| With the increasing number of wireless devices and applications, cognitive radio (CR) hasbeen proposed as an efficient technology to improve spectrum efficiency and recently it has beenwidely studied to deal with the underutilization of the licensed spectrum. Due to its flexibility inallocating resources among CR users (CRUs) as well as its ability to monitor the spectral activitiesof Primary users (PUs) at no extra cost, orthogonal frequency division multiple access (OFDMA),also known as multiuser orthogonal frequency division multiplexing (multiuser OFDM), has beenrecognized as a potential candidate for CR systems. However, in OFDMA-based CR systems, bothCRU and PU may exist in side-by-side bands and they may have different access technologies.Thus, the transmitted signals of CRU and PU are not orthogonal and this non-orthogonality of therespective transmitted signals may cause mutual interference between PU and CRU. Besides,spectrum sharing may also cause interference between PU and CRU. As a limiting factor for theperformance of CR systems, interference (especially interference caused by CRUs to PUs) shouldbe limited under specified thresholds. In addition, QoS requirements of CRUs which accessspectrum holes should also be maintained. In general, resource allocation is an efficient approachto protect PU from unacceptable interference and maintain QoS requirements of CRUs. In thisthesis, several optimization problems are formulated, and the related resource allocation andinterference suppression techniques in OFDMA-based CR systems are investigated.The main research work and outcome of this thesis include:1. To begin with, resource allocation to maintain minimum transmission rate of CRUs withthe specified interference thresholds is investigated. Firstly, a single PU CR system is considered,and a suboptimal resource allocation algorithm to maximize the sum transmission rate of all CRUsis proposed. Secondly, the single PU scenario is extended to multiple PUs case and anasymptotically optimal resource allocation algorithm is proposed using dual methods subject toconstraints on both interference thresholds of PUs and total transmit power of all CRUs. Analysisand numerical results show that, in contrast to classical resource allocation algorithms, theproposed algorithm can achieve higher transmission rate and guarantee each CRU’s minimumtransmission rate in both scenarios.2. Then, the resource allocation problem for statistical proportional fairness ininterference-limited OFDMA-based CR systems is studied. Resource allocation for proportionalfairness in CR systems has two challenges: firstly, the instantaneous channel gains of PU aredifficult to be estimated at the CR transmitter; secondly, the number of available subchannels is smaller than that of CRUs in some OFDM symbol durations. In this thesis, taking themaximization of the ergodic sum capacity of all CRUs as the optimization object, a resourceallocation algorithm under the constraints on the long-term transmit power of all CRUs, thelong-term interference thresholds of PUs, and the statistical proportional rates among all CRUs isproposed. It is shown show that, in contrast to traditional resource allocation algorithm, theproposed algorithm can achieve higher transmission rate and guarantee proportional fairnessamong CRUs.3. Next, resource allocation problem for proportional fairness in hybrid CR systems isstudied. In OFDMA-based CR systems, traditional resource allocation algorithms can notguarantee proportional rates among CRUs in each OFDM symbol because the number of availablesubchannels might be smaller than that of CRUs in some OFDM symbols. To deal with thistime-varying nature of available spectrum resource, a hybrid CR scheme in which CRUs areallowed to use subchannels in both spectrum holes and PU bands is adopted and a resourceallocation algorithm is proposed to guarantee proportional rates among CRUs with no undueinterference to PUs.4. Since spectrum sensing is a key technique for determining the spectrum available in CRnetworks. This thesis studies how to jointly optimize sensing time and resource allocation tomaximize the sum transmission rate of all CRUs of a multichannel CR network. This thesis takesinto consideration the transmission power and interference constraints to protect PUs fromharmful interference, as well as constraints of detection probability and false alarm probability. Anasymptotically optimal resource allocation algorithm is presented. The optimal sensing time canbe obtained using the traditional one-dimensional exhaustive search. However, to overcome thehigh complexity of searching for the sensing time, a simplified method to get the optimal sensingtime under the assumption that false alarm probability is small, is also proposed. It is demonstratedthat the simplified method can obtain the optimal sensing time efficiently under strict constraint offalse alarm probability.5. Finally, because open access is an efficient approach to reduce cross-tier interference infemtocell networks. Resource allocation in open access OFDMA femtocell networks to guaranteeQoS of the neighboring macrocell user (MU) in Dead Zone and limit cross-tier interference toother MUs is investigated. A new resource allocation method is proposed to improve performanceof both neighboring MU and femtocell users (FU). In specific, the subchannel set originallyassigned to the MU may overlap the subchannel set occupied by FAP (femtocell access point) andcause cross-tier interference. The overlapped subchannel set is freed by macro base station (MBS)after MU resigns and joins the nearby femtocell. Then the subchannel and power resources in thefemtocell are re-allocated. This thesis leverages CR technology in femtocell networks andproposes an asymptotically optimal resource allocation algorithm using dual decompositionmethods. It is shown that the proposed algorithm for the open access scheme can achieve highertransmission rate in contrast to the closed access scheme. |
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