Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks

Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843

Sparse Array Architectures for Wireless Communication and Radar Applications

This thesis focuses on sparse array architectures for the next generation of wireless communication, known as fifth-generation (5G), and automotive radar direction-of-arrival (DOA) estimation. For both applications, array spatial resolution plays a critical role to better distinguish multiple users/sources. Two novel base station antenna (BSA) configurations and a new sparse MIMO radar, which both outperform their conventional counterparts, are proposed.\ua0We first develop a multi-user (MU) multiple-input multiple-output (MIMO) simulation platform which incorporates both antenna and channel effects based on standard network theory. The combined transmitter-channel-receiver is modeled by cascading Z-matrices to interrelate the port voltages/currents to one another in the linear network model. The herein formulated channel matrix includes physical antenna and channel effects and thus enables us to compute the actual port powers. This is in contrast with the assumptions of isotropic radiators without mutual coupling effects which are commonly being used in the Wireless Community.\ua0Since it is observed in our model that the sum-rate of a MU-MIMO system can be adversely affected by antenna gain pattern variations, a novel BSA configuration is proposed by combining field-of-view (FOV) sectorization, array panelization and array sparsification. A multi-panel BSA, equipped with sparse arrays in each panel, is presented with the aim of reducing the implementation complexities and maintaining or even improving the sum-rate.\ua0We also propose a capacity-driven array synthesis in the presence of mutual coupling for a MU-MIMO system. We show that the appearance of\ua0grating lobes is degrading the system capacity and cannot be disregarded in a MU communication, where space division\ua0multiple access (SDMA) is applied. With the aid of sparsity and aperiodicity, the adverse effects of grating lobes and mutual coupling\ua0are suppressed and capacity is enhanced. This is performed by proposing a two-phase optimization. In Phase I, the problem\ua0is relaxed to a convex optimization by ignoring the mutual coupling and weakening the constraints. The solution of Phase I\ua0is used as the initial guess for the genetic algorithm (GA) in phase II, where the mutual coupling is taken into account. The\ua0proposed hybrid algorithm outperforms the conventional GA with random initialization.\ua0A novel sparse MIMO radar is presented for high-resolution single snapshot DOA estimation. Both transmit and receive arrays are divided into two uniform arrays with increased inter-element spacings to generate two uniform sparse virtual arrays. Since virtual arrays are uniform, conventional spatial smoothing can be applied for temporal correlation suppression among sources. Afterwards, the spatially smoothed virtual arrays satisfy the co-primality concept to avoid DOA ambiguities. Physical antenna effects are incorporated in the received signal model and their effects on the DOA estimation performance are investigated

Reduced complexity multicast beamforming and group assignment schemes for multi-antenna coded caching

Abstract. In spite of recent advancements in wireless communication technologies and data delivery networks, it is unlikely that the speeds supported by these networks will be able to keep up with the exponentially increasing demand caused by the widespread adoption of high-speed and large-data applications. One appealing idea proposed to address this issue is coded caching, which is an innovative data delivery technique that makes use of the network’s aggregate cache rather than the individual memory available to each user. This proposed idea of coded caching helps boost the data rates by distributing cache material throughout the network and delivering independent content to many users at a time. Despite the original theoretical promises for large caching gains, in reality, coded caching suffers from severe bottlenecks that dramatically limit these gains. Some of these bottlenecks are requiring complex successive interference cancellation (SIC) at the receiver, exponential increase in subpacketization, applicability to a limited range of input parameters, and performance losses in low- and mid- signal to noise ratio (SNR) regimes. In this study, we present a novel coded caching scheme based on user grouping for cache-aided multi-input single-output (MISO) networks. One special property of this new scheme is its applicability to every set of input values for the user count ($K$), transmitter-side antenna count ($L$), and the global coded caching gain ($t$). Moreover, for a fixed $t$, this scheme can achieve theoretical sum-DoF optimality with no limitations. This strategy yields superior performance in terms of subpacketization when input parameters satisfy $\frac{t+L}{t+1} \in \mathbb{N}$. This performance boost is enabled by the underlying user grouping structure during data delivery. However, when input parameters do not comply with $\frac{t+L}{t+1}$ $\in \mathbb{N}$, in order to guarantee symmetry of the scheme and optimal DoF, multicast and unicast messages need to be constructed using a tree diagram, resulting in excess subpacketization and transmission count. Nevertheless, the simple receiver structure without the SIC requirement not only simplifies the implementation complexity but also enables us to use state-of-the-art methods to readily design optimized transmit beamformers maximizing the achievable symmetric rate. Finally, we use numerical analysis to compare our new proposed scheme with well-known coded caching schemes in the literature

Development of antenna arrays for terrestrial and satellite applications: Feasibility study of different solutions to monitoring the atmospheric pollution, determination of electromagnetic fields in urban scenario and calculation of their dosimetry in small animals

The present work can be summarized as it follows: First of all, it will be held theoretical and numerical studies to improve the performance of antenna arrays by focusing on the isophoric case. Then, different antenna designs are shown and discussed, in order to be integrated within the urban environment. Some of these designs are experimentally tested. On the other hand, a study on the characterization of the electromagnetic fields through urban areas based on an equivalent planar circuit model is highlighted. Moreover and lastly, the influence of the electromagnetic fields in small animals is discussed by using two methods for the SAR level determination