This paper studies the detection problem for the Gaussian random access channels, in which only a randomly chosen αK out of K senders wish to convey their messages to a receiver that has the side information of which sender is actively transmitting. A novel coding scheme, referred to as L-interleaved block coding, based on interleaving L single-user codes and successive cancellation decoding is proposed for the symmetric rate tuples in the capacity region of this channel. L-interleaved block coding with L sufficiently large is shown to achieve arbitrarily close to the symmetric capacity. Therefore, it replaces the efforts of finding capacity achieving codes for the Gaussian random access channels with selecting L off-the-shelf codes for Gaussian point-to-point channels for L sufficiently large. An example illustrates that this scheme with a small number of blocks (L = 16) achieves more than 0.95 of the symmetric capacity when two senders are active.

The increasing number of connected vehicles in densely populated urban areas provides an interesting opportunity to counteract the high wireless data demands in high density and highly mobile scenarios. The idea is to support the macro base station (BS) with a secondary communication tier composed of a set of smart and connected vehicles that are in movement in the urban area. As a first step towards a comprehensive cost-benefit analysis of this architecture, this paper considers the case where these vehicles are equipped with femto-mobile Access Points (fmAPs) and constitute a mobile out-of-band relay infrastructure. In particular, three techniques to select an fmAP (if more than one is available) are proposed and the maximal feasible gain in the data rate is characterized as a function of the vehicle density, average vehicle speeds, handoff overhead cost, as well as physical layer parameters. The analytical and simulation results provide a first benchmark characterizing this architecture and the definition of guidelines for its future realistic study and implementation.

A novel architecture for the future data center networks with possibly up to a thousand of Top of the Rack (ToR) switches is proposed. The proposed architecture, WiCOD, relies on a wireless control plane serving an all-optical data plane. The first contribution of the work is the separation of the data and the control planes: while the data is switched between the ToR switches in an all-optical high rate network, the network state and control information is continuously conveyed to and from a central unit over an ultra low-latency wireless network. A proof of concept for this architecture is also presented by considering the initial design possibilities for each one of the planes. In order to obtain low packet delays, the data plane scheduling policies take non-zero reconfiguration and monitoring delays into consideration. The results prove that very low queueing delays are guaranteed for strictly frequent updates on the network state. Based on this observation, a technique for monitoring of ToR switch queue occupancy information is purposed. This monitoring technique uses mmWave wireless communications via a spatially adapted MIMO Orthogonal Frequency Division Multiple Access (MIMO-OFDMA) over a static frequency selective channel with large number of densely packed ToRs. The reduced monitoring delays, offered by this low-latency radio access technology, makes the fine-grained and adaptive circuit switching feasible and, in turn, enables a high utilization of optical switches.

In-network queuing in the Internet-style networks enables the distributed operation and scalability across the network at the cost of excessive delay and tardy flow completion times. Data center networking, in contrast, are proposed to depart from this classical approach and avoid in-network queuing all together. In this new class of network solutions serving interdata center traffic, a densely packed fairly local area network of stationary end hosts are often managed by a single entity, allowing for fine-grained management and scheduling of flows across the data center. The overall objective of this work is to develop a framework, from first principles, which relies on the unique attributes of data centers to propose a transformative novel networking architecture with increased level of efficiency and significantly smaller latency. By separating the control and data planes, the proposed hybrid architecture avoids in-network queuing and results in significantly lower delay. The critical technical challenge is to design endend circuit switching mechanisms that account for monitoring as well as circuit reconfiguration delays. Furthermore, the design has to minimize the computational complexity of the scheduling algorithm as well as the cost of monitoring across the network. In this context, this paper underlines a family of recent technologies and networking advances as promising enablers and discusses the most significant set of challenges.

We propose a low complexity graph-based linear minimum mean square error (LMMSE) equalizer which considers both the intersymbol interference (ISI) and the effect of non-white noise inherent in Faster-than-Nyquist (FTN) signaling. In order to incorporate the statistics of noise signal into the factor graph over which the LMMSE algorithm is implemented, we suggest a method that models it as an autoregressive (AR) process. Furthermore, we develop a new mechanism for exchange of information between the proposed equalizer and the channel decoder through turbo iterations. Based on these improvements, we show that the proposed low complexity receiver structure performs close to the optimal decoder operating in ISI-free ideal scenario without FTN signaling through simulations.

This paper extends some approximation methods that are used to identify closed form Bit Error Rate (BER) expressions which are frequently utilized in investigation and comparison of performance for wireless communication systems in the literature. By using this group of approximation methods, some expectation integrals, whose exact analyses are intractable and whose Monte Carlo simulation computations have high complexity, can be computed. For these integrals, by using the sampling property of the integrand functions of one or more arguments, reliable BER expressions revealing the diversity and coding gains are derived. Although the methods we present are valid for a larger class of integration problems, in this work we illustrate the method by showing the step by step derivation of the BER expressions for a canonical cooperative communication scenario as well as a network coded system scenario. The derived expressions agree with the simulation results for a very wide range of signal-to-noise ratio (SNR) values.

We propose a simple yet effective wireless network coding and decoding technique for a multiple unicast network. It utilizes spatial diversity through cooperation between nodes which carry out distributed encoding operations dictated by generator matrices of linear block codes. In order to exemplify the technique, we make use of greedy codes over the binary field and show that the arbitrary diversity orders can be flexibly assigned to nodes. Furthermore, we present the optimal detection rule for the given model that accounts for intermediate node errors and suggest a low-complexity network decoder using the sum-product (SP) algorithm. The proposed SP detector exhibits near optimal performance. We also show asymptotic superiority of network coding over a method that utilizes the wireless channel in a repetitive manner without network coding (NC) and give related rate-diversity trade-off curves. Finally, we extend the given encoding method through selective encoding in order to obtain extra coding gains.

We propose a simple yet effective wireless network coding (NC) and decoding technique. It utilizes spatial diversity through cooperation between nodes which carry out distributed encoding operations dictated by generator matrices of linear block codes. For this purpose, we make use of greedy codes over the binary field and show that desired diversity orders can be flexibly assigned to nodes in a multiple unicast network, contrary to the previous findings in the literature. Furthermore, we present the optimal detection rule for the given model that accounts for intermediate node errors and suggest a network decoder using the sum-product algorithm. The proposed sum-product detector exhibits near optimal performance.

The case of rotation, in use together with coding in a channel with B fading blocks, is analyzed in terms of diversity properties of the coded systems with multi-dimensional rotated constellations (coded-rotated system) output. First closed-form expression obtained is related to the diversity performance of unrotated generic coding structures with given minimum distance, d, block length, and number of fading blocks. Afterwards, another closed-form expression is derived for distinguishing the effect of rotation applied on the given coding structures. This latter expression yields a strict lower bound on the probability of attaining full diversity for any coded-rotated system and gives us a tool to evaluate the improvement with respect to systems involving only coding and also systems with only rotation. The results shown summarize the benefits of utilizing rotation together with coding, even in the cases of very simple non-full-diversity rotations like DFT rotations.