Performance analysis of LTE physical layer using hardware cosimulation techniques and implementation on FPGA for communication systems

Abstract

The recent mobile networks provide large data access using long-term evolution networks. Long-term evolution networks are a third-generation partnership project standard that provides different speed limits for uplink and downlink. The different network operators have different bandwidth requirements to provide different services. Long-term evolution improves the efficiency of the network. The analysis of long-term evolution is performed using different signal processing algorithms that require a realistic, flexible, and standard compliant simulation environment. This study emphasizes to measure the performance of long-term evolution downlink and uplink physical layer based on Release 11, 12, and 13. The analysis of orthogonal frequency division multiple access for downlink and single-carrier frequency division multiplexing access for uplink using different modulation schemes like quadrature amplitude modulation (4, 16, 64) and different antenna configurations in long-term evolution physical layer is analyzed using hardware cosimulation platform.

CapsNet‐based computing in cognitive communications

“…The approach is based on training machine learning models with energy vectors in presence and absence of PUs. “Optimal Handover Scheme for Device‐to‐device Communication in Highly Mobile LTE HetNets”—Authored by C G , Balaji; Varghese , Nidhia; K , Murugan: The proposed [8] optimal D2D HO scheme tries to improve the duration of D2D communication by considering not only the signal quality between the D2D UE pairs but also the distance between them. The simulation results show that the proposed scheme improves the D2D mode duration, even in high mobility, thereby reducing frequent HO of the D2D UE, which is in D2D communication. “Performance Analysis of LTE Physical layer using Hardware Co‐simulation Techniques in Cognitive Communication Systems”—Authored by V , Venkataramanan; S , Lakshmi : This research study [9] emphasizes to measure the performance of long‐term evolution downlink and uplink physical layer based on Release 11, 12, and 13. The analysis of orthogonal frequency division multiple access for downlink and single‐carrier frequency division multiplexing access for uplink using different modulation schemes like quadrature amplitude modulation (4, 16, 64) and different antenna configurations in long‐term evolution physical layer is analyzed using hardware co‐simulation platform. “Design of a compact T‐shaped Slot Antenna for Wireless Applications”—Authored by C , Thiripurasundari; M , Mahadevi; V , Sumathy; C , Thiruvengadam: The proposed system [10] (antenna) has a dielectric substrate material and radiating patch (T‐shaped) with an inverted‐L slot (both left and right sides of the feed), circle slot, and comb‐shaped ground structure on the back of the substrate.…”

Hardware software SoC co‐design analysis and implementation of MIMO‐OFDM for 4G/5G/6G eNodeB applications

“…When compared to the literature with 49,83–89 and optical systems, 90–92 Table 21 indicates that the findings obtained are suitable for system designs to achieve high data rates from 10.9 Gbps to 50 Gbps with a BER of 10 −3 to 10 −4 . The suggested technique describes MIMO‐OFDM programmable and reconfigurable co‐design, simulation, and implementation using a model‐based and SoC platform with computer architecture performances that are PS, Mali‐400 GPU, and Programmable Logic (PL).…”

“…When compared to the literature with 49,[83][84][85][86][87][88][89] and optical systems, [90][91][92] Table 21 indicates that the findings obtained are suitable for system designs to achieve high data rates from 10.9 Gbps to 50 Gbps with a BER of 10 83 MIMO-OFDM has a data rate of 1347.2 Mbps, or 1 Gbps, and uses a Simulink implementation on an FPGA implementation. 84 Kilaru implemented a MISO OFDM system with a 100 Mbps data throughput and a BER of 10 −4 at an SNR of 18 dB.…”

“…The design implementation is static, fine-grained, and lacks clarity. 87 Fadhil developed OFDM with QPSK and 2048-point FFT on the FPGA Spartan 3 xc3s200 with a static design and fine grain architecture. The design implementation is lacking clarity on the hardware design.…”

“…Venkataramanan and Lakshmi used the OFDM with 16 QAM and 64‐FFT using a FPGA Spartan xc5slx45 with 210 ms timing. The design implementation is static, fine‐grained, and lacks clarity 87 . Fadhil developed OFDM with QPSK and 2048‐point FFT on the FPGA Spartan 3 xc3s200 with a static design and fine grain architecture.…”