Outage Constrained Design in NOMA-Based D2D Offloading Systems

Non-orthogonal multiple access (NOMA) is a new multiple access method that has been considered in 5G cellular communications in recent years, and can provide better throughput than traditional orthogonal multiple access (OMA) to save communication bandwidth. Device-to-device (D2D) communication, as a key technology of 5G, can reuse network resources to improve the spectrum utilization of the entire communication network. Combining NOMA technology with D2D is an effective solution to improve mobile edge computing (MEC) communication throughput and user access density. Considering the estimation error of channel, we investigate the power of the transmit nodes optimization problem of NOMA-based D2D networks under the rates outage probability (OP) constraints of all single users. Specifically, under the channel statistical error model, the total system transmit power is minimized with the rate OP constraint of a single device. Unfortunately, the problem presented is thorny and non-convex. After equivalent transformation of the rate OP constraints by the Bernstein inequality, an algorithm based on semi-definite relaxation (SDR) can efficiently solve this challenging non-convex problem. Numerical results show that the channel estimation error increases the power consumption of the system. We also compare NOMA with the OMA mode, and the numerical results show that the D2D offloading systems based on NOMA are superior to OMA.

Interference Suppression in Heterogeneous Massive MIMO Systems with Imperfect CSI

Interference management is of paramount importance in heterogeneous massive mimo networks (HetNet). In this paper, an algorithm has been suggested to suppress the interference in large-MIMO HetNets with imperfect channel state information(CSI). The proposed technique controls both the intra-tier and cross-tier interference of the macrocell as well as the small cells. The intra-tier interference of the macrocell as well as the cross-tier interference have been minimized under maximum transmission power and minimum signal to interference and noise ratio (SINR) constraint. The channel estimation error matrix has also been modeled using the joint sparsity property. The precoding algorithm is thus achieved through the application of semi-definite relaxation and block coordinate descent techniques. The intra-tier interference of the small cells are addressed with the aid of the zero forcing scheme. The proposed method has been validated through various simulations which confirm the superiority of the algorithm over its counterparts.

Channel Estimation for Large Intelligent Surface-Based Transceiver Using a Parametric Channel Model

<div>Large intelligent surface-based transceivers (LISBTs), in which a spatially continuous surface is being used for signal transmission and reception, have emerged as a promising solution for improving the coverage and data rate of wireless communication systems. To realize these objectives, the acquisition of accurate channel state information (CSI) in LISBT-assisted wireless communication systems is crucial. In this paper, we propose a channel estimation scheme based on a parametric physical channel model for line-of-sight dominated communication in millimeter and terahertz wave bands. The proposed estimation scheme requires only five pilot signals to perfectly estimate the channel parameters assuming there is no noise at the receiver. In the presence of noise, we propose an iterative estimation algorithm that decreases the channel estimation error due to noise. The training overhead and computational cost of the proposed scheme do not scale with the number of antennas. The simulation results demonstrate that the proposed estimation scheme significantly outperforms other benchmark schemes.</div>

Channel Estimation for Large Intelligent Surface-Based Transceiver Using a Parametric Channel Model

<div>Large intelligent surface-based transceivers (LISBTs), in which a spatially continuous surface is being used for signal transmission and reception, have emerged as a promising solution for improving the coverage and data rate of wireless communication systems. To realize these objectives, the acquisition of accurate channel state information (CSI) in LISBT-assisted wireless communication systems is crucial. In this paper, we propose a channel estimation scheme based on a parametric physical channel model for line-of-sight dominated communication in millimeter and terahertz wave bands. The proposed estimation scheme requires only five pilot signals to perfectly estimate the channel parameters assuming there is no noise at the receiver. In the presence of noise, we propose an iterative estimation algorithm that decreases the channel estimation error due to noise. The training overhead and computational cost of the proposed scheme do not scale with the number of antennas. The simulation results demonstrate that the proposed estimation scheme significantly outperforms other benchmark schemes.</div>

Performance Analysis of Intelligent Reflecting Surface-Assisted Multi-Users Communication Networks

An intelligent reflecting surface (IRS) is an array that consists of a large number of passive reflecting elements. Such a device possesses the potential to extend the coverage of transmission in future communication networks by overcoming the effects of non line-of-sight propagation. Accordingly, to present the case for utilizing IRS panels in future wireless networks, in this paper, we analyze a multi-user downlink network aided by IRS. In particular, by using a realistic 5G channel model, we compare the performance of the IRS-aided network with a decode and forward (DF) relay-aided scenario and a network without IRS or relay. Our analysis revealed the following: (i) At best, communication aided by a DF relay with perfect channel state information (CSI) could match the performance of the IRS-aided network with imperfect CSI when the channel estimation error was high and the number of users was large. (ii) IRS-aided communication outright outperformed the DF relay case when the transmit power was high or the number of users in the network was low. (iii) Increasing the number of elements in an IRS translated to greater quality of service for the users. (iv) IRS-aided communication showed better energy efficiency compared with the other two scenarios for higher quality of service requirements.

Implementation of Underground Water for Wireless Optical Communication System using CDMA

Optical wireless communications is a powerful and cost-effective approach for high-speed wireless links that have been tightly guarded For underwater optical wireless communication, the following three optical code division multiple access (CDMA) techniques have been used. systems are associated, investigated, and presented in this paper, such as AC-biased optical CDMA (ACO-CDMA), symmetrically-SCO-OFDM (clipped optical OFDM), and unipolar CDMA (U-CDMA). Peak power constraints, light source bandwidth tag, there are so many factors to recognize, such turbulence, fading underwater signals, and channel estimation error. Advocate for a bit loading algorithm and a simplified modulation index that determines signal magnitude is being used to minimize the achievable data propagation distance. In this optimization procedure, the signal-to-noise ratio and the clipping distortion triggered by the peak power limitation are balanced (SNR). The SNR and clipping effects of the three compared CDMA techniques are represented in this paper. When the transmitted bit index is greater than the channel bandwidth, ACO-OFDM outperforms SCO- and UCDMA, according to the determined model. U-CDMA, on the other end, has a longer propagation distance but needs less transmitted power.