Throughput analysis for cognitive radio networks with multiple primary users and imperfect spectrum sensing

In cognitive radio networks, the licensed frequency bands of the primary users (PUs) are available to the secondary user (SU) provided that they do not cause significant interference to the PUs. In this study, the authors analysed the normalised throughput of the SU with multiple PUs coexisting under any frequency division multiple access communication protocol. The authors consider a cognitive radio transmission where the frame structure consists of sensing and data transmission slots. In order to achieve the maximum normalised throughput of the SU and control the interference level to the legal PUs, the optimal frame length of the SU is found via simulation. In this context, a new analytical formula has been expressed for the achievable normalised throughput of SU with multiple PUs under prefect and imperfect spectrum sensing scenarios. Moreover, the impact of imperfect sensing, variable frame length of SU and the variable PU traffic loads, on the normalised throughput has been critically investigated. It has been shown that the analytical and simulation results are in perfect agreement. The authors analytical results are much useful to determine how to select the frame duration length subject to the parameters of cognitive radio network, such as network traffic load, achievable sensing accuracy and number of coexisting PUs

Asymptotic Analysis of RZF in Large-Scale MU-MIMO Systems over Rician Channels

In this paper, we focus on the downlink ergodic sum rate of a single-cell large-scale multiuser MIMO system in which the base station employs $N$ antennas to communicate with $K$ single-antenna user equipments (UEs). A regularized zero-forcing (RZF) scheme is used for precoding under the assumption that each UE uses a specific power and each link forms a spatially correlated MIMO Rician fading channel. The analysis is conducted assuming that $N$ and $K$ grow large with a given ratio and perfect channel state information is available at the base station. New results from random matrix theory and large system analysis are used to compute an asymptotic expression of the signal-to-interference-plus-noise ratio as a function of system parameters, spatial correlation matrix, and Rician factor. Numerical results are used to validate the accuracy of asymptotic approximations in the finite system regime and to evaluate the performance under different operating conditions. It turns out that the asymptotic expressions provide accurate approximations even for relatively small values of $N$ and $K$

Recycling cellular downlink energy for overlay self-sustainable IoT networks

This paper investigates the self-sustainability of an overlay Internet of Things (IoT) network that relies on harvest- ing energy from a downlink cellular network. Using stochastic geometry and queueing theory, we develop a spatiotemporal model to derive the steady state distribution of the number of packets in the bu ff ers and energy levels in the batteries of IoT devices given that the IoT and cellular communications are allocated disjoint spectrum. Particularly, each IoT device is modeled via a two-dimensional discrete-time Markov Chain (DTMC) that jointly tracks the evolution of data bu ff er and energy battery. In this context, stochastic geometry is used to derive the energy generation at the batteries and the packet transmission probability from bu ff ers taking into account the mutual interference from other active IoT devices. To this end, we show the Pareto-Frontiers of the sustainability region, which defines the network parameters that ensure stable network operation and finite packet delay. The results provide several insights to design self-sustainable IoT networks. Index Terms —Spatiotemporal models, stochastic geometry, queuing theory, energy harvesting, packet transmission success probability, two-dimensional discrete-time Markov chain, sta- bility conditions

Half-Duplex and Full-Duplex AF and DF Relaying with Energy-Harvesting in Log-Normal Fading

Energy-harvesting (EH) and wireless power transfer in cooperative relaying networks have recently attracted a considerable amount of research attention. Most of the existing work on this topic however focuses on Rayleigh fading channels, which represent outdoor environments. In contrast, this paper is dedicated to analyze the performance of dual-hop relaying systems with EH over indoor channels characterized by log-normal fading. Both half-duplex (HD) and full-duplex (FD) relaying mechanisms are studied in this work with decode-and-forward (DF) and amplify-and-forward (AF) relaying protocols. In addition, three EH schemes are investigated, namely, time switching relaying, power splitting relaying and ideal relaying receiver which serves as a lower bound. The system performance is evaluated in terms of the ergodic outage probability for which we derive accurate analytical expressions. Monte Carlo simulations are provided throughout to validate the accuracy of our analysis. Results reveal that, in both HD and FD scenarios, AF relaying performs only slightly worse than DF relaying which can make the former a more efficient solution when the processing energy cost at the DF relay is taken into account. It is also shown that FD relaying systems can generally outperform HD relaying schemes as long as the loop-back interference in FD is relatively small. Furthermore, increasing the variance of the log-normal channel has shown to deteriorate the performance in all the relaying and EH protocols considered

Opportunistic Scheduling with Quantized Feedback in Wireless Networks

Wireless scheduling algorithm can extract multiuser diversity (MUDiv) via prioritizing the users with best current channel condition. One drawback of MUDiv is the required feedback carrying the instantiations channel rate from all active users to the access point base station. This paper shows that this feedback load is, for the most part, unjustified. To alleviate this problem, we propose an optimal discrete rate switch-based multi-user diversity system (DSMUDiv) that allows reducing the feedback load while preserving the essential of the scheme performance. We examine DSMUDiv scheme using an absolute signal-to-noise ratio (SNR)-based scheduling mechanism, assuming all users are independent identical distributed (i.i.d.). We provide a theoretical analysis of the feedback load and the spectral efficiency for the DSMUDiv scheme and compare it with the optimal (full feedback load) selective diversity scheme. Slow Rayleigh fading is assumed. Our results show a reduction in the feedback load