Optimization of Channel Sensing Time and Order
for Cognitive Radios
Ahmed Ewaisha, Ahmed Sultan, Tamer ElBatt
Wireless Intelligent Networks Center (WINC)
School of Communication and Information Technology
Nile University
Cairo, Egypt, 12677
ahmed.ewaisha@nileu.edu.eg
Abstract—In this paper we consider a single cognitive radio
seeking a transmission opportunity by sequentially sensing a
number of statistically independent primary channels. We study
the joint optimization of the time spent to sense a channel, the
decision threshold to determine whether the channel is free
or busy, together with the order with which the channels are
sensed. The sensing time and decision threshold are assumed
to be the same for all channels. The design objective is to
maximize the expected secondary throughput taking sensing
errors into account and penalizing for collisions that may dis-
rupt the primary transmission. Motivated by the computational
complexity of the problem, we propose suboptimal solutions
that significantly reduce the complexity without sacrificing
accuracy. Our results reveal a fundamental trade-off between
minimizing the probability of collision with the primary user via
reducing the sensing errors, which favors a longer sensing time,
and increasing the secondary user’s throughput, which favors
shorter sensing time. The suboptimal approach, for plausible
simulation scenarios, is found to reduce the computational
complexity by more than 89%, while maintaining a near-
optimal throughput within 0.28% of the optimal performance.
1
I. I NTRODUCTION
The rapid growth in wireless communications and net-
working, evidenced by the wide proliferation of mobile
devices, variety of standards and new use cases, gives rise to
the problem of spectrum scarcity. However, recent spectrum
measurement studies [1] have revealed that the assigned
spectrum is used sporadically and, hence, remains largely
under-utilized. This, in turn, has led to the concept of
Dynamic Spectrum Access (DSA), or alternatively cognitive
radios (CRs), which received recent attention in an attempt
to remedy this problem. The notion of DSA hinges on the
assumption that unlicensed users (secondary users) could
access the spectrum, opportunistically, at times and locations
where licensed users (primary users) are inactive.
Spectrum sensing is a major building block in such sys-
tems in order to enable the secondary users to detect the
inactivity of primary users on a particular frequency channel
(i.e., to discover spectrum holes). In this paper, we consider a
secondary terminal that senses a specific number of primary
channels, one at a time, to find a transmission opportunity as
quickly and reliably as possible. The secondary transmitter
relies on conventional energy detection to determine the
1
This work was funded by the Egyptian National Telecommunication
Regulatory Authority (NTRA).
occupancy state of a certain primary channel. Accordingly,
the cognitive transmitter decides, jointly, the optimal order at
which channels has to be sensed, the optimal sensing time,
and the optimal sensing energy threshold based on which the
channel is determined to be busy or free.
The problem of optimal channel selection in cognitive
radio networks has received recent attention in the literature,
e.g., [2]–[6]. In [3], given different channel availability
probabilities and sensing times, the optimal sensing sequence
is to sort the channels in ascending order of the ratio of the
channel sensing time to the channel availability probability.
This result is for the homogeneous channel capacity case,
where all the channels have the exact same capacity. Note
that in [3], the sensing times are fixed for each channel, i.e.,
they are not considered as optimization variables. In addition,
the channel capacities are not considered to be time-varying.
For heterogeneous channel capacities, the problem becomes
NP-hard and is solved via exhaustive search.
In [4], the authors investigate the optimal channel selection
problem assuming error-free sensing. Given a set of channels
and their probing costs, the sender’s objective is to choose
the strategy that maximizes transmission reward minus the
sensing costs. The strategies available to the cognitive ter-
minal are either to transmit on a free channel, or to transmit
on a previously found free channel, or to randomly select an
unprobed channel and use it for transmission. The authors of
[5] build upon the work in [4] by incorporating the possibility
of sensing errors. Although the optimization of the sensing
time is included in [5], the order by which the channels are
sensed is random. When a cognitive radio wishes to transmit,
it starts scanning the channels in a sequential manner. It
randomly picks a channel and samples it for some time, and
then decides whether the channel is idle or busy. If it is busy,
another channel is randomly selected, otherwise the channel
is probed to determine its quality. Depending on this quality,
the channel is either used for transmission or is skipped in
search for a better opportunity.
Perhaps the closest to our work is [2], where a dynamic
programming approach is adopted for finding the optimal
order due to the sequential decision nature of the problem at
hand. In [2], the time incurred for sensing a primary channel
is assumed given and fixed. Although the authors tackle the
issue of imperfect sensing via incorporating the probabilities
of false alarm and misdetection, their formulation does not
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