1,019 research outputs found
Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret
The problem of distributed learning and channel access is considered in a
cognitive network with multiple secondary users. The availability statistics of
the channels are initially unknown to the secondary users and are estimated
using sensing decisions. There is no explicit information exchange or prior
agreement among the secondary users. We propose policies for distributed
learning and access which achieve order-optimal cognitive system throughput
(number of successful secondary transmissions) under self play, i.e., when
implemented at all the secondary users. Equivalently, our policies minimize the
regret in distributed learning and access. We first consider the scenario when
the number of secondary users is known to the policy, and prove that the total
regret is logarithmic in the number of transmission slots. Our distributed
learning and access policy achieves order-optimal regret by comparing to an
asymptotic lower bound for regret under any uniformly-good learning and access
policy. We then consider the case when the number of secondary users is fixed
but unknown, and is estimated through feedback. We propose a policy in this
scenario whose asymptotic sum regret which grows slightly faster than
logarithmic in the number of transmission slots.Comment: Submitted to IEEE JSAC on Advances in Cognitive Radio Networking and
Communications, Dec. 2009, Revised May 201
Decentralized Fair Scheduling in Two-Hop Relay-Assisted Cognitive OFDMA Systems
In this paper, we consider a two-hop relay-assisted cognitive downlink OFDMA
system (named as secondary system) dynamically accessing a spectrum licensed to
a primary network, thereby improving the efficiency of spectrum usage. A
cluster-based relay-assisted architecture is proposed for the secondary system,
where relay stations are employed for minimizing the interference to the users
in the primary network and achieving fairness for cell-edge users. Based on
this architecture, an asymptotically optimal solution is derived for jointly
controlling data rates, transmission power, and subchannel allocation to
optimize the average weighted sum goodput where the proportional fair
scheduling (PFS) is included as a special case. This solution supports
decentralized implementation, requires small communication overhead, and is
robust against imperfect channel state information at the transmitter (CSIT)
and sensing measurement. The proposed solution achieves significant throughput
gains and better user-fairness compared with the existing designs. Finally, we
derived a simple and asymptotically optimal scheduling solution as well as the
associated closed-form performance under the proportional fair scheduling for a
large number of users. The system throughput is shown to be
, where is the
number of users in one cluster, is the number of subchannels and is
the active probability of primary users.Comment: 29 pages, 9 figures, IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL
PROCESSIN
A Hop-by-Hop Relay Selection Strategy in Multi-Hop Cognitive Relay Networks
In this paper, a hop-by-hop relay selection strategy for multi-hop underlay cognitive relay networks (CRNs) is proposed. In each stage, relays that successfully decode the message from previous hop form a decoding set. Taking both maximum transmit power and maximum interference constraints into consideration, the relay in the decoding set which has the largest number of channels with an acceptable signal-to-noise ratio (SNR) level to the relays in the next stage is selected for retransmission. Therefore, relay selection in each stage only relies on channel state information (CSI) of the channels in that stage and does not require the CSI of any other stage. We analyze the performance of the proposed strategy in terms of endto-end outage probability and throughput, and show that the results match those obtained from simulation closely. Moreover, we derive the asymptotic end-to-end outage probability of the proposed strategy when there is no upper bound on transmitters’ power. We compare this strategy to other hop-by-hop strategies that have appeared recently in the literature and show that this strategy has the best performance in terms of outage probability and throughput. Finally it is shown that the outage probability and throughput of the proposed strategy are very close to that of exhaustive strategy which provides a lower bound for outage probability and an upper bound for throughput of all path selection strategies
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