プライマリシステムの干渉制限を考慮した周波数共用のためのリソース割り当てに関する研究

In wireless communications, the improvement of spectral efficiency isrequired due to the shortage of frequency resource. As an effectivesolution, spectrum sharing has been attracted attention. A cognitiveradio is promising technology for realization of spectrum sharing. Inthe spectrum sharing, cognitive user (secondary user) has to protectlicensed user (primary user) according to the interference constraint.However, conventional metric of interference constraint cannot avoidlarge performance degradation in primary system with widely rangeof Signal to Noise Ratio (SNR) such as a cellular system. Additionally,conventional interference constraints do not considers schedulingbehavior in cellular system. In order to solve these problems, thispaper proposes novel metric of the interference constraint whichsupports the widely SNR region of the primary system, so calledcapacity conservation ratio (CCR). The CCR is defined as the ratio ofthe capacity of the Primary receiver without interference from thesecondary transmitter, to the decreased primary capacity due tointerference. Proposed interference constraint based on CCR canprotect primary capacities over the widely SNR region. In addition,scheduling behavior of the primary system can be protected by usingproposed interference constraint. In addition, we propose transmitpower control schemes: exact and simplified power control. The exactpower control can satisfy requirement of interference constraintwithout large margin; however, transmit power cannot be derivewithout numerical analysis. In contrast, transmit power isclosed-form solution in the simplified power control with satisfyingthe interference constraint. Finally, this thesis proposes the resourcescheduling under the interference constraint. Proposed schedulingachieves the high throughput and high user fairness in the secondarysystem without increasing feedback information compared withconventional algorithm.現在、無線通信において周波数リソース不足が深刻な問題となっており、抜本的な対策技術としてコグニティブ周波数共用が注目されている。本論文では、周波数共用において既存システムの周波数帯を他システム（2 次システム）が二次利用するために干渉制限指標及びリソース割り当てに関する研究を行った。一つ目の研究では、既存システムに与える与干渉状態の評価指標について提案を行い，幅広い通信品質の既存システムを保護可能な干渉制限について評価を行った．評価ではシステムのリンクが静的モデルおよび動的なリソース配分で変更される動的モデルを用いた．二つ目の研究では，その干渉制限達成可能な送信電力制御の検討を行った。送信電力制御を行う際に，外部からチャネル情報の一部のみが得られると仮定し，確率的に変動するフェージング要素について所望のアウテージ確率を満足できるように数値解析を行い，厳密設計および簡易設計について提案を行った．三つ目の研究では、既存システムが複数端末に対して無線リソースをスケジューリングするモデルへと拡張し，2 次システムが干渉を回避しつつ，効率的リソース割り当てに関する検討を行った。電気通信大学201

Mathematical optimization techniques for resource allocation and spatial multiplexing in spectrum sharing networks

Due to introduction of smart phones with data intensive multimedia and interactive applications and exponential growth of wireless devices, there is a shortage for useful radio spectrum. Even though the spectrum has become crowded, many spectrum occupancy measurements indicate that most of the allocated spectrum is underutilised. Hence radically new approaches in terms of allocation of wireless resources are required for better utilization of radio spectrum. This has motivated the concept of opportunistic spectrum sharing or the so-called cognitive radio technology that has great potential to improve spectrum utilization. The cognitive radio technology allows an opportunistic user namely the secondary user to access the spectrum of the licensed user (known as primary user) provided that the secondary transmission does not harmfully affect the primary user. This is possible with the introduction of advanced resource allocation techniques together with the use of wireless relays and spatial diversity techniques. In this thesis, various mathematical optimization techniques have been developed for the efficient use of radio spectrum within the context of spectrum sharing networks. In particular, optimal power allocation techniques and centralised and distributed beamforming techniques have been developed. Initially, an optimization technique for subcarrier and power allocation has been proposed for an Orthogonal Frequency Division Multiple Access (OFDMA) based secondary wireless network in the presence of multiple primary users. The solution is based on integer linear programming with multiple interference leakage and transmission power constraints. In order to enhance the spectrum efficiency further, the work has been extended to allow multiple secondary users to occupy the same frequency band under a multiple-input and multiple-output (MIMO) framework. A sum rate maximization technique based on uplink-downlink duality and dirty paper coding has been developed for the MIMO based OFDMA network. The work has also been extended to handle fading scenarios based on maximization of ergodic capacity. The optimization techniques for MIMO network has been extended to a spectrum sharing network with relays. This has the advantage of extending the coverage of the secondary network and assisting the primary network in return for the use of the primary spectrum. Finally, instead of considering interference mitigation, the recently emerged concept of interference alignment has been used for the resource allocation in spectrum sharing networks. The performances of all these new algorithms have been demonstrated using MATLAB based simulation studies

Channel assembling and resource allocation in multichannel spectrum sharing wireless networks

Submitted in fulfilment of the academic requirements for the degree of Doctor of Philosophy (Ph.D.) in Engineering, in the School of Electrical and Information Engineering, Faculty of Engineering and the Built Environment, at the University of the Witwatersrand, Johannesburg, South Africa, 2017The continuous evolution of wireless communications technologies has increasingly imposed a burden on the use of radio spectrum. Due to the proliferation of new wireless networks applications and services, the radio spectrum is getting saturated and becoming a limited resource. To a large extent, spectrum scarcity may be a result of deficient spectrum allocation and management policies, rather than of the physical shortage of radio frequencies. The conventional static spectrum allocation has been found to be ineffective, leading to overcrowding and inefficient use. Cognitive radio (CR) has therefore emerged as an enabling technology that facilitates dynamic spectrum access (DSA), with a great potential to address the issue of spectrum scarcity and inefficient use. However, provisioning of reliable and robust communication with seamless operation in cognitive radio networks (CRNs) is a challenging task. The underlying challenges include development of non-intrusive dynamic resource allocation (DRA) and optimization techniques. The main focus of this thesis is development of adaptive channel assembling (ChA) and DRA schemes, with the aim to maximize performance of secondary user (SU) nodes in CRNs, without degrading performance of primary user (PU) nodes in a primary network (PN). The key objectives are therefore four-fold. Firstly, to optimize ChA and DRA schemes in overlay CRNs. Secondly, to develop analytical models for quantifying performance of ChA schemes over fading channels in overlay CRNs. Thirdly, to extend the overlay ChA schemes into hybrid overlay and underlay architectures, subject to power control and interference mitigation; and finally, to extend the adaptive ChA and DRA schemes for multiuser multichannel access CRNs. Performance analysis and evaluation of the developed ChA and DRA is presented, mainly through extensive simulations and analytical models. Further, the cross validation has been performed between simulations and analytical results to confirm the accuracy and preciseness of the novel analytical models developed in this thesis. In general, the presented results demonstrate improved performance of SU nodes in terms of capacity, collision probability, outage probability and forced termination probability when employing the adaptive ChA and DRA in CRNs.CK201

Mathematical optimization techniques for resource allocation in cognitive radio networks

Introduction of data intensive multimedia and interactive services together with exponential growth of wireless applications have created a spectrum crisis. Many spectrum occupancy measurements, however, have shown that most of the allocated spectrum are used inefficiently indicating that radically new approaches are required for better utilization of spectrum. This motivates the concept of opportunistic spectrum sharing or the so-called cognitive radio technology that has great potential to improve spectrum utilization. This technology allows the secondary users to access the spectrum which is allocated to the licensed users in order to transmit their own signal without harmfully affecting the licensed users' communications. In this thesis, an optimal radio resource allocation algorithm is proposed for an OFDM based underlay cognitive radio networks. The proposed algorithm optimally allocates transmission power and OFDM subchannels to the users at the basestation in order to satisfy the quality of services and interference leakage constraints based on integer linear programming. To reduce the computational complexity, a novel recursive suboptimal algorithm is proposed based on a linear optimization framework. To exploit the spatial diversity, the proposed algorithms are extended to a MIMO-OFDM based cognitive radio network. Finally, a novel spatial multiplexing technique is developed to allocate resources in a cognitive radio network which consists of both the real time and the non-real users. Conditions required for convergence of the proposed algorithm are analytically derived. The performance of all these new algorithms are verified using MATLAB simulation results.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Spectral Efficiency of Multi-User Adaptive Cognitive Radio Networks

In this correspondence, the comprehensive problem of joint power, rate, and subcarrier allocation have been investigated for enhancing the spectral efficiency of multi-user orthogonal frequency-division multiple access (OFDMA) cognitive radio (CR) networks subject to satisfying total average transmission power and aggregate interference constraints. We propose novel optimal radio resource allocation (RRA) algorithms under different scenarios with deterministic and probabilistic interference violation limits based on a perfect and imperfect availability of cross-link channel state information (CSI). In particular, we propose a probabilistic approach to mitigate the total imposed interference on the primary service under imperfect cross-link CSI. A closed-form mathematical formulation of the cumulative density function (cdf) for the received signal-to-interference-plus-noise ratio (SINR) is formulated to evaluate the resultant average spectral efficiency (ASE). Dual decomposition is utilized to obtain sub-optimal solutions for the non-convex optimization problems. Through simulation results, we investigate the achievable performance and the impact of parameters uncertainty on the overall system performance. Furthermore, we present that the developed RRA algorithms can considerably improve the cognitive performance whilst abide the imposed power constraints. In particular, the performance under imperfect cross-link CSI knowledge for the proposed `probabilistic case' is compared to the conventional scenarios to show the potential gain in employing this scheme