1,993 research outputs found
Dynamic Time-domain Duplexing for Self-backhauled Millimeter Wave Cellular Networks
Millimeter wave (mmW) bands between 30 and 300 GHz have attracted
considerable attention for next-generation cellular networks due to vast
quantities of available spectrum and the possibility of very high-dimensional
antenna ar-rays. However, a key issue in these systems is range: mmW signals
are extremely vulnerable to shadowing and poor high-frequency propagation.
Multi-hop relaying is therefore a natural technology for such systems to
improve cell range and cell edge rates without the addition of wired access
points. This paper studies the problem of scheduling for a simple
infrastructure cellular relay system where communication between wired base
stations and User Equipment follow a hierarchical tree structure through fixed
relay nodes. Such a systems builds naturally on existing cellular mmW backhaul
by adding mmW in the access links. A key feature of the proposed system is that
TDD duplexing selections can be made on a link-by-link basis due to directional
isolation from other links. We devise an efficient, greedy algorithm for
centralized scheduling that maximizes network utility by jointly optimizing the
duplexing schedule and resources allocation for dense, relay-enhanced OFDMA/TDD
mmW networks. The proposed algorithm can dynamically adapt to loading, channel
conditions and traffic demands. Significant throughput gains and improved
resource utilization offered by our algorithm over the static,
globally-synchronized TDD patterns are demonstrated through simulations based
on empirically-derived channel models at 28 GHz.Comment: IEEE Workshop on Next Generation Backhaul/Fronthaul Networks -
BackNets 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
Low Complexity WMMSE Power Allocation In NOMA-FD Systems
In this paper we study the problem of power and channel allocation with the
objective of maximizing the system sum-rate for multicarrier non-orthogonal
multiple access (NOMA) full duplex (FD) systems. Such an allocation problem is
non-convex and, thus, with the goal of designing a low complexity solution, we
propose a scheme based on the minimization of the weighted mean square error,
which achieves performance reasonably close to the optimum and allows to
clearly outperforms a conventional orthogonal multiple access approach.
Numerical results assess the effectiveness of our algorithm.Comment: 5 pages conference paper, 3 figures. Submitted on ICASSP 202
Multi-Objective Optimization for Power Efficient Full-Duplex Wireless Communication Systems
In this paper, we investigate power efficient resource allocation algorithm
design for multiuser wireless communication systems employing a full-duplex
(FD) radio base station for serving multiple half-duplex (HD) downlink and
uplink users simultaneously. We propose a multi-objective optimization
framework for achieving two conflicting yet desirable system design objectives,
i.e., total downlink transmit power minimization and total uplink transmit
power minimization, while guaranteeing the quality-of-service of all users. To
this end, the weighted Tchebycheff method is adopted to formulate a
multi-objective optimization problem (MOOP). Although the considered MOOP is
non-convex, we solve it optimally by semidefinite programming relaxation.
Simulation results not only unveil the trade-off between the total downlink and
the total uplink transmit power, but also confirm that the proposed FD system
provides substantial power savings over traditional HD systems.Comment: Accepted for presentation at the IEEE Globecom 2015, San Diego, CA,
USA, Dec. 201
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