逐次干渉除去を用いた多元接続システムのパワー割り当てに関する研究

In future wireless communication networks, the number of devices is likely to increase dramatically due to potential development of new applications such as the Internet of Things (IoT). Consequently, radio access network is required to support multiple access of massive users and achieve high spectral efficiency. From the information theoretic perspective, orthogonal multiple access protocols are suboptimal. To achieve the multiple access capacity, non-orthogonal multiple access protocols and multiuser detection (MUD) are required. For the non-orthogonal code-division multiple access (CDMA), several MUD techniques have been proposed to improve the spectrum efficiency. Successive interference cancellation (SIC) is a promising MUD techniques due to its low complexity and good decoding performance. Random access protocols are designed for the system with bursty traffic to reduce the delay, compared to the channelized multiple access. Since the users contend for the channel instead of being assigned by the base station (BS), collisions happen with a certain probability. If the traffic load becomes relatively high, the throughput of these schemes steeply falls down because of collisions. However, it has been well-recognized that more complex procedures can permit decoding of interfering signals, which is referred to as multi-packet reception (MPR). Also, an SIC decoder might decode more packets by successively subtracting the correctly decoded packets from the collision. Cognitive radio (CR) is an emerging technology to solve the problem of spectrum scarcity by dynamically sharing the spectrum. In the CR networks, the secondary users (SUs) are allowed to dynamically share the frequency bands with primary users (PUs) under primary quality-of-service (QoS) protection such as the constraint of interference temperature at the primary base station (PBS). For the uplink multiple access to the secondary base station (SBS), transmit power allocation for the SUs is critical to control the interference temperature at the PBS. Transmit power allocation has been extensively studied in various multiple access scenarios. The power allocation algorithms can be classified into two types, depending on whether the process is controlled by the base station (BS). For the centralized power allocation (CPA) algorithms, the BS allocates the transmit powers to the users through the downlink channels. For the random access protocols, there are also efforts on decentralized power allocation (DPA) that the users select transmit powers according to given distributions of power and probability, instead of being assigned the transmit power at each time slot by the BS. In this dissertation, the DPA algorithms for the random access protocols with SIC are investigated and new methods are proposed. First a decentralized multilevel power allocation algorithm to improve the MAC throughput performance is proposed, for the general SIC receiver that can decode multiple packets from one collision. Then an improved DPA algorithm to maximize the overall system sum rate is proposed, taking into account of both the MAC layer and PHY layer. Finally, a DPA algorithm for the CR secondary random access is proposed, considering the constraint of interference temperature and the practical assumption of imperfect cancellation. An opportunistic transmission protocol for the fading environment to further reduce the interference temperature is also proposed. For the future work, the optimal DPA for the random access with the SIC receiver is still an open problem. Besides, advanced multiple access schemes that aim to approach the multiple access capacity by combining the advantages of the network coded cooperation, the repetition slotted ALOHA, and the SIC receiver are also interesting.電気通信大学201

Energy-Efficient Cooperative Cognitive Relaying Schemes for Cognitive Radio Networks

We investigate a cognitive radio network in which a primary user (PU) may cooperate with a cognitive radio user (i.e., a secondary user (SU)) for transmissions of its data packets. The PU is assumed to be a buffered node operating in a time-slotted fashion where the time is partitioned into equal-length slots. We develop two schemes which involve cooperation between primary and secondary users. To satisfy certain quality of service (QoS) requirements, users share time slot duration and channel frequency bandwidth. Moreover, the SU may leverage the primary feedback message to further increase both its data rate and satisfy the PU QoS requirements. The proposed cooperative schemes are designed such that the SU data rate is maximized under the constraint that the PU average queueing delay is maintained less than the average queueing delay in case of non-cooperative PU. In addition, the proposed schemes guarantee the stability of the PU queue and maintain the average energy emitted by the SU below a certain value. The proposed schemes also provide more robust and potentially continuous service for SUs compared to the conventional practice in cognitive networks where SUs transmit in the spectrum holes and silence sessions of the PUs. We include primary source burstiness, sensing errors, and feedback decoding errors to the analysis of our proposed cooperative schemes. The optimization problems are solved offline and require a simple 2-dimensional grid-based search over the optimization variables. Numerical results show the beneficial gains of the cooperative schemes in terms of SU data rate and PU throughput, average PU queueing delay, and average PU energy savings

Dynamic Flow-Adaptive Spectrum Leasing with Channel Aggregation in Cognitive Radio Networks

Cognitive radio networks (CRNs), which allow secondary users (SUs) to dynamically access a network without affecting the primary users (PUs), have been widely regarded as an effective approach to mitigate the shortage of spectrum resources and the inefficiency of spectrum utilization. However, the SUs suffer from frequent spectrum handoffs and transmission limitations. In this paper, considering the quality of service (QoS) requirements of PUs and SUs, we propose a novel dynamic flow-adaptive spectrum leasing with channel aggregation. Specifically, we design an adaptive leasing algorithm, which adaptively adjusts the portion of leased channels based on the number of ongoing and buffered PU flows. Furthermore, in the leased spectrum band, the SU flows with access priority employ dynamic spectrum access of channel aggregation, which enables one flow to occupy multiple channels for transmission in a dynamically changing environment. For performance evaluation, the continuous time Markov chain (CTMC) is developed to model our proposed strategy and conduct theoretical analyses. Numerical results demonstrate that the proposed strategy effectively improves the spectrum utilization and network capacity, while significantly reducing the forced termination probability and blocking probability of SU flows.publishedVersio

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 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

Spectrum sharing in cognitive radio networks

Cognitive radio networks are the next step to tackle scarcity in wireless networks given the increasing demand of radioelectric spectrum where the proposed solution is to share said resource to improve this situation. In the present article, a review of the current state of spectrum sharing in cognitive radio networks. To achieve this purpose, the articles published over the last 4 years on the matter were reviewed including topics such as mobile networks and TV. Some studies and simulations proposed to share the spectrum is shown. The current state of the studies reveals that there has been significant progress in this research area yet it is necessary to continue similar studies and set in motion different schemes

Implementation of spectrum sensing techniques for cognitive radio systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This work presents a method for real-time detection of secondary users at the cognitive wireless technologies base stations. Cognitive radios may hide themselves in between the primary users to avoid being charged for spectrum usage. To deal with such scenarios, a cyclostationary Fast Fourier Transform accumulation method (FAM) has been used to develop a new strategy for recognising channel users under perfect and different noise environment conditions. Channel users are tracked according to the changes in their signal parameters, such as modulation techniques. MATLAB® Simulation tool was used to run various modulation signals on channels, and the obtained spectral correlation density function shows successful recognition between secondary and primary signals. We are unaware of previous efforts to use the FAM characteristics or other detection methods to make a distinction between channel users as presented in this thesis. A novel combination of both cognitive radio technology and ultra wideband technology is interdicted in this thesis, looking for an efficient and reliable spectrum sensing method to detect the presence of primary transmitters, and a number of spectrum-sensing techniques implemented in ultra wideband and cognitive radio component (UWB-CR) under different AWGN and fading settings environments. The sensing performance of different detectors is compared in conditions of probability of detection and miss detection curves. Simulation results show that the selection of detectors rely on the different fading scenarios, detector requirements and on a priori knowledge. Furthermore, result showed that the matched filter detection method is suitable for detecting signals through UWB-CR system under various fading channels. A general observation is that the matched filter detector outperforms the other detectors in all scenarios by an average of SNR=-20 dB in the level of probability of detection (Pd) , and the energy detector slightly outperforms the cyclostationary detector, in the level Pd at SNR=-20 dB. Furthermore, the thesis adapts novel detection models of cooperative and cluster cooperative wideband spectrum sensing in cognitive radio networks. In the proposed schemes, wavelet-based multi-resolution spectrum sensing and a proposed approach scheme are utilized for improving sensing performance of both models. On the other hand, cluster based cooperative spectrum sensing with soft combination Equal Gain Combination (EGC) scheme is proposed. The proposed detection models could achieve improvement of transmitter signal detection in terms of higher probability of detection and lower probability of false alarm. In the cooperative wideband spectrum sensing model, using traditional fusion rule, existing worst performance of false alarms by measurement is 78% of the sensing bands at an average SNR=5 dB; this compares with the proposed model, which is by measurement 19% false alarms of scanning spectrum at the same SNR for cluster cooperative wideband spectrum sensing. The proposed combining methods shows improvements of results with a high probability of detection (Pd) and low probability of false alarm (Pf) at an average SNR=-16 dB compared with other traditional fusion methods; this is illustrated through numerical results