1,847 research outputs found
Optimization Framework and Graph-Based Approach for Relay-Assisted Bidirectional OFDMA Cellular Networks
This paper considers a relay-assisted bidirectional cellular network where
the base station (BS) communicates with each mobile station (MS) using OFDMA
for both uplink and downlink. The goal is to improve the overall system
performance by exploring the full potential of the network in various
dimensions including user, subcarrier, relay, and bidirectional traffic. In
this work, we first introduce a novel three-time-slot time-division duplexing
(TDD) transmission protocol. This protocol unifies direct transmission, one-way
relaying and network-coded two-way relaying between the BS and each MS. Using
the proposed three-time-slot TDD protocol, we then propose an optimization
framework for resource allocation to achieve the following gains: cooperative
diversity (via relay selection), network coding gain (via bidirectional
transmission mode selection), and multiuser diversity (via subcarrier
assignment). We formulate the problem as a combinatorial optimization problem,
which is NP-complete. To make it more tractable, we adopt a graph-based
approach. We first establish the equivalence between the original problem and a
maximum weighted clique problem in graph theory. A metaheuristic algorithm
based on any colony optimization (ACO) is then employed to find the solution in
polynomial time. Simulation results demonstrate that the proposed protocol
together with the ACO algorithm significantly enhances the system total
throughput.Comment: 27 pages, 8 figures, 2 table
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
Maximizing Energy-Efficiency in Multi-Relay OFDMA Cellular Networks
This contribution presents a method of obtaining the optimal power and
subcarrier allocations that maximize the energy-efficiency (EE) of a
multi-user, multi-relay, orthogonal frequency division multiple access (OFDMA)
cellular network. Initially, the objective function (OF) is formulated as the
ratio of the spectral-efficiency (SE) over the power consumption of the
network. This OF is shown to be quasi-concave, thus Dinkelbach's method can be
employed for solving it as a series of parameterized concave problems. We
characterize the performance of the aforementioned method by comparing the
optimal solutions obtained to those found using an exhaustive search.
Additionally, we explore the relationship between the achievable SE and EE in
the cellular network upon increasing the number of active users. In general,
increasing the number of users supported by the system benefits both the SE and
EE, and higher SE values may be obtained at the cost of EE, when an increased
power may be allocated.Comment: 6 pages, 5 figures, 1 table, to appear in Proc. IEEE 2013 56th Global
Communications Conference (GLOBECOM 2013), Atlanta, USA, December, 201
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
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