157,742 research outputs found
Generalised MBER-based vector precoding design for multiuser transmission
We propose a generalized vector precoding (VP) design based on the minimum bit error rate (MBER) criterion for multiuser transmission in the downlink of a multiuser system, where the base station (BS) equipped with multiple transmitting antennas communicates with single-receiving-antenna mobile station (MS) receivers each having a modulo device. Given the knowledge of the channel state information and the current information symbol vector to be transmitted, our scheme directly generates the effective symbol vector based on the MBER criterion using the particle swarm optimization (PSO) algorithm. The proposed PSO-aided generalized MBER VP scheme is shown to outperform the powerful minimum mean-square-error (MMSE) VP and improved MMSE-VP benchmarks, particularly for rank-deficient systems, where the number of BS transmitting antennas is lower than the number of MSs supported
The Right Mutation Strength for Multi-Valued Decision Variables
The most common representation in evolutionary computation are bit strings.
This is ideal to model binary decision variables, but less useful for variables
taking more values. With very little theoretical work existing on how to use
evolutionary algorithms for such optimization problems, we study the run time
of simple evolutionary algorithms on some OneMax-like functions defined over
. More precisely, we regard a variety of
problem classes requesting the component-wise minimization of the distance to
an unknown target vector . For such problems we see a crucial
difference in how we extend the standard-bit mutation operator to these
multi-valued domains. While it is natural to select each position of the
solution vector to be changed independently with probability , there are
various ways to then change such a position. If we change each selected
position to a random value different from the original one, we obtain an
expected run time of . If we change each selected position
by either or (random choice), the optimization time reduces to
. If we use a random mutation strength with probability inversely proportional to and change
the selected position by either or (random choice), then the
optimization time becomes , bringing down
the dependence on from linear to polylogarithmic. One of our results
depends on a new variant of the lower bounding multiplicative drift theorem.Comment: an extended abstract of this work is to appear at GECCO 201
Optimal resource allocation for route selection in ad-hoc networks
Nowadays, the selection of the optimum path in mobile ad hoc networks (MANETS) is being an important issue that should be solved smartly. In this paper, an optimal path selection method is proposed for MANET using the Lagrange multiplier approach. The optimization problem considers the objective function of maximizing bit rate, under the constraints of minimizing the packet loss, and latency. The obtained simulation results show that the proposed Lagrange optimization of rate, delay, and packet loss algorithm (LORDP) improves the selection of optimal path in comparison to ad-hoc on-demand distance vector protocol (AODV). We increased the performance of the system by 10.6 Mbps for bit rate and 0.133 ms for latency
Transceiver design with vector perturbation technique and iterative power loading
In this paper we consider the optimization of transceivers which use the nonlinear vector perturbation technique at the transmitter. Since the perturbation vector can be almost totally removed at the receiver, the transmitter can use this extra freedom to reduce the transmitted power while maintaining the performance. The two cases considered in this paper are linear transceivers and transceivers with decision feedback (DFE). For both cases, efficient iterative power loading algorithms are developed to reduce the average bit error rate under the total transmitted power constraint. We present simulation results showing that the proposed technique performs better than the existing state-of-the-art uniform channel decomposition (UCD) system and the vector perturbation (VP) precoder
- âŠ