Self-organizing network is used for regional communications, which makes up for the coverage of mobile communication system. In LTE-Advanced network, such network forms by proximity communications and utilizes the limited bandwidth efficiently. However, the system frequencies shared by the terminals in self-organizing network belong to cellular terminals, the resource reusing leads to interference. Meanwhile, due to the mobility of devices and the dynamic topology of self-organizing network, the level of interference becomes more unpredictable. In this paper, we proposed to establish a probabilistic statistical model that randomizer the spectrum allocation problem for self-organizing terminals. Through the model, we simplify the power control algorithm with convex optimization method. Simulation shows that our proposed distributed admission and power control (DAPC) algorithm can improve the Signal to Interference plus Noise Ratio of users mostly 5-10dB. Even the network changes during the communication process, this algorithm also province that the interference is acceptable.
UTRAN Long Term Evolution (LTE), marked as 4G LTE, is a standard for wireless communication developed by 3GPP, which is aiming to provide a spectral efficiency 2 to 4 times higher than its predecessor HS UPA/HS DPA Release 6. As a downlink access scheme for LTE, the Orthogonal Frequency Division Multiple Access (OFDMA) technology can allocate resources flexibly at the cost of additional control signals, so this will limit the throughput of the system. In this paper, we propose a new algorithm, named as Resource Allocation with Shared Channel and Control Channel (RA-SCCC) algorithm to be able to achieve the maximum possible throughput. The simulation result indicated two major conclusions: one is that the RA-S CCC algorithm in this paper could gain 40% ~ 80% throughput than the Roundup Robin algorithm and the other is that the RA-S CCC could provide the better fairness relative to the Max C/I algorithm.
Device to device (D2D) multi-hop communication in multicast networks solves the contradiction between high speed requirements and limited bandwidth in regional data sharing communication services. However, most networking models demand a large control overhead in eNodeB. Moreover, the topology should be calculated again due to the mobility of terminals, which causes the long delay. In this work, we model multicast network construction in D2D communication through a fuzzy mathematics and game theory based algorithm. In resource allocation, we assume that user equipment (UE) can detect the available frequency and the fuzzy mathematics is introduced to describe an uncertain relationship between the resource and UE distributedly, which diminishes the time delay. For forming structure, a distributed myopic best response dynamics formation algorithm derived from a novel concept from the coalitional game theory is proposed, in which every UE can self-organize into stable structure without the control from eNodeB to improve its utilities in terms of rate and bit error rate (BER) while accounting for a link maintenance cost, and adapt this topology to environmental changes such as mobility while converging to a Nash equilibrium fast. Simulation results show that the proposed architecture converges to a tree network quickly and presents significant gains in terms of average rate utility reaching up to 50% compared to the star topology where all of the UE is directly connected to eNodeB.
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