Spatial networks with wireless applications

Many networks have nodes located in physical space, with links more common between closely spaced pairs of nodes. For example, the nodes could be wireless devices and links communication channels in a wireless mesh network. We describe recent work involving such networks, considering effects due to the geometry (convex,non-convex, and fractal), node distribution, distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina

Analysis of millimeter wave and massive MIMO cellular networks

Millimeter wave (mmWave) communication and massive multiple-input multiple-output (MIMO) are promising techniques to increase system capacity in 5G cellular networks. The prior frameworks for conventional cellular systems do not directly apply to analyze mmWave or massive MIMO networks, as (i) mmWave cellular networks differ in the different propagation conditions and hardware constraints; and (ii) with a order of magnitude more antennas than conventional multi-user MIMO systems, massive MIMO systems will be operated in time-division duplex (TDD) mode, which renders pilot contamination a primary limiting factor. In this dissertation, I develop stochastic geometry frameworks to analyze the system-level performance of mmWave, sub-6 GHz massive MIMO, and mmWave massive MIMO cellular networks. The proposed models capture the key features of each technique, and allow for tractable signal-to-interference-plus-noise ratio (SINR) and rate analyses. In the first contribution, I develop an mmWave cellular network model that incorporates the blockage effect and directional beamforming, and analyze the SINR and rate distributions as functions of the base station density, blockage parameters, and antenna geometry. The analytical results demonstrate that with a sufficiently dense base station deployment, mmWave cellular networks are capable to achieve comparable SINR coverage and much higher rates than conventional networks. In my second contribution, I analyze the uplink SINR and rate in sub-6 GHz massive MIMO networks with the incorporation of pilot contamination and fractional power control. Based on the analysis, I show scaling laws between the number of antennas and scheduled users per cell that maintain the uplink signal-to-interference ratio (SIR) distributions are different for maximum ratio combining (MRC) and zero-forcing (ZF) receivers. In my third contribution, I extend the sub-6 GHz massive MIMO model to mmWave frequencies, by incorporating key mmWave features. I leverage the proposed model to investigate the asymptotic SINR performance, when the number of antennas goes to infinity. Numerical results show that mmWave massive MIMO outperforms its sub-6 GHz counterpart in cell throughput with a dense base station deployment, while the reverse can be true with a low base station density.Electrical and Computer Engineerin

Connectivity vs Capacity in Dense Ad Hoc Networks

We study the connectivity and capacity of finite area ad hoc wireless networks, with an increasing number of nodes (dense networks). We find that the properties of the network strongly depend on the shape of the attenuation function. For power law attenuation functions, connectivity scales, and the available rate per node is known to decrease like 1/sqrt(n). On the contrary, if the attenuation function does not have a singularity at the origin and is uniformly bounded, we obtain bounds on the percolation domain for large node densities, which show that either the network becomes disconnected, or the available rate per node decreases like 1/n

Analysis of millimeter wave ad hoc networks

Over the coming few years, the next-generation of wireless networks will be standardized and defined. Ad hoc networks, which operate without expensive infrastructure, are desirable for use cases such as military networks or disaster relief. Millimeter wave (mmWave) technology may enable high speed ad hoc networks. Directional antennas and building blockage limit the received interference power while the huge bandwidth enables high data rates. For this reason, understanding the interference and network performance of mmWave ad hoc networks is crucial for next-generation network design. In my first contribution, I derive the SINR complementary cumulative distribution function (CCDF) for a random single-hop mmWave ad hoc network. These base results are used to further give insights in mmWave ad hoc networks. The SINR distribution is used to compute the transmission capacity of a mmWave ad hoc network using a Taylor bound. The CDF of the interference to noise ratio (INR) is also derived which shows that mmWave ad hoc networks are line-of-sight interference limited. I extend my work in the second contribution to include general clustered Poisson point processes to derive insights in the effect of different spatial interference patterns. Using the developed framework, I derive the ergodic rate of both spatially uniform and cluster mmWave ad hoc networks. I develop scaling trends for the antenna array size to keep the ergodic rate constant. The impact of beam alignment is computed in the final part of the contribution. Finally, I account for the overhead of beam alignment in mmWave ad hoc networks. The final contribution leverages the first two contributions to derive the expected training time a mmWave ad hoc network must perform before data transmission occurs. The results show that the optimal conditions for minimizing the training time are different than the optimal conditions for maximizing rate.Electrical and Computer Engineerin

Energy Efficient Massive MIMO and Beamforming for 5G Communications

Massive multiple-input multiple-output (MIMO) has been a key technique in the next generation of wireless communications for its potential to achieve higher capacity and data rates. However, the exponential growth of data traffic has led to a significant increase in the power consumption and system complexity. Therefore, we propose and study wireless technologies to improve the trade-off between system performance and power consumption of wireless communications. This Thesis firstly proposes a strategy with partial channel state information (CSI) acquisition to reduce the power consumption and hardware complexity of massive MIMO base stations. In this context, the employment of partial CSI is proposed in correlated communication channels with user mobility. By exploiting both the spatial correlation and temporal correlation of the channel, our analytical results demonstrate significant gains in the energy efficiency of the massive MIMO base station. Moreover, relay-aided communications have experienced raising interest; especially, two-way relaying systems can improve spectral efficiency with short required operating time. Therefore, this Thesis focuses on an uncorrelated massive MIMO two-way relaying system and studies power scaling laws to investigate how the transmit powers can be scaled to improve the energy efficiency up to several times the energy efficiency without power scaling while approximately maintaining the system performance. In a similar line, large antenna arrays deployed at the space-constrained relay would give rise to the spatial correlation. For this reason, this Thesis presents an incomplete CSI scheme to evaluate the trade-off between the spatial correlation and system performance. In addition, the advantages of linear processing methods and the effects of channel aging are investigated to further improve the relay-aided system performance. Similarly, large antenna arrays are required in millimeter-wave communications to achieve narrow beams with higher power gain. This poses the problem that locating the best beam direction requires high power and complexity consumption. Therefore, this Thesis presents several low-complexity beam alignment methods with respect to the state-of-the-art to evaluate the trade-off between complexity and system performance. Overall, extensive analytical and numerical results show an improved performance and validate the effectiveness of the proposed techniques

Asymptotic properties of wireless multi-hop networks

In this dissertation, we consider wireless multi-hop networks, where the nodes are randomly placed. We are particularly interested in their asymptotic properties when the number of nodes tends to infinity. We use percolation theory as our main tool of analysis. As a first model, we assume that nodes have a fixed connectivity range, and can establish wireless links to all nodes within this range, but no other (Boolean model). We compute for one-dimensional networks the probability that two nodes are connected, given the distance between them. We show that this probability tends exponentially to zero when the distance increases, proving that pure multi-hopping does not work in large networks. In two dimensions however, an unbounded cluster of connected nodes forms if the node density is above a critical threshold (super-critical phase). This is known as the percolation phenomenon. This cluster contains a positive fraction of the nodes that depends on the node density, and remains constant as the network size increases. Furthermore, the fraction of connected nodes tends rapidly to one when the node density is above the threshold. We compare this partial connectivity to full connectivity, and show that the requirement for full connectivity leads to vanishing throughput when the network size increases. In contrast, partial connectivity is perfectly scalable, at the cost of a tiny fraction of the nodes being disconnected. We consider two other connectivity models. The first one is a signal-to-interference- plus-noise-ratio based connectivity graph (STIRG). In this model, we assume deterministic attenuation of the signals as a function of distance. We prove that percolation occurs in this model in a similar way as in the previous model, and study in detail the domain of parameters where it occurs. We show in particular that the assumptions on the attenuation function dramatically impact the results: the commonly used power-law attenuation leads to particular symmetry properties. However, physics imposes that the received signal cannot be stronger than the emitted signal, implying a bounded attenuation function. We observe that percolation is harder to achieve in most cases with such an attenuation function. The second model is an information theoretic view on connectivity, where two arbitrary nodes are considered connected if it is possible to transmit data from one to the other at a given rate. We show that in this model the same partial connectivity can be achieved in a scalable way as in the Boolean model. This result is however a pure connectivity result in the sense that there is no competition and interferences between data flows. We also look at the other extreme, the Gupta and Kumar scenario, where all nodes want to transmit data simultaneously. We show first that under point-to-point communication and bounded attenuation function the total transport capacity of a fixed area network is bounded from above by a constant, whatever the number of nodes may be. However, if the network area increases linearly with the number of nodes (constant density), or if we assume power-law attenuation function, a throughput per node of order 1/√n can be achieved. This latter result improves the existing results about random networks by a factor (log n)1/2. In the last part of this dissertation, we address two problems related to latency. The first one is an intruder detection scenario, where a static sensor network has to detect an intruder that moves with constant speed along a straight line. We compute an upper bound to the time needed to detect the intruder, under the assumption that detection by disconnected sensors does not count. In the second scenario, sensors switch off their radio device for random periods, in order to save energy. This affects the delivery of alert messages, since they may have to wait for relays to turn on their radio to move further. We show that asymptotically, alert messages propagate with constant, deterministic speed in such networks

Nuts and Bolts of a Realistic Stochastic Geometric Analysis of mmWave HetNets: Hardware Impairments and Channel Aging

© 2019 IEEE.Motivated by heterogeneous network (HetNet) design in improving coverage and by millimeter-wave (mmWave) transmission offering an abundance of extra spectrum, we present a general analytical framework shedding light on the downlink of realistic mmWave HetNets consisting of K tiers of randomly located base stations. Specifically, we model, by virtue of stochastic geometry tools, the multi-Tier multi-user (MU) multiple-input multiple-output (MIMO) mmWave network degraded by the inevitable residual additive transceiver hardware impairments (RATHIs) and channel aging. Given this setting, we derive the coverage probability and the area spectral efficiency (ASE), and we subsequently evaluate the impact of residual transceiver hardware impairments and channel aging on these metrics. Different path-loss laws for line-of-sight and non-line-of-sight are accounted for the analysis, which are among the distinguishing features of mmWave systems. Among the findings, we show that the RATHIs have a meaningful impact at the high-signal-To-noise-ratio regime, while the transmit additive distortion degrades further than the receive distortion the system performance. Moreover, serving fewer users proves to be preferable, and the more directive the mmWaves are, the higher the ASE becomes.Peer reviewedFinal Accepted Versio