Earticle

Issues in spectrum allocation between wireless network users have arisen due to the fast increase in the number of broadband services. Such issues include the failure to maximize the performance of all users by considering only a particular category of users. Specifically, a previously adopted selfish algorithm for spectrum allocation considers only the performance of the weakest user. To resolve this issue, we propose a new target data rate setting algorithm for dynamic spectrum allocation. In this algorithm, a Gaussian process regression model is trained to predict the target data rate. All users that perform below the defined target rate will have their frequency band allocations changed to one that guarantees a better performance. Through simulations, we show that the maximum data rate achieved by the weakest user in our algorithm is 121.7% higher than the selfish algorithm.

In this paper, we considered heterogeneous spectrum sharing system where the number of subcarriers of the primary user (PU) was twice as much as that of the secondary user (SU). In this case, due to non-orthogonality and inter-carrier interference (ICI) from SU to PU, it is difficult to satisfy the interference constraint of PU. In order to mitigate ICI and satisfy the interference constraint, we proposed a new transmission scheme of the SU with power allocation scheme. The proposed scheme will only generate subcarrier-by-subcarrier interference. Therefore, it can easily satisfy the interference constraint of the PR and enhance the capacity of the SU. In addition, we derived the ergodic capacity of the SU. Based on numerical results, we confirmed that the proposed schemes could guarantee SU with a reliable capacity while satisfying the interference constraint of the PU. In addition, the derived capacity well matched the numerical results.

실감미디어에 대한 시청자의 욕구가 증가하고 초고화질 방송을 위한 기술적 노력의 결과로 UHD(Ultra-High Definition) 방송시장의개시를 위한 움직임이 가속화되고 있다. 케이블 방송은 2013년 UHD 시범방송에 이어 2014년 4월 UHD 방송 상용화를 계획하고있다. 지상파 방송도 전송 규격에 대한 다양한 검토를 진행하며 2013년 2차례 실험방송을 실시하는 등 기술적 준비를 진행하고 있는상황이다. 하지만 아직 주파수 대역과 대역폭 등이 결정되지 않는 등 본격적인 서비스를 위해 해결할 과제가 남아있다. 이러한 배경에서 UHD 방송의 성공적인 개시와 방송시장의 활성화를 위해 본 논문은 차세대 지상파 방송을 위한 효율적인 주파수 운용 방안에대해 논의한다. 압축 부호기술과 채널 부호기술의 부호율 및 변조방식 등에 대한 고려를 통해 차세대 방송서비스를 위해 요구되는데이터 전송률을 검토하고, 시스템의 요구 대역폭을 제시한다. 또한 전국을 9개의 권역으로 나누고 SFN(Single FrequencyNetwork)망을 활용하여 4개의 주파수 군을 배분하는 안을 제시하였으며, 현재 사용하고 있는 지상파 디지털 주파수 대역을 재배치하여 지상파 UHD방송을 활성화하는 방안에 대해 제시한다.

Increasing demand for realistic media and improvement of transmission and device techniques accelerate ultra-highdefinition (UHD) service realization. In Korea, the cable TV broadcasting companies are planning to commercialize in Apr. 2014. For the terrestrial TV broadcasting service, technical issues are considered for the specification of UHD broadcastingsystem. However, the frequency bands and the system bandwidth for the terrestrial UHD broadcasting system have not beendecided. In this paper, we propose required spectrum bandwidth for the next-generation terrestrial broadcasting serviceconsidering source coding, error correcting codes and modulation techniques. Also, we propose frequency management planfor terrestrial UHD broadcasting system in which we divide all parts of the country into 9 frequency zones and allocate 4frequency band to each frequency zone considering single frequency network (SFN).

무선통신망에서 예측기법을 이용하는 경우는 대부분 사용자호가 요구하는 자원의 크기를 예측하여 미리 요구자원을 예약함으로써 사용자호가 요구하는 품질을 보장한다. 그러나 본 논문에서는 무선인지통신망에서 면허사용자가 사용하지 않는 스펙트럼홀(spectrum hole)자원의 크기를 예측하여 대여사용자의 스펙트럼 핸드오프호의 서비스 품질을 향상시킬 수 있는 채널할당방법을 제안한다. 스펙트럼홀의 예측은 위너예측모델을 이용한다. 채널할당 방법은 대여사용자호를 초기 발생호와 스펙트럼 핸드오프호로 구분하고, 예측된 스펙트럼홀 자원의 일정부분을 예약하여 스펙트럼 핸드오프호에 우선적으로 할당한다. 시뮬레이션을 통하여 제안한 기법이 스펙트럼홀 예측을 사용하지 않는 방법보다 대여사용자의 스펙트럼 핸드오프호의 서비스 품질을 향상(50% 예약시 평균 11% 개선)시킬 수 있음을 보인다.

In wireless communication networks, most of the prediction techniques are used for predicting the amount of resource required by user's calls for improving their demanding quality of service. However, we propose a channel allocation scheme based on predicting the resources of white spectrum holes for improving the QoS of rental user's spectrum handoff calls for cognitive radio networks in this paper. This method is supported by Wiener predictor to predict the amount of white spectrum holes of license user's free spectrum resources. We classify rental user's calls into initial calls and spectrum handoff calls, and some portion of predicted spectrum-hole resources is reserved for spectrum handoff calls' priority allocation. Simulations show that the performance of the proposed scheme outperforms in spectrum handoff call's dropping rate than an existing method without spectrum hole prediction(11% average improvement in 50% reservation).

본 논문에서는 셀룰러 기반 무선 인지망에서 스펙트럼 인지(CR)기술을 이용하여 모바일 사용자의 핸드오버 호의 손실확률을 줄이는 방법을 제안한다. 제안한 방법에서는 모바일이 방문할 셀을 Ziv-Lempel 알고리듬을 이용하여 예측하고, 방문할 셀에 할당된 채널이 부족할 때는 CR기술에 기초한 스펙트럼 홀 자원을 예측하여 모바일 사용자를 지원한다. 스펙트럼 홀 자원의 크기는 신경망기법으로 예측하며, 예측된 스펙트럼 홀 자원은 핸드오버 호가 초기 발생 호 보다 우선하여 사용할 수 있게 한다. 시뮬레이션을 통하여 셀룰러 이동 통신망에 CR기술을 사용함으로써 모바일 사용자의 핸드오버 호 손실확률을 줄일 수 있음을 보인다.

In this paper, we propose a method that reduces mobile user's handover call dropping probability by using cognitive radio technology(CR) in cellular - based wireless cognitive radio networks. The proposed method predicts a cell to visit by Ziv-Lempel algorithm, and then supports mobile user with prediction of spectrum holes based on CR technology when allocated channels are short in the cell. We make neural network predict spectrum hole resources, and make handover calls use the resources before initial calls. Simulation results show CR technology has the capability to reduce mobile user handover call dropping probability in cellular mobile communication networks.

In recent years, traffic requirement with variable bit rates and Quality of Service due to online High Definition video streaming, downloading movies and transferring of files are being satisfied with Elastic Optical Network (EON). Most efficient spectrum utilization is required to satisfy the demand with minimum blocking probability. The network is unstable and a small failure can lead to tremendous loss of data, hence survivability is mandatory. Slot Capacity based Spectrum Allocation with Survivability (SCSAS) algorithm is proposed which aims at the efficient spectrum utilization and configuration of protection paths. Duty Cycle Division Multiplexing (DCDM) and hop based modulation technique are also introduced to manage the spectrum which further reduces the spectrum wastage. The formation of spectrum fragments on the termination of existing requests increases the blocking probability. In order to improve the spectrum utilization, a spectrum defragmentation technique is introduced in the proposed work. Dynamic configuration of backup paths provides survivability. Results show an increase in free spectrum for dynamic requests, lesser spectrum wastage, and reduced blocking probability than the traditional algorithms such as fixed, flexible and random spectrum allocation.

To deal with the issues like existing generation of congestion nodes and redundancy transmission in the traditional load balancing algorithm, this paper puts forward the load balance multicast routing and spectrum allocation algorithm based on QOS constraints. The algorithm adopts LBWC algorithm to calculate the wireless link weight, and carries out the structure of the load balancing multicast tree. Then, the QOS constraints spectrum allocation algorithm is adopted based on wireless channel broadcast feature to conduct channel allocation of wireless link. Algorithm in this paper is under the condition of wireless multicast QOS constraints satisfactions, which balance the node load, minimize the transmission times of the wireless multicast business and reduce the consumption of network resources. Finally, simulation experiments are carried out, such as the influence of wireless multicast business number on the performance of the algorithm, the influence of the number of multicast destination node on the performance of the algorithm, the influence of the number of available channel on the performance of the algorithm and the influence of the control parameter β on the performance of algorithm, etc. Experimental results show that in the case of wireless multicast service constraint, the algorithm avoids the congestion nodes and reduces the times of transmission.

Spectrum allocation is a key operation in cognitive radio networks (CRNs), where secondary users (SUs) are usually selfish – to achieve itself utility maximization. In view of this context, much prior lit literature proposed spectrum allocation base on non-cooperative game models. However, the most of them proposed non-cooperative game models based on complete information of CRNs. In practical, primary users (PUs) in a dynamic wireless environment with noise uncertainty, shadowing, and fading is difficult to attain a complete information about them. In this paper, we propose a non-cooperative game joint hidden markov model scheme for spectrum allocation in CRNs. Firstly, we propose a new hidden markov model for SUs to predict the sensing results of competitors. Then, we introduce the proposed hidden markov model into the non-cooperative game. That is, it predicts the sensing results of competitors before the non-cooperative game. The simulation results show that the proposed scheme improves the energy efficiency of networks and utilization of SUs.

In this study, energy-efficient (EE) resource allocation in orthogonal frequency division multiplexing-based cognitive radio networks with imperfect spectrum sensing is investigated. We present a new EE model by considering the sensing errors. Optimizing such an EE expression saves valuable resources, such as battery life, by selectively allocating power to underutilized subcarriers, and also achieves EE gain compared with general EE expression. Given that the primary user’s interference tolerance can be defined as either the Peak Interference Power (PIP) constraint or Average Interference Power (AIP) constraint for all subchannels, we compare the EE performance for the two interference power constraints. Finally, we propose an optimal EE resource allocation scheme based on the quasiconcave relation between the EE and transmit power. Simulations show that the new EE design improves EE compared with the conventional EE design, and the EE is higher with AIP constraint than that with PIP constrain under certain interference power.

Increasing convergence among heterogeneous radio networks is expected to be a key feature of future ubiquitous services. The convergence of radio networks in combination with dynamic spectrum allocation (DSA) could be a beneficial means to solve the growing demand for radio spectrum. DSA might enhance the spectrum utilization of involved radio networks to comply with user requirements for high-quality multimedia services. This paper proposes a simple spectrum allocation algorithm and presents an analytical model of dynamic spectrum resource allocation between two networks using a 4-D Markov chain. We argue that there may exist a break-even point for choosing whether or not to adopt DSA in a system. We point out certain circumstances where DSA is not a viable alternative. We also discuss the performance of DSA against the degree of resource sharing using the proposed analytical model and simulations. The presented analytical model is not restricted to DSA, and can be applied to a general resource sharing study.

This study examines the use of score auctions in spectrum allocation as a policy instrument for promoting efficient network deployment. Because mobile networks generate substantial positive externalities, including broader connectivity benefits, industrial spillovers, and public-interest gains, market incentives alone may lead to insufficient investment relative to the social optimum. Governments have traditionally addressed this problem through direct regulation, typically by imposing mandatory build-out obligations as a condition of spectrum assignment. In South Korea, for example, regulators have commonly required assignees to deploy a fixed number of base stations within specified time periods. While this command-and-control approach is effective in achieving predetermined deployment targets, it is often inefficient because it lacks flexibility and cannot accommodate heterogeneity in operators’ deployment costs and business conditions. This paper shows that an indirect regulatory approach based on score auctions can improve the efficiency of network deployment. In a score auction, bidders submit both a price bid and a quality commitment, and the winner is selected according to a scoring rule that combines both components. In our model, each bidder’s private information is a two-dimensional vector consisting of a valuation for the spectrum and a cost parameter governing the cost of deployment. We analyze the first-score and second-score auction formats and show that both can be reduced to a tractable one-dimensional model. Our main results are twofold. First, we show that by designing the scoring rule to internalize network externalities, a score auction can align bidders’ private incentives with the social objective, thereby attaining the socially optimal outcome. Implementing this optimal mechanism, however, requires an estimate of the entire externality function, which is often unavailable to the regulator. To mitigate this informational burden, our second result shows that even when the global externality function is unknown, a score auction based on a point estimate of the marginal externality yields higher welfare than traditional direct regulation. This result provides a practical compromise between efficiency and implementability. Overall, our findings offer a theoretical foundation for shifting from direct to indirect regulation to enhance network deployment efficiency.

This paper addresses the resource allocation (RA) problem in multi-cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered-such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP-hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub-gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.

Traditional designs of cognitive radio (CR) focus on maximizing system throughput. In this paper, we study the joint overlay and underlay power allocation problem for orthogonal frequency-division multiple access-based CR. Instead of maximizing system throughput, we aim to maximize system energy efficiency (EE), measured by a "bit per Joule" metric, while maintaining the minimal rate requirement of a given CR system, under the total power constraint of a secondary user and interference constraints of primary users. The formulated energy-efficient power allocation (EEPA) problem is nonconvex; to make it solvable, we first transform the original problem into a convex optimization problem via fractional programming, and then the Lagrange dual decomposition method is used to solve the equivalent convex optimization problem. Finally, an optimal EEPA allocation scheme is proposed. Numerical results show that the proposed method can achieve better EE performance.

비능률적인 스펙트럼 이용률과 제한적인 스펙트럼 밴드 사용의 문제점을 해결하기 위하여, Cognitive Radio가 중요한 솔루션으로써 많은 연구가 진행되고 있다. 본 논문에서는 다중 채널 무선 네트워크에서의 QoS 보장을 위하여 Cognitive Radio 기반의 동적인 스펙트럼 할당 (Dynamic Spectrum Allocation)을 이용한 새로운 MAC 프로토콜을 제안한다. 사용자의 요청에 따라서, 유동적인 스펙트럼은 DSA 메커니즘을 통한 QoS 보장을 위하여 할당 된다. 그리고 동적인 스펙트럼 할당 (DSA)은 컨트롤 채널의 FRQ/FRP/ACK-hello와 데이터 채널의 DATA/ACK에 의하여 동작한다. 스펙트럼 공유의 성능을 증가시키기 위한 협력 검출 (Cooperative Detection)을 위하여, MAC 프로토콜에서는 Hello 메시지가 주기적으로 교환된다. 추가적으로, 성능 평가를 통하여 본 논문에서 제안한 DSA-MAC이 IEEE 802.11 MAC에 비하여 높은 데이터 처리량을 보임을 증명했다.

This study aims to derive the implications for Korean spectrum policies through an in-depth analysis of 5G spectrum-allocation cases. By examining the cases of four countries-France, Canada, the Netherlands and Colombia-the following key characteristics and implications were identified. First, the minimum bandwidth essential for service competition was guaranteed, easing the burden of spectrum acquisition on mobile operators. Second, auction rules were established to achieve an appropriate level of spectrum-allocation prices, which limited excessive price increases. Finally, license conditions such as the definitive re-allocation of the spectrum, were established to increase the infrastructure-investment incentives of mobile operators. The results of this study are expected to provide useful information for establishing auction rules for future Korean 5G spectrum allocations.

본 연구는 우리나라의 지상파 방송 디지털 전환에 따른 700MHz 대역의 여유주파수를 이동통신용으로 분배하여 이용하는 경우의 사회후생변화를 측정한다. 이를 위하여 헤이즐넛과 무네즈(Hazlett & Muñoz, 2009a)의 모형에 따라 이동전화시장의 서비스 수요와 공급함수를 추정하고 주파수 변화가 소비자잉여를 얼마나 변화시키는지를 측정하였다. 추정에는 우리나라를 포함한 29개국 이동통신사업자의 1999년부터 2008년까지의 분기별 패널자료를 이용하였다. 생산자 잉여는 국내 이동통신사업자의 영업이익과 매출을 감안하여 산출하였으며 소비자잉여와 생산자 잉여를 합한 사회후생 변화분을 측정하였다. 이동전화서비스의 수요 및 공급함수 추정결과 공급함수에서의 주파수탄력성은-0.07로 추정되었으며, 수요함수에서의 가격탄력성은 -0.28로 추정되었다. 추정된 공급함수 및 수요함수를 이용하여 100MHz의 주파수가 이동통신용으로 분배되어 활용될 경우 우리나라의 사회후생변화를 측정한 결과 현재가치 기준으로 약 11.5조원(103억불)이 증가되는 것으로 파악되었다. 본 연구에서 이용한 방법론과 분석결과는 주파수 분배에 있어 몇가지 착안사항을 제공한다. 우선 정책입안자는 주파수 용도별로 사회후생변화를 측정하여 주파수 분배에 활용하면 바람직할 것으로 보인다. 두번째로는 여유주파수의 통신용으로의 분배는 일반적으로 이동통신 요금하락을 낳는다는 점에 주목하고 이러한 주파수 분배 정책의 경제적 효과에도 주의를 기울일 필요가 있다.

This paper aims to estimate the social welfare change from the additional allocation of radio spectrum to mobile telecommunications service, which is expected to be released according to digital switchover in Korea. To this end, using a model of Hazlett & Munoz (2009a) (HM hereafter), we estimated demand and supply equations of mobile service to calculate the change of social welfare according to the additional allocation of spectrum. In the estimation, quarterly panel data of 29 countries for the period 1999~2008 was employed. In addition to consumer surplus, producer surplus was also estimated based on financial data of telecommunications operators on operating profit and sales. According to the estimation, the spectrum elasticity of supply was -0.07, and the price elasticity of demand was -0.28. Using the estimation results, it is forecast that social welfare increase by about 11.5 trillion won (10.3 billion dollars) at present value according to the additional 100 MHz allocation. The methodology and result of this study may provide some insights to those in charge of spectrum allocation policy. Policy makers may employ the MH methodology to evaluate the effect of spectrum allocation for various purposes. If spectrum is allocated according to the size of welfare increase, it will contribute to the efficient use of the spectrum. Secondly, they need to pay attention to the price-reducing effect of spectrum allocation for mobile services. Policy makers should consider this kind of economic effect of spectrum allocation policy.

본 논문에서는 최근 주파수 자원에 대한 수요가 급증하면서 효율적으로 주파수를 이용하기 위해 주파수 공유를 하면서 생길 수 있는 비용문제의 최고의 이득을 발생시킬 수 있도록 하기 위하여 이종네크워크(Heterogeneous Network)에서 매크로셀과 펨토셀 환경에서 스펙트럼 공유에 있어서 매크로셀이 사용하지 않는 스펙트럼을 펨토셀에 공유해줌으로써 이득을 취할 수 있는데 이러한 이득에 있어서 최고의 이득을 발생시킬 수 있도록 하기 위하여 펨토셀의 스펙트럼 공유당 비용 최적화 알고리즘을 제안 하였다.