Consider a cognitive overlaid network (CON) that has two tiers with different
priorities: a primary tier vs. a secondary tier, which is an emerging network scenario
with the advancement of cognitive radio (CR) technologies. The primary tier consists
of randomly distributed primary radios (PRs) of density n, which have an absolute
priority to access the spectrum. The secondary tier consists of randomly distributed
CRs of density m = n^y with y greater than or equal to 1, which can only access the spectrum opportunistically to limit the interference to PRs. In this dissertation, the fundamental limits
of such a network are investigated in terms of the asymptotic throughput and packet
delay performance when m and n approaches infinity. The following two types of
CONs are considered: 1) selfish CONs, in which neither the primary tier nor the
secondary tier is willing to route the packets for the other, and 2) supportive CONs,
in which the secondary tier is willing to route the packets for the primary tier while
the primary tier does not. It is shown that in selfish CONs, both tiers can achieve
the same throughput and delay scaling laws as a stand-alone network. In supportive
CONs, the throughput and delay scaling laws of the primary tier could be significantly
improved with the aid of the secondary tier, while the secondary tier can still achieve
the same throughput and delay scaling laws as a stand-alone network. Finally, the
throughput and packet delay of a CON with a small number of nodes are investigated.
Specifically, we investigate the power and rate control schemes for multiple CR links in the same neighborhood, which operate over multiple channels (frequency bands)
in the presence of PRs with a delay constraint imposed on data transmission. By
further considering practical limitations in spectrum sensing, an efficient algorithm is
proposed to maximize the average sum-rate of the CR links over a finite time horizon
under the constraints on the CR-to-PR interference and the average transmit power
for each CR link. In the proposed algorithm, the PR occupancy of each channel is
modeled as a discrete-time Markov chain (DTMC). Based on such a model, a novel
power and rate control strategy based on dynamic programming (DP) is derived,
which is a function of the spectrum sensing output, the instantaneous channel gains
for the CR links, and the remaining power budget for the CR transmitter. Simulation results show that the proposed algorithm leads to a significant performance
improvement over heuristic algorithms.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2009-12-7531 |
| Date | 2009 December 1900 |
| Creators | Gao, Long |
| Contributors | Cui, Shuguang |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | application/pdf |
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