9,399 research outputs found
Opportunistic Access in Frequency Hopping Cognitive Radio Networks
Researchers in the area of cognitive radio often investigate the utility of dynamic spectrum access as a means to make more efficient use of the radio frequency spectrum. Many studies have been conducted to find ways in which a secondary user can occupy spectrum licensed to a primary user in a manner which does not disrupt the primary user\u27s performance. This research investigates the use of opportunistic access in a frequency hopping radio to mitigate the interference caused by other transmitters in a contentious environment such as the unlicensed 2.4 GHz region. Additionally, this work demonstrates how dynamic spectrum access techniques can be used not only to prevent interfering with other users but also improve the robustness of a communication system
Multihop Rendezvous Algorithm for Frequency Hopping Cognitive Radio Networks
Cognitive radios allow the possibility of increasing utilization of the wireless spectrum, but because of their dynamic access nature require new techniques for establishing and joining networks, these are known as rendezvous. Existing rendezvous algorithms assume that rendezvous can be completed in a single round or hop of time. However, cognitive radio networks utilizing frequency hopping that is too fast for synchronization packets to be exchanged in a single hop require a rendezvous algorithm that supports multiple hop rendezvous. We propose the Multiple Hop (MH) rendezvous algorithm based on a pre-shared sequence of random numbers, bounded timing differences, and similar channel lists to successfully match a percentage of hops. It is tested in simulation against other well known rendezvous algorithms and implemented in GNU Radio for the HackRF One. We found from the results of our simulation testing that at 100 hops per second the MH algorithm is faster than other tested algorithms at 50 or more channels with timing ±50 milliseconds, at 250 or more channels with timing ±500 milliseconds, and at 2000 channels with timing ±5000 milliseconds. In an asymmetric environment with 100 hops per second, a 500 millisecond timing difference, and 1000 channels the MH algorithm was faster than other tested algorithms as long as the channel overlap was 35% or higher for a 50% required packet success to complete rendezvous. We recommend the Multihop algorithm for use cases with a fast frequency hop rate and a slow data transmission rate requiring multiple hops to rendezvous or use cases where the channel count equals or exceeds 250 channels, as long as timing data is available and all of the radios to be connected to the network can be pre-loaded with a shared seed
Optimizing Average-Maximum TTR Trade-off for Cognitive Radio Rendezvous
In cognitive radio (CR) networks, "TTR", a.k.a. time-to-rendezvous, is one of
the most important metrics for evaluating the performance of a channel hopping
(CH) rendezvous protocol, and it characterizes the rendezvous delay when two
CRs perform channel hopping. There exists a trade-off of optimizing the average
or maximum TTR in the CH rendezvous protocol design. On one hand, the random CH
protocol leads to the best "average" TTR without ensuring a finite "maximum"
TTR (two CRs may never rendezvous in the worst case), or a high rendezvous
diversity (multiple rendezvous channels). On the other hand, many
sequence-based CH protocols ensure a finite maximum TTR (upper bound of TTR)
and a high rendezvous diversity, while they inevitably yield a larger average
TTR. In this paper, we strike a balance in the average-maximum TTR trade-off
for CR rendezvous by leveraging the advantages of both random and
sequence-based CH protocols. Inspired by the neighbor discovery problem, we
establish a design framework of creating a wake-up schedule whereby every CR
follows the sequence-based (or random) CH protocol in the awake (or asleep)
mode. Analytical and simulation results show that the hybrid CH protocols under
this framework are able to achieve a greatly improved average TTR as well as a
low upper-bound of TTR, without sacrificing the rendezvous diversity.Comment: Accepted by IEEE International Conference on Communications (ICC
2015, http://icc2015.ieee-icc.org/
Decentralized Dynamic Hop Selection and Power Control in Cognitive Multi-hop Relay Systems
In this paper, we consider a cognitive multi-hop relay secondary user (SU)
system sharing the spectrum with some primary users (PU). The transmit power as
well as the hop selection of the cognitive relays can be dynamically adapted
according to the local (and causal) knowledge of the instantaneous channel
state information (CSI) in the multi-hop SU system. We shall determine a low
complexity, decentralized algorithm to maximize the average end-to-end
throughput of the SU system with dynamic spatial reuse. The problem is
challenging due to the decentralized requirement as well as the causality
constraint on the knowledge of CSI. Furthermore, the problem belongs to the
class of stochastic Network Utility Maximization (NUM) problems which is quite
challenging. We exploit the time-scale difference between the PU activity and
the CSI fluctuations and decompose the problem into a master problem and
subproblems. We derive an asymptotically optimal low complexity solution using
divide-and-conquer and illustrate that significant performance gain can be
obtained through dynamic hop selection and power control. The worst case
complexity and memory requirement of the proposed algorithm is O(M^2) and
O(M^3) respectively, where is the number of SUs
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