539 research outputs found
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
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
Delay aware optimal resource allocation in MU MIMO-OFDM using enhanced spider monkey optimization
In multiple users MIMO- OFDM system allocates the available resources to the optimal users is a difficult task. Hence the scheduling and resource allocation become the major problem in the wireless network mainly in case of multiple input and multiple output method that has to be made efficient. There is various method introduced to give an optimal solution to the problem yet it has many drawbacks. So we propose this paper to provide an efficient solution for resource allocation in terms of delay and also added some more features such as high throughout, energy efficient and fairness. To make optimal resource allocation we introduce optimization algorithm named spider monkey with an enhancement which provides the efficient solution. In this optimization process includes the scheduling and resource allocation, the SNR values, channel state information (CSI) from the base station. To make more efficient finally we perform enhanced spider - monkey algorithm hence the resource allocation is performed based on QoS requirements. Thus the simulation results in our paper show high efficiency when compared with other schedulers and techniques
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
Weighted Max-Min Resource Allocation for Frequency Selective Channels
In this paper, we discuss the computation of weighted max-min rate allocation
using joint TDM/FDM strategies under a PSD mask constraint. We show that the
weighted max-min solution allocates the rates according to a predetermined rate
ratio defined by the weights, a fact that is very valuable for
telecommunication service providers. Furthermore, we show that the problem can
be efficiently solved using linear programming. We also discuss the resource
allocation problem in the mixed services scenario where certain users have a
required rate, while the others have flexible rate requirements. The solution
is relevant to many communication systems that are limited by a power spectral
density mask constraint such as WiMax, Wi-Fi and UWB
- …