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In massive multiple-input multiple-output (M-MIMO) systems, a large number of antennas increase system complexity as well as the cost of hardware. In this paper, we propose an M-MIMO-OFDM model using per-subcarrier antenna selection and bulk antenna selection schemes to mitigate these problems. Also, we derive a new uplink and downlink energy effic...
Citations
... The authors used the cross-layer approach based on system capacity and system throughput for energy-efficient antenna selection, which improved the EE of the system. A comparison between the per-subcarrier antenna selection scheme and the bulk antenna selection scheme is presented in [16] for the massive MIMO OFDM system. Upon analyzing the EE, the bulk antenna selection scheme performs better than the persubcarrier antenna selection system. ...
... This entails a power consumption model that incorporates transmit power amplifier, RF switching power, and circuitry power consumption [60,61]. Also, the cases of imperfect CSI and SIC can potentially be considered and incorporated into the algorithmic designs to maximize the spatial-diversity gains. ...
This paper considers the problem of joint power allocation and antenna selection (J-PA-AS) for downlink (DL) and uplink (UL) clustered non-orthogonal multiple-access (NOMA) networks. In particular, the goal is to perform antenna selection for each user cluster and allocate transmit power to its users so as to maximize the network sum-rate in the DL and UL directions, while satisfying quality-of-service (QoS) requirements. The formulated problem happens to be non-convex and NP-hard, and thus, there is no systematic or computationally-efficient approach to solve it directly. In turn, a low-complexity two-stage algorithm is proposed. Specifically, the first stage optimally solves the sum-rate maximizing power allocation for each (antenna, user cluster) pair. After that, antenna selection is optimally solved in polynomial-time complexity via the Kuhn-Munkres with backtracking (KMB) algorithm. Extensive simulation results are provided to validate the proposed algorithm, which is shown to efficiently yield the optimal network sum-rate in each link direction, in comparison to the optimal J-PA-AS scheme (solved via a global optimization package), and superior to other benchmark schemes. Light is also shed on the impact of spatial-diversity on the network sum-rate, where it is shown that the greater the number of base-station antennas is, the higher the network sum-rate, and the lower the outage events. Additionally, the significance of decoupling antenna selection in each link direction on the network sum-rate is highlighted. Lastly, the cases of imperfect channel state information (CSI) and imperfect successive interference cancellation (SIC) have been investigated, where it is demonstrated that spatial-diversity gains reduce the adverse effect of imperfect CSI and SIC on the network sum-rate.
... In [15] the capacity to the total energy consumption per bit ratio of multiple antennas systems with distributed fashion is evaluated in the case where MIMO is used for WSNs with Rician fading channel modeling. In [16]- [18] antenna selection strategies for MIMO-OFDM wireless systems are studied. Following the above studies, we study the Total power consumption of MIMO systems in the presence of fast and block Rayleigh fading channels. ...
In this article, a 4 × 4 miniaturized UWB-MIMO antenna with reduced isolation is designed and analyzed using a unique methodology known as characteristic mode analysis. To minimize the antenna’s physical size and to improve the isolation, an arrangement of four symmetrical radiating elements is positioned orthogonally. The antenna dimension is 40 mm × 40 mm (0.42λ0 × 0.42λ0) (λ0 is the wavelength at first lower frequency), which is printed on FR-4 material with a width of 1.6 mm and εr = 4.3. A square-shaped defected ground framework was placed on the ground to improve the isolation. Etching square-shaped slots on the ground plane achieved the return losses S11 < −10 dB and isolation 26 dB in the entire operating band 3.2 GHz–12.44 GHz (UWB (3.1–10.6 GHz) and X-band (8 GHz–12 GHz) spectrum and achieved good isolation bandwidth of 118.15%. The outcomes of estimated and observed values are examined for MIMO inclusion factors such as DG, ECC, CCL, and MEG. The antenna’s performances, including radiation efficiency and gain, are remarkable for this antenna design. The designed antenna is successfully tested in a cutting-edge laboratory. The measured outcomes are quite similar to the modeled outcomes. This antenna is ideal for WLAN and Wi-Max applications.
Over recent epoch, initial uplink synchronization has become an essential part of the wireless communication systems owing to its amenities in the identification of new users to originate communication. Yet, allocating and sharing resources to users is a bottleneck due to the interference caused by multiple users. Besides, preceding works didn't concentrate on the usage of an effective mechanism to estimate the parameters of the received signal in the multiuser synchronization environment. These downsides affect the throughput and spectrum efficiency of the designed OFDMA system. To address these bottlenecks, this paper proposes the Joint Initial Uplink Synchronization and Interference Aware Resource Allocation (JIUS-IRA) in the Multi-User OFDMA system. JIUS-IRA comprises four processes: Parameter Estimation, Optimum Antenna Selection, Resource Allocation, and Resource Sharing. Initially, JIUS-IRA executes the Fast Block Least Mean Square-based Parameters Estimation Scheme (FBLMS-PES) to estimate the user parameters. To reduce the power consumption during transmission between 5G MIMO base station and users, JIUS-IRA selects the optimal antenna for transmission. The Sign Rank Oriented Resource Allocation (SO-RA) method is executed to allocate sub-channel resources to the cellular user. The resource requirement of D2D users present in the OFDMA system is resolved via the Harris Hawks Optimizer based Resource Sharing Scheme (H2ORSS). The numerical results acquired from the simulation are highly confidential with regard to metrics Root Mean Square Error (RMSE) of timing estimation (∼0.006), RMSE of power estimation (∼0.0079), RMSE of frequency estimation (∼ 0.008), Throughput (∼95%), Spectrum Efficiency (∼11.9 bps), and Complexity (0.045 × 10⁴).
