by increasing the number of transmit and/or receive apertures.

^{[21]}Our goal is to maximize the AEE by deploying the optimal number of BSs given some requirements, such as demanded network capacity, amount of interference and employed MIMO scheme.

^{[22]}However, the performance advantages combined with the possibility of parallel receiver implementations, make those techniques particularly interesting for m-MIMO schemes, either employing OFDM or SC-FDE modulations.

^{[23]}Simulation results show that the proposed method has significant improvement in spectral efficiency and bit-error-rate (BER) performance as compared to other MIMO schemes.

^{[24]}However, the expensive hardware and software overheads for transmitting and receiving OAM waves lead to an unexpected cost for the OFDM-OAM MIMO scheme.

^{[25]}Since the required overheads in massive MIMO schemes can be too high, leading to spectral degradation, the use of superimposed pilots (i.

^{[26]}To address these challenges, we propose a novel compressed sensing (CS)-based nonorthogonal multiple access (NOMA) multiple-input multiple-output (MIMO) scheme, called the CS-NOMA MIMO scheme, for the downlink of massive mission-critical machine-type communication (mmcMTC).

^{[27]}Based on the framework of SPIM-mmWave, a fundamental study is conducted towards a theoretic condition under which SPIM-mmWave guarantees to outperform conventional mmWave-MIMO schemes.

^{[28]}Compared to conventional massive MIMO, the proposed cache-aided massive MIMO scheme achieves a significantly higher ergodic rate especially when the number of users approaches the number of transmit antennas.

^{[29]}The MIMO schemes considered for this paper are repetition coding (RC), space-time block codes (STBCs), and spatial multiplexing (SMP).

^{[30]}In this paper, we develop a joint blind identification algorithm to determine the number of transmit antennas and MIMO schemes simultaneously.

^{[31]}

## Conventional Mimo Scheme

QSM is a recently proposed propitious MIMO technique that promises significant advantages over conventional MIMO schemes including high spectral efficiency with single RF-chain transmitter and very low receiver complexity.^{[1]}Numerical simulation results demonstrate that the proposed scheme outperforms the conventional MIMO scheme.

^{[2]}

## Massive Mimo Scheme

Since the required overheads in massive MIMO schemes can be too high, leading to spectral degradation, the use of superimposed pilots (i.^{[1]}Compared to conventional massive MIMO, the proposed cache-aided massive MIMO scheme achieves a significantly higher ergodic rate especially when the number of users approaches the number of transmit antennas.

^{[2]}