1,335 research outputs found
Interference-Aware Downlink Resource Management for OFDMA Femtocell Networks
Femtocell is an economical solution to provide high speed indoor communication instead of the conventional macro-cellular networks. Especially, OFDMA femtocell is considered in the next generation cellular network such as 3GPP LTE and mobile WiMAX system. Although the femtocell has great advantages to accommodate indoor users, interference management problem is a critical issue to operate femtocell network. Existing OFDMA resource management algorithms only consider optimizing system-centric metric, and cannot manage the co-channel interference. Moreover, it is hard to cooperate with other femtocells to control the interference, since the self-configurable characteristics of femtocell. This paper proposes a novel interference-aware resource allocation algorithm for OFDMA femtocell networks. The proposed algorithm allocates resources according to a new objective function which reflects the effect of interference, and the heuristic algorithm is also introduced to reduce the complexity of the original problem. The Monte-Carlo simulation is performed to evaluate the performance of the proposed algorithm compared to the existing solutions
Spectral Efficiency of Multi-User Adaptive Cognitive Radio Networks
In this correspondence, the comprehensive problem of joint power, rate, and
subcarrier allocation have been investigated for enhancing the spectral
efficiency of multi-user orthogonal frequency-division multiple access (OFDMA)
cognitive radio (CR) networks subject to satisfying total average transmission
power and aggregate interference constraints. We propose novel optimal radio
resource allocation (RRA) algorithms under different scenarios with
deterministic and probabilistic interference violation limits based on a
perfect and imperfect availability of cross-link channel state information
(CSI). In particular, we propose a probabilistic approach to mitigate the total
imposed interference on the primary service under imperfect cross-link CSI. A
closed-form mathematical formulation of the cumulative density function (cdf)
for the received signal-to-interference-plus-noise ratio (SINR) is formulated
to evaluate the resultant average spectral efficiency (ASE). Dual decomposition
is utilized to obtain sub-optimal solutions for the non-convex optimization
problems. Through simulation results, we investigate the achievable performance
and the impact of parameters uncertainty on the overall system performance.
Furthermore, we present that the developed RRA algorithms can considerably
improve the cognitive performance whilst abide the imposed power constraints.
In particular, the performance under imperfect cross-link CSI knowledge for the
proposed `probabilistic case' is compared to the conventional scenarios to show
the potential gain in employing this scheme
Efficient Heuristic for Resource Allocation in Zero-forcing OFDMA-SDMA Systems with Minimum Rate Constraints
4G wireless access systems require high spectral efficiency to support the
ever increasing number of users and data rates for real time applications.
Multi-antenna OFDM-SDMA systems can provide the required high spectral
efficiency and dynamic usage of the channel, but the resource allocation
process becomes extremely complex because of the augmented degrees of freedom.
In this paper, we propose two heuristics to solve the resource allocation
problem that have very low computational complexity and give performances not
far from the optimal. The proposed heuristics select a set of users for each
subchannel, but contrary to the reported methods that solve the throughput
maximization problem, our heuristics consider the set of real-time (RT) users
to ensure that their minimum rate requirements are met. We compare the
heuristics' performance against an upper bound and other methods proposed in
the literature and find that they give a somewhat lower performance, but
support a wider range of minimum rates while reducing the computational
complexity. The gap between the objective achieved by the heuristics and the
upper bound is not large. In our experiments this gap is 10.7% averaging over
all performed numerical evaluations for all system configurations. The increase
in the range of the supported minimum rates when compared with a method
reported in the literature is 14.6% on average.Comment: 8 figure
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