| Nowadays, the fixed spectrum management policy has resulted in very low spectrum efficiency, and the shortage of spectrum resources is becoming the bottleneck to limit the sustained development of wireless communication service. How to solve the problem of scarce spectrum resources to improve spectrum efficiency in limited radio resource environment, has become a hot issue in the study field of wireless communications technology. The cognitive radio, which emerges in this background, is known as the most popular wireless technology for its intelligent and revolutionary spectrum sharing.Spectrum allocation, as one of the key technologies for cognitive radio, improves the whole performance of networks to approximate optimal condition. There are many disadvantages in representative pricing auction allocation model and graph coloring allocation model. Comparing with traditional ones, game theory allocation model is able to overcome these disadvantages through not limited to the dynamic characteristics of networks and the number of idle channels. On the basis this paper put forward a further improvement by considering the user preference from vertical differentiation of spectrum. Moreover, partly limited spectrum allocation can take no account of the strict restrict of spectrum occupied by primary users, so it improves more spectrum efficiency than completely limited spectrum allocation. This paper presented an algorithm of subcarrier and power allocation by using CR-OFDM under the constraint of interference power threshold and maximum transmit power. The system took account of proportion fair principle on the premise of pursuing maximum throughput to achieve optimal performance by incessant self-adaption.The main contents included the following:Part1reviewed the background and significance of cognitive radio technology, then illustrated the research status and standardization progress of it.Part2introduced the definition of cognitive radio, after that described some of the key technologies in the cognitive radio networks, and finally illustrated the application prospects of it.Part3gave the basic concept of spectrum allocation, then divided spectrum allocation technology into six categories and briefly described the several typical spectrum allocation strategies.Part4formulated the spectrum allocation problem as a duopoly market with vertical differentiation in cognitive radio environment. The vertical differentiation showed the not fully substitutability of similar channels. It used static Cournot game to acquire demand functions. On the basis it presented dynamic Cournot game to compute the stable region and equilibrium. After determining the convergence condition of stable state, we conducted the simulation. The results show when the speed adjustment parameter is a smaller value and in the stable region, game is smooth and achieves the ultimate Nash equilibrium in a short time. The profit of primary user is more related to channel quality instead of allocated channel number. Because of the not fully substitutability and two-order cost function, the primary user who lends too many channels could not improve its profit even decrease it sometimes.Part5focused on the combination of CR wireless networks and OFDM subcarrier to divide spectrum resource allocation algorithm into two steps. The first step is according to relative gain factor to distribute subcarriers for each cognitive user on the premise of taking account of proportion fair principle. The second step is filling power and carrying on self-adaption for distributed subcarriers under constraint conditions. The simulation results show that taking account of proportion fair principle can enhance more system performance than only considering maximum throughput. The throughput sustains growth by self-adaption under maximum transmit power constraint. In addition, when the SNR is high or the maximum transmit power is small, linear water-filling power allocation can be used to reduce computational complexity. |
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