116 research outputs found

    Channel-Aware Random Access in the Presence of Channel Estimation Errors

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    In this work, we consider the random access of nodes adapting their transmission probability based on the local channel state information (CSI) in a decentralized manner, which is called CARA. The CSI is not directly available to each node but estimated with some errors in our scenario. Thus, the impact of imperfect CSI on the performance of CARA is our main concern. Specifically, an exact stability analysis is carried out when a pair of bursty sources are competing for a common receiver and, thereby, have interdependent services. The analysis also takes into account the compound effects of the multipacket reception (MPR) capability at the receiver. The contributions in this paper are twofold: first, we obtain the exact stability region of CARA in the presence of channel estimation errors; such an assessment is necessary as the errors in channel estimation are inevitable in the practical situation. Secondly, we compare the performance of CARA to that achieved by the class of stationary scheduling policies that make decisions in a centralized manner based on the CSI feedback. It is shown that the stability region of CARA is not necessarily a subset of that of centralized schedulers as the MPR capability improves.Comment: The material in this paper was presented in part at the IEEE International Symposium on Information Theory, Cambridge, MA, USA, July 201

    COOPERATIVE NETWORKING AND RELATED ISSUES: STABILITY, ENERGY HARVESTING, AND NEIGHBOR DISCOVERY

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    This dissertation deals with various newly emerging topics in the context of cooperative networking. The first part is about the cognitive radio. To guarantee the performance of high priority users, it is important to know the activity of the high priority communication system but the knowledge is usually imperfect due to randomness in the observed signal. In such a context, the stability property of cognitive radio systems in the presence of sensing errors is studied. General guidelines on controlling the operating point of the sensing device over its receiver operating characteristics are also given. We then consider the hybrid of different modes of operation for cognitive radio systems with time-varying connectivity. The random connectivity gives additional chances that can be utilized by the low priority communication system. The second part of this dissertation is about the random access. We are specifically interested in the scenario when the nodes are harvesting energy from the environment. For such a system, we accurately assess the effect of limited, but renewable, energy availability on the stability region. The effect of finite capacity batteries is also studied. We next consider the exploitation of diversity amongst users under random access framework. That is, each user adapts its transmission probability based on the local channel state information in a decentralized manner. The impact of imperfect channel state information on the stability region is investigated. Furthermore, it is compared to the class of stationary scheduling policies that make centralized decisions based on the channel state feedback. The backpressure policy for cross-layer control of wireless multi-hop networks is known to be throughput-optimal for i.i.d. arrivals. The third part of this dissertation is about the backpressure-based control for networks with time-correlated arrivals that may exhibit long-range dependency. It is shown that the original backpressure policy is still throughput-optimal but with increased average network delay. The case when the arrival rate vector is possibly outside the stability region is also studied by augmenting the backpressure policy with the flow control mechanism. Lastly, the problem of neighbor discovery in a wireless sensor network is dealt. We first introduce the realistic effect of physical layer considerations in the evaluation of the performance of logical discovery algorithms by incorporating physical layer parameters. Secondly, given the lack of knowledge of the number of neighbors along with the lack of knowledge of the individual signal parameters, we adopt the viewpoint of random set theory to the problem of detecting the transmitting neighbors. Random set theory is a generalization of standard probability theory by assigning sets, rather than values, to random outcomes and it has been applied to multi-user detection problem when the set of transmitters are unknown and dynamically changing

    Distributed Adaptive Algorithms for Optimal Opportunistic Medium Access

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    We examine threshold-based transmission strategies for distributed opportunistic medium access in a scenario with fairly general probabilistic interference conditions. Specifically, collisions between concurrent transmissions are governed by arbitrary probabilities, allowing for a form of channel capture and covering binary interference constraints as an important special case. We address the problem of setting the threshold values so as to optimize the aggregate throughput utility of the various users, and particularly focus on a weighted logarithmic throughput utility function (Proportional Fairness). We provide an adaptive algorithm for finding the optimal threshold values in a distributed fashion, and rigorously establish the convergence of the proposed algorithm under mild statistical assumptions. Moreover, we discuss how the algorithm may be adapted to achieve packet-level stability with only limited exchange of queue length information among the various users. We also conduct extensive numerical experiments to corroborate the theoretical convergence results.14 page(s

    Sparse Signal Processing Concepts for Efficient 5G System Design

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    As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will discribe applications of this sparse signal processing paradigm in MIMO random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces

    Low-latency Networking: Where Latency Lurks and How to Tame It

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    While the current generation of mobile and fixed communication networks has been standardized for mobile broadband services, the next generation is driven by the vision of the Internet of Things and mission critical communication services requiring latency in the order of milliseconds or sub-milliseconds. However, these new stringent requirements have a large technical impact on the design of all layers of the communication protocol stack. The cross layer interactions are complex due to the multiple design principles and technologies that contribute to the layers' design and fundamental performance limitations. We will be able to develop low-latency networks only if we address the problem of these complex interactions from the new point of view of sub-milliseconds latency. In this article, we propose a holistic analysis and classification of the main design principles and enabling technologies that will make it possible to deploy low-latency wireless communication networks. We argue that these design principles and enabling technologies must be carefully orchestrated to meet the stringent requirements and to manage the inherent trade-offs between low latency and traditional performance metrics. We also review currently ongoing standardization activities in prominent standards associations, and discuss open problems for future research

    The role of SIC on the design of next generation multiple access

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    The interplay of physical layer enhancements and classic random access protocols is the objective of this paper. Successive interference cancellation (SIC) is among the major enhancements of the physical layer. Considering the classic representatives of random access protocols, Slotted ALOHA and Channel Sensing Multiple Access (CSMA), we show that two regimes can be identified as a function of the communication link spectral efficiency. In case of high levels of spectral efficiency, multi-packet reception enabled by SIC is of limited benefit. Sum-rate performance is dominated by the effectiveness of the Medium Access Control (MAC) protocol. On the contrary, for low spectral efficiency levels, sum-rate performance is essentially dependent on physical layer SIC capability, while the MAC protocol has a marginal impact. Limitations due to transmission power dynamic range are shown to induce unfairness among nodes. However, the unfairness issue fades away when the system is driven to work around the sum-rate peak achieved for low spectral efficiency. This can also be confirmed by looking at Age of Information (AoI) metric. The major finding of this work is that SIC can boost performance, while still maintaining a fair sharing of the communication channel among nodes. In this regime, the MAC protocol appears to play a marginal role, while multi-packet reception endowed by SIC is prominent to provide high sum-rate, low energy consumption, and low AoI

    Throughput Maximization in Unmanned Aerial Vehicle Networks

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    The use of Unmanned Aerial Vehicles (UAVs) swarms in civilian applications such as surveillance, agriculture, search and rescue, and border patrol is becoming popular. UAVs have also found use as mobile or portable base stations. In these applications, communication requirements for UAVs are generally stricter as compared to conventional aircrafts. Hence, there needs to be an efficient Medium Access Control (MAC) protocol that ensures UAVs experience low channel access delays and high throughput. Some challenges when designing UAVs MAC protocols include interference and rapidly changing channel states, which require a UAV to adapt its data rate to ensure data transmission success. Other challenges include Quality of Service (QoS) requirements and multiple contending UAVs that result in collisions and channel access delays. To this end, this thesis aims to utilize Multi-Packet Reception (MPR) technology. In particular, it considers nodes that are equipped with a Successive Interference Cancellation (SIC) radio, and thereby, allowing them to receive multiple transmissions simultaneously. A key problem is to identify a suitable a Time Division Multiple Access (TDMA) transmission schedule that allows UAVs to transmit successfully and frequently. Moreover, in order for SIC to operate, there must be a sufficient difference in received power. However, in practice, due to the location and orientation of nodes, the received power of simultaneously transmitting nodes may cause SIC decoding to fail at a receiver. Consequently, a key problem concerns the placement and orientation of UAVs to ensure there is diversity in received signal strength at a receiving node. Lastly, interference between UAVs serving as base station is a critical issue. In particular, their respective location may have excessive interference or cause interference to other UAVs; all of which have an impact on the schedule used by these UAVs to serve their respective users
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