Two dimensional quantum and reliability modelling for lightly doped nanoscale devices

The downscaling of MOSFET devices leads to well-studied short channel effects and more complex quantum mechanical effects. Both quantum and short channel effects not only alter the performance but they also affect the reliability. This continued scaling of the MOS device gate length puts a demand on the reduction of the gate oxide thickness and the substrate doping density. Quantum mechanical effects give rise to the quantization of energy in the conduction band, which consequently creates a larger effective bandgap and brings a displacement of the inversion layer charge out of the Si/SiO2 interface. Such a displacement of charge is equivalent to an increase in the effective oxide layer thickness, a growth in the threshold voltage, and a decrease in the current level. Therefore, using the classical analysis approach without including the quantum effects may lead to perceptible errors in the prognosis of the performance of modern deep submicron devices. In this work, compact Verilog-A compatible 2D models including quantum short channel effects and confinement for the potential, threshold voltage, and the carrier charge sheet density for symmetrical lightly doped double-gate MOSFETs are developed. The proposed models are not only applicable to ultra-scaled devices but they have also been derived from analytical 2D Poisson and 1D Schrodinger equations including 2D electrostatics, in order to incorporate quantum mechanical effects. Electron and hole quasi-Fermi potential effects were considered. The models were further enhanced to include negative bias temperature instability (NBTI) in order to assess the reliability of the device. NBTI effects incorporated into the models constitute interface state generation and hole-trapping. The models are continuous and have been verified by comparison with COMSOL and BALMOS numerical simulations for channel lengths down to 7nm; very good agreement within ±5% has been observed for silicon thicknesses ranging from 3nm to 20nm at 1 GHz operation after 10 years

Edge Caching in Dense Heterogeneous Cellular Networks with Massive MIMO Aided Self-backhaul

This paper focuses on edge caching in dense heterogeneous cellular networks (HetNets), in which small base stations (SBSs) with limited cache size store the popular contents, and massive multiple-input multiple-output (MIMO) aided macro base stations provide wireless self-backhaul when SBSs require the non-cached contents. Our aim is to address the effects of cell load and hit probability on the successful content delivery (SCD), and present the minimum required base station density for avoiding the access overload in an arbitrary small cell and backhaul overload in an arbitrary macrocell. The massive MIMO backhaul achievable rate without downlink channel estimation is derived to calculate the backhaul time, and the latency is also evaluated in such networks. The analytical results confirm that hit probability needs to be appropriately selected, in order to achieve SCD. The interplay between cache size and SCD is explicitly quantified. It is theoretically demonstrated that when non-cached contents are requested, the average delay of the non-cached content delivery could be comparable to the cached content delivery with the help of massive MIMO aided self-backhaul, if the average access rate of cached content delivery is lower than that of self-backhauled content delivery. Simulation results are presented to validate our analysis.Comment: Accepted to appear in IEEE Transactions on Wireless Communication

Modeling and Simulation of Molecular Communication Systems with a Reversible Adsorption Receiver

In this paper, we present an analytical model for the diffusive molecular communication (MC) system with a reversible adsorption receiver in a fluid environment. The widely used concentration shift keying (CSK) is considered for modulation. The time-varying spatial distribution of the information molecules under the reversible adsorption and desorption reaction at the surface of a receiver is analytically characterized. Based on the spatial distribution, we derive the net number of newly-adsorbed information molecules expected in any time duration. We further derive the number of newly-adsorbed molecules expected at the steady state to demonstrate the equilibrium concentration. Given the number of newly-adsorbed information molecules, the bit error probability of the proposed MC system is analytically approximated. Importantly, we present a simulation framework for the proposed model that accounts for the diffusion and reversible reaction. Simulation results show the accuracy of our derived expressions, and demonstrate the positive effect of the adsorption rate and the negative effect of the desorption rate on the error probability of reversible adsorption receiver with last transmit bit-1. Moreover, our analytical results simplify to the special cases of a full adsorption receiver and a partial adsorption receiver, both of which do not include desorption.Comment: 14 pages, 8 figures, 1 algorithm, submitte

Joint Transmit Power and Placement Optimization for URLLC-enabled UAV Relay Systems

This letter considers an unmanned aerial vehicle (UAV)-enabled relay communication system for delivering latency-critical messages with ultra-high reliability, where the relay is operating under amplifier-and-forward (AF) mode. We aim to jointly optimize the UAV location and power to minimize decoding error probability while guaranteeing the latency constraints. Both the free-space channel model and three-dimensional (3-D) channel model are considered. For the first model, we propose a low-complexity iterative algorithm to solve the problem, while globally optimal solution is derived for the case when the signal-to-noise ratio (SNR) is extremely high. For the second model, we also propose a low-complexity iterative algorithm to solve the problem. Simulation results confirm the performance advantages of our proposed algorithms

Safeguarding Massive MIMO Aided HetNets Using Physical Layer Security

This paper exploits the potential of physical layer security in massive multiple-input multiple-output (MIMO) aided two-tier heterogeneous networks (HetNets). We focus on the downlink secure transmission in the presence of multiple eavesdroppers. We first address the impact of massive MIMO on the maximum receive power based user association. We then derive the tractable upper bound expressions for the secrecy outage probability of a HetNets user.We show that the implementation of massive MIMO significantly improves the secrecy performance, which indicates that physical layer security could be a promising solution for safeguarding massive MIMO HetNets. Furthermore, we show that the secrecy outage probability of HetNets user first degrades and then improves with increasing the density of PBSs

Multicell MIMO Communications Relying on Intelligent Reflecting Surfaces

Intelligent reflecting surfaces (IRSs) constitute a disruptive wireless communication technique capable of creating a controllable propagation environment. In this paper, we propose to invoke an IRS at the cell boundary of multiple cells to assist the downlink transmission to cell-edge users, whilst mitigating the inter-cell interference, which is a crucial issue in multicell communication systems. We aim for maximizing the weighted sum rate (WSR) of all users through jointly optimizing the active precoding matrices at the base stations (BSs) and the phase shifts at the IRS subject to each BS’s power constraint and unit modulus constraint. Both the BSs and the users are equipped with multiple antennas, which enhances the spectral efficiency by exploiting the spatial multiplexing gain. Due to the nonconvexity of the problem, we first reformulate it into an equivalent one, which is solved by using the block coordinate descent (BCD) algorithm, where the precoding matrices and phase shifts are alternately optimized. The optimal precoding matrices can be obtained in closed form, when fixing the phase shifts. A pair of efficient algorithms are proposed for solving the phase shift optimization problem, namely the Majorization-Minimization (MM) Algorithm and the Complex Circle Manifold (CCM) Method. Both algorithms are guaranteed to converge to at least locally optimal solutions. We also extend the proposed algorithms to the more general multiple-IRS and network MIMO scenarios. Finally, our simulation results confirm the advantages of introducing IRSs in enhancing the cell-edge user performance