A Review and Evaluation of Queue Based Control Power Efficient Spectrum Allocation Method for LTE Networks

The cognitive radio based wireless regional area networks (WRAN) is nothing but IEEE-802.22 standard. IEEE 802.22 standard enables opportunistic access to in-use or free 900 MHz TV sub bands by secondary networks. There are many other standards presented; however there is no efficient methods for cognitive networks like LTE for channel access and bandwidth utilization. The existing methods for spectrum access in LTE networks, however most of methods are not flexible, power consuming. Also in literature, we studied that existing methods of spectrum allocation in LTE networks does not efficiently achieve the tradeoff between network QoS (Quality of Service) and power efficiency. The goal of this paper is to present the review on such different spectrum efficiency techniques for LTE networks and then evaluate the recent Queue Based Control (QBC) for power efficient spectrum allocation with its limitations and benefits. QBC approach helps in solving the research problem related to the energy efficiency as well as QoS efficiency to some extent. There are two variants of QBC method such as QBC1 and QBC2 with different objectives and configurations. We are evaluating both this approach on LTE network which is composed of Spectrum Manager (SM), evolved Nodes B (eNBs) and number of user’s. The experimental work is conducted using network simulator (NS2) for delay and energy consumption parameters

Skedulering i kognitiva månghopps- och mångbandsradionätverk utnyttjandes potentialfält

The problem of scheduling transmissions in multi-hop multi-band cognitive radio (CR) networks is studied. The scheduling is subdivided into long- and short-term problems. The long-term problem concerns the routing of data packets. It is solved by means of a novel potential field based modeling technique that abstracts routes away from paths defined by sequences of specific network links and onto an underlying potential field. The short-term problem is formulated as a mixed integer nonlinear program (MINLP) that describes the instantaneous interference constraints that secondary users (SUs) have to satisfy if they wish to utilize the spectrum licensed to primary users (PUs). These interference constraints are defined in terms of required signal-to-interference-plus-noise ratios (SINRs) at receivers. A centralized greedy algorithm, as well as a distributed version of it, is proposed for solving the short-term problem. Simulations show that the proposed methods work well in both static and dynamic networks. Moreover, the methods contain adjustable parameters that allow one to e.g. improve the fairness of the scheduling at the cost of overall throughput, or to significantly improve the overall throughput at the cost of a non-zero but arbitrarily small probability of violating the interference constraints.Skedulering av sändningar i kognitiva månghopps- och mångbandsradionätverk undersöks. Skeduleringen delas upp i ett långsiktigt respektive ett kortsiktigt problem. Det långsiktiga problemet behandlar dirigeringen av datapaket. Problemet löses genom en ny potentialfältsbaserad modelleringsteknik där datarutterna beskrivs av ett underliggande potentialfält istället för sekvenser av specifika nätverkslänkar. Det kortsiktiga problemet utgörs av ett icke-linjärt optimeringsproblem som beskriver de interferensvillkor vilka de sekundära användarna måste uppfylla för att få tillgång till det spektrum som licensierats till primära användare. Interferensvillkoren är definierade i form av nödvändiga signal-till-interferens-plus-brusförhållanden hos mottagare. En centraliserad girig algoritm, samt en distribuerad version av den, föreslås som lösning på det kortsiktiga problemet. Simulationer visar att de föreslagna metoderna fungerar väl i både statiska och dynamiska nätverk. Dessutom innehåller metoderna justerbara parametrar med vilka man t.ex. kan förbättra rättvisheten i skeduleringen på bekostnad av den totala datahastigheten, eller märkbart förbättra den totala datahastigheten på bekostnad av en positiv men godtyckligt liten sannolikhet att interferensvillkoren inte alltid uppfylls

Cooperative Spectrum Sensing in Cognitive Radio Networks Using Multidimensional Correlations

In this paper, a multidimensional-correlation-based sensing scheduling algorithm, (CORN)2, is developed for cognitive radio networks to minimize energy consumption. A sensing quality metric is defined as a measure of the correctness of spectral availability information based on the fact that spectrum sensing information at a given space and time can represent spectrum information at a different point in space and time. The scheduling algorithm is shown to achieve a cost of sensing (e.g., energy consumption, sensing duration) arbitrarily close to the possible minimum, while meeting the sensing quality requirements. To this end, (CORN)2 utilizes a novel sensing deficiency virtual queue concept and exploits the correlation between spectrum measurements of a particular secondary user and its collaborating neighbors. The proposed algorithm is proved to achieve a distributed and arbitrarily close to optimal solution under certain, easily satisfied assumptions. Furthermore, a distributed Selective-(CORN)2 (S-(CORN)2) is introduced by extending the distributed algorithm to allow secondary users to select collaboration neighbors in densely populated cognitive radio networks. In addition to the theoretically proved performance guarantees, the algorithms are evaluated through simulations