2,182 research outputs found
Resource Allocation for Delay Differentiated Traffic in Multiuser OFDM Systems
Most existing work on adaptive allocation of subcarriers and power in
multiuser orthogonal frequency division multiplexing (OFDM) systems has focused
on homogeneous traffic consisting solely of either delay-constrained data
(guaranteed service) or non-delay-constrained data (best-effort service). In
this paper, we investigate the resource allocation problem in a heterogeneous
multiuser OFDM system with both delay-constrained (DC) and
non-delay-constrained (NDC) traffic. The objective is to maximize the sum-rate
of all the users with NDC traffic while maintaining guaranteed rates for the
users with DC traffic under a total transmit power constraint. Through our
analysis we show that the optimal power allocation over subcarriers follows a
multi-level water-filling principle; moreover, the valid candidates competing
for each subcarrier include only one NDC user but all DC users. By converting
this combinatorial problem with exponential complexity into a convex problem or
showing that it can be solved in the dual domain, efficient iterative
algorithms are proposed to find the optimal solutions. To further reduce the
computational cost, a low-complexity suboptimal algorithm is also developed.
Numerical studies are conducted to evaluate the performance the proposed
algorithms in terms of service outage probability, achievable transmission rate
pairs for DC and NDC traffic, and multiuser diversity.Comment: 29 pages, 8 figures, submitted to IEEE Transactions on Wireless
Communication
Resource allocation for transmit hybrid beamforming in decoupled millimeter wave multiuser-MIMO downlink
This paper presents a study on joint radio resource allocation and hybrid precoding in multicarrier massive multiple-input multiple-output communications for 5G cellular networks. In this paper, we present the resource allocation algorithm to maximize the proportional fairness (PF) spectral efficiency under the per subchannel power and the beamforming rank constraints. Two heuristic algorithms are designed. The proportional fairness hybrid beamforming algorithm provides the transmit precoder with a proportional fair spectral efficiency among users for the desired number of radio-frequency (RF) chains. Then, we transform the number of RF chains or rank constrained optimization problem into convex semidefinite programming (SDP) problem, which can be solved by standard techniques. Inspired by the formulated convex SDP problem, a low-complexity, two-step, PF-relaxed optimization algorithm has been provided for the formulated convex optimization problem. Simulation results show that the proposed suboptimal solution to the relaxed optimization problem is near-optimal for the signal-to-noise ratio SNR <= 10 dB and has a performance gap not greater than 2.33 b/s/Hz within the SNR range 0-25 dB. It also outperforms the maximum throughput and PF-based hybrid beamforming schemes for sum spectral efficiency, individual spectral efficiency, and fairness index
SYNCHRONIZATION AND RESOURCE ALLOCATION IN DOWNLINK OFDM SYSTEMS
The next generation (4G) wireless systems are expected to provide
universal personal and multimedia communications with seamless connection
and very high rate transmissions and without regard to the users’ mobility and
location. OFDM technique is recognized as one of the leading candidates to
provide the wireless signalling for 4G systems. The major challenges in
downlink multiuser OFDM based 4G systems include the wireless channel, the
synchronization and radio resource management. Thus algorithms are required
to achieve accurate timing and frequency offset estimation and the efficient
utilization of radio resources such as subcarrier, bit and power allocation.
The objectives of the thesis are of two fields. Firstly, we presented the
frequency offset estimation algorithms for OFDM systems. Building our work
upon the classic single user OFDM architecture, we proposed two FFT-based
frequency offset estimation algorithms with low computational complexity.
The computer simulation results and comparisons show that the proposed
algorithms provide smaller error variance than previous well-known algorithm.
Secondly, we presented the resource allocation algorithms for OFDM
systems. Building our work upon the downlink multiuser OFDM architecture,
we aimed to minimize the total transmit power by exploiting the system
diversity through the management of subcarrier allocation, adaptive
modulation and power allocation. Particularly, we focused on the dynamic
resource allocation algorithms for multiuser OFDM system and multiuser
MIMO-OFDM system. For the multiuser OFDM system, we proposed a lowiv
complexity channel gain difference based subcarrier allocation algorithm. For
the multiuser MIMO-OFDM system, we proposed a unit-power based
subcarrier allocation algorithm. These proposed algorithms are all combined
with the optimal bit allocation algorithm to achieve the minimal total transmit
power. The numerical results and comparisons with various conventional nonadaptive
and adaptive algorithmic approaches are provided to show that the
proposed resource allocation algorithms improve the system efficiencies and
performance given that the Quality of Service (QoS) for each user is
guaranteed.
The simulation work of this project is based on hand written codes in the
platform of the MATLAB R2007b
Resource Allocation for Outdoor-to-Indoor Multicarrier Transmission with Shared UE-side Distributed Antenna Systems
In this paper, we study the resource allocation algorithm design for downlink
multicarrier transmission with a shared user equipment (UE)-side distributed
antenna system (SUDAS) which utilizes both licensed and unlicensed frequency
bands for improving the system throughput. The joint UE selection and
transceiver processing matrix design is formulated as a non-convex optimization
problem for the maximization of the end-to-end system throughput (bits/s). In
order to obtain a tractable resource allocation algorithm, we first show that
the optimal transmitter precoding and receiver post-processing matrices jointly
diagonalize the end-to-end communication channel. Subsequently, the
optimization problem is converted to a scalar optimization problem for multiple
parallel channels, which is solved by using an asymptotically optimal iterative
algorithm. Simulation results illustrate that the proposed resource allocation
algorithm for the SUDAS achieves an excellent system performance and provides a
spatial multiplexing gain for single-antenna UEs.Comment: accepted for publication at the IEEE Vehicular Technology Conference
(VTC) Spring, Glasgow, Scotland, UK, May 201
Resource Allocation for Power Minimization in the Downlink of THP-based Spatial Multiplexing MIMO-OFDMA Systems
In this work, we deal with resource allocation in the downlink of spatial
multiplexing MIMO-OFDMA systems. In particular, we concentrate on the problem
of jointly optimizing the transmit and receive processing matrices, the channel
assignment and the power allocation with the objective of minimizing the total
power consumption while satisfying different quality-of-service requirements. A
layered architecture is used in which users are first partitioned in different
groups on the basis of their channel quality and then channel assignment and
transceiver design are sequentially addressed starting from the group of users
with most adverse channel conditions. The multi-user interference among users
belonging to different groups is removed at the base station using a
Tomlinson-Harashima pre-coder operating at user level. Numerical results are
used to highlight the effectiveness of the proposed solution and to make
comparisons with existing alternatives.Comment: 12 pages, 6 figures, IEEE Trans. Veh. Techno
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