Sum-rate maximisation comparison using incremental approaches with different constraints

In this work, the problem of rate maximisation of multichannel systems is considered. Two greedy allocation approaches using power (GPA) and bit (GBA) loading schemes with a slight difference in design constraints that aiming to maximise the overall system throughput are compared. Both algorithms use incremental bit loading whereby, the GPA is designed with main interest of efficient power utilisation. Whereas, the GBA sacrifices power utilisation to another design issue of achieving an average bit error ratio (BER) less than the target BER. Simulation results shows that with GPA algorithm better throughput is gained over the GBA algorithm while the latter guaranteed less BER

The linear time optimal control problem from a calculus of variations point of view

Linear time optimal control problem and calculus of variation

Bounded state variables and the calculus of variations

An optimal control problem with bounded state variables is transformed into a Lagrange problem by means of differentiable mappings which take some Euclidean space onto the control and state regions. Whereas all such mappings lead to a Lagrange problem, it is shown that only those which are defined as acceptable pairs of transformations are suitable in the sense that solutions to the transformed Lagrange problem will lead to solutions to the original bounded state problem and vice versa. In particular, an acceptable pair of transformations is exhibited for the case when the control and state regions are right parallelepipeds. Finally, a description of the necessary conditions for the bounded state problem which were obtained by this method is given

Trade-off between complexity and BER performance of a polynomial SVD-based broadband MIMO transceiver

In this paper we investigate non-linear precoding solutions for the problem of broadband multiple-input multiple output(MIMO) systems. Based on a polynomial singular value decomposition (PSVD) we can decouple a broadband MIMO channel into independent dispersive spectrally majorised single-input single-output (SISO) subchannels. In this contribution, the focus of our work is to explore the influence of approximations on the PSVD, and the performance degradation that can be expected as a result

Reduced complexity schemes to greedy power allocation for multicarrier systems

Discrete bit loading for multicarrier systems based on the greedy power allocation (GPA) algorithm is considered in this paper. A new suboptimal scheme that independently performs GPA on groups of subcarriers and therefore can significantly reduce complexity compared to the standard GPA is proposed. These groups are formed in an initial step of a uniform power allocation (UPA) algorithm. In order to more efficiently allocate the available transmit power, two power re-distribution algorithms are further introduced by including a transfer of residual power between groups. Simulation results show that the two proposed algorithms can achieve near optimal performance in two separate and distinctive SNR regions. We demonstrate by analysis how these methods can greatly simplify the computational complexity of the GPA algorithm

Greedy power allocation for multicarrier systems with reduced complexity

In this paper we consider a reduced complexity discrete bit loading for Multicarrier systems based on the greedy power allocation (GPA) under the constraints of transmit power budget, target BER, and maximum permissible QAM modulation order. Compared to the standard GPA, which is optimal in terms of maximising the data throughput, three suboptimal schemes are proposed, which perform GPA on subsets of subcarriers only. These subsets are created by considering the minimum SNR boundaries of QAM levels for a given BER. We demonstrate how these schemes can reduce complexity. Two of the proposed algorithms can achieve near optimal performance by including a transfer of residual power between groups at the expense of a very small extra cost. It is shown that the two near optimal schemes,while greatly reducing complexity, perform best in two separate and distinct SNR regions

A Built-in Inflation in the f(T)f(T)-Cosmology

In the present work we derive an exact solution of an isotropic and homogeneous Universe governed by $f(T)$ gravity. We show how the torsion contribution to the FRW cosmology can provide a \textit{unique} origin for both early and late acceleration phases of the Universe. The three models ($k=0, \pm 1$) show a \textit{built-in} inflationary behavior at some early Universe time; they restore suitable conditions for the hot big bang nucleosynthesis to begin. Unlike the standard cosmology, we show that even if the Universe initially started with positive or negative sectional curvatures, the curvature density parameter enforces evolution to a flat Universe. The solution constrains the torsion scalar $T$ to be a constant function at all time $t$, for the three models. This eliminates the need for the dark energy (DE). Moreover, when the continuity equation is assumed for the torsion fluid, we show that the flat and closed Universe models \textit{violate} the conservation principle, while the open one does not. The evolution of the effective equation of state (EoS) of the torsion fluid implies a peculiar trace from a quintessence-like DE to a phantom-like one crossing a matter and radiation EoS in between; then it asymptotically approaches a de Sitter fate.Comment: LaTeX2e: 19 pages, 9 figures, 1 table. Version 4 Published versio