371 research outputs found

    Topology-Transparent Scheduling in Mobile Ad Hoc Networks With Multiple Packet Reception Capability

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    Recent advances in the physical layer have enabled wireless devices to have multiple packet reception (MPR) capability, which is the capability of decoding more than one packet, simultaneously, when concurrent transmissions occur. In this paper, we focus on the interaction between the MPR physical layer and the medium access control (MAC) layer. Some random access MAC protocols have been proposed to improve the network performance by exploiting the powerful MPR capability. However, there are very few investigations on the schedule-based MAC protocols. We propose a novel m-MPR-l-code topology-transparent scheduling ((m, l)-TTS) algorithm for mobile ad hoc networks with MPR, where m indicates the maximum number of concurrent transmissions being decoded, and l is the number of codes assigned to each user. Our algorithm can take full advantage of the MPR capability to improve the network performance. The minimum guaranteed throughput and average throughput of our algorithm are studied analytically. The improvement of our (m, l)-TTS algorithm over the conventional topology-transparent scheduling algorithms with the collision-based reception model is linear with m. The simulation results show that our proposed algorithm performs better than slotted ALOHA as well.published_or_final_versio

    The Practical Challenges of Interference Alignment

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    Interference alignment (IA) is a revolutionary wireless transmission strategy that reduces the impact of interference. The idea of interference alignment is to coordinate multiple transmitters so that their mutual interference aligns at the receivers, facilitating simple interference cancellation techniques. Since IA's inception, researchers have investigated its performance and proposed improvements, verifying IA's ability to achieve the maximum degrees of freedom (an approximation of sum capacity) in a variety of settings, developing algorithms for determining alignment solutions, and generalizing transmission strategies that relax the need for perfect alignment but yield better performance. This article provides an overview of the concept of interference alignment as well as an assessment of practical issues including performance in realistic propagation environments, the role of channel state information at the transmitter, and the practicality of interference alignment in large networks.Comment: submitted to IEEE Wireless Communications Magazin

    Full-duplex wireless communications: challenges, solutions and future research directions

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    The family of conventional half-duplex (HD) wireless systems relied on transmitting and receiving in different time-slots or frequency sub-bands. Hence the wireless research community aspires to conceive full-duplex (FD) operation for supporting concurrent transmission and reception in a single time/frequency channel, which would improve the attainable spectral efficiency by a factor of two. The main challenge encountered in implementing an FD wireless device is the large power difference between the self-interference (SI) imposed by the device’s own transmissions and the signal of interest received from a remote source. In this survey, we present a comprehensive list of the potential FD techniques and highlight their pros and cons. We classify the SI cancellation techniques into three categories, namely passive suppression, analog cancellation and digital cancellation, with the advantages and disadvantages of each technique compared. Specifically, we analyse the main impairments (e.g. phase noise, power amplifier nonlinearity as well as in-phase and quadrature-phase (I/Q) imbalance, etc.) that degrading the SI cancellation. We then discuss the FD based Media Access Control (MAC)-layer protocol design for the sake of addressing some of the critical issues, such as the problem of hidden terminals, the resultant end-to-end delay and the high packet loss ratio (PLR) due to network congestion. After elaborating on a variety of physical/MAC-layer techniques, we discuss potential solutions conceived for meeting the challenges imposed by the aforementioned techniques. Furthermore, we also discuss a range of critical issues related to the implementation, performance enhancement and optimization of FD systems, including important topics such as hybrid FD/HD scheme, optimal relay selection and optimal power allocation, etc. Finally, a variety of new directions and open problems associated with FD technology are pointed out. Our hope is that this treatise will stimulate future research efforts in the emerging field of FD communication

    Interference Alignment for Cognitive Radio Communications and Networks: A Survey

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    © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe
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