1,096 research outputs found
Incremental rate maximisation power loading with BER improvements
This paper aims to maximise the rate over a MIMO link using incremental power and bit allocation. Two different schemes, greedy power allocation (GPA) and greedy bit allocation (GBA), are addressed and compared with the standard uniform power allocation (UPA). The design is constrained by the target BER, the total power budget, and fixed discrete modulation orders. We demonstrate through simulations that GPA outperforms GBA in terms of throughput and power conservation,while GBA is advantageouswhen a lower BER is beneficial. Once the design constraints are satisfied, remaining power is utilised in two possible ways, leading to improved performance of GPA and UPA algorithms. This redistribution is analysed for fairness in BER performance across all active subchannels using a bisection method
Coded Adaptive Linear Precoded Discrete Multitone Over PLC Channel
Discrete multitone modulation (DMT) systems exploit the capabilities of
orthogonal subcarriers to cope efficiently with narrowband interference, high
frequency attenuations and multipath fadings with the help of simple
equalization filters. Adaptive linear precoded discrete multitone (LP-DMT)
system is based on classical DMT, combined with a linear precoding component.
In this paper, we investigate the bit and energy allocation algorithm of an
adaptive LP-DMT system taking into account the channel coding scheme. A coded
adaptive LPDMT system is presented in the power line communication (PLC)
context with a loading algorithm which accommodates the channel coding gains in
bit and energy calculations. The performance of a concatenated channel coding
scheme, consisting of an inner Wei's 4-dimensional 16-states trellis code and
an outer Reed-Solomon code, in combination with the proposed algorithm is
analyzed. Theoretical coding gains are derived and simulation results are
presented for a fixed target bit error rate in a multicarrier scenario under
power spectral density constraint. Using a multipath model of PLC channel, it
is shown that the proposed coded adaptive LP-DMT system performs better than
coded DMT and can achieve higher throughput for PLC applications
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
Robustness maximization of parallel multichannel systems
Bit error rate (BER) minimization and SNR-gap maximization, two robustness
optimization problems, are solved, under average power and bit-rate
constraints, according to the waterfilling policy. Under peak-power constraint
the solutions differ and this paper gives bit-loading solutions of both
robustness optimization problems over independent parallel channels. The study
is based on analytical approach with generalized Lagrangian relaxation tool and
on greedy-type algorithm approach. Tight BER expressions are used for square
and rectangular quadrature amplitude modulations. Integer bit solution of
analytical continuous bit-rates is performed with a new generalized secant
method. The asymptotic convergence of both robustness optimizations is proved
for both analytical and algorithmic approaches. We also prove that, in
conventional margin maximization problem, the equivalence between SNR-gap
maximization and power minimization does not hold with peak-power limitation.
Based on a defined dissimilarity measure, bit-loading solutions are compared
over power line communication channel for multicarrier systems. Simulation
results confirm the asymptotic convergence of both allocation policies. In non
asymptotic regime the allocation policies can be interchanged depending on the
robustness measure and the operating point of the communication system. The low
computational effort of the suboptimal solution based on analytical approach
leads to a good trade-off between performance and complexity.Comment: 27 pages, 8 figures, submitted to IEEE Trans. Inform. Theor
Suboptimal greedy power allocation schemes for discrete bit loading
In this paper we consider low cost discrete bit loading based on greedy power allocation (GPA) under the constraints of total 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 subchannels only. These subsets are created by considering the minimum SNR boundaries of QAM levels for a given target BER. We demonstrate how these schemes can significantly reduce the computational complexity required for power allocation, particularly in the case of a large number of subchannels. Two of the proposed algorithms can achieve near optimal performance including a transfer of residual power between subsets at the expense of a very small extra cost. By simulations, we show that the two near optimal schemes, while greatly reducing complexity, perform best in two separate and distinct SNR regions
A Coded Bit-Loading Linear Precoded Discrete Multitone Solution for Power Line Communication
Linear precoded discrete multitone modulation (LP-DMT) system has been
already proved advantageous with adaptive resource allocation algorithm in a
power line communication (PLC) context. In this paper, we investigate the bit
and energy allocation algorithm of an adaptive LP-DMT system taking into
account the channel coding scheme. A coded adaptive LP-DMT system is presented
in the PLC context with a loading algorithm which ccommodates the channel
coding gains in bit and energy calculations. The performance of a concatenated
channel coding scheme, consisting of an inner Wei's 4-dimensional 16-states
trellis code and an outer Reed-Solomon code, in combination with the roposed
algorithm is analyzed. Simulation results are presented for a fixed target bit
error rate in a multicarrier scenario under power spectral density constraint.
Using a multipath model of PLC channel, it is shown that the proposed coded
adaptive LP-DMT system performs better than classical coded discrete multitone
Suboptimal greedy power allocation schemes for discrete bit loading
In this paper we consider low cost discrete bit loading based on greedy power allocation (GPA) under the constraints of total 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 subchannels only. These subsets are created by considering the minimum SNR boundaries of QAM levels for a given target BER. We demonstrate how these schemes can significantly reduce the computational complexity required for power allocation, particularly in the case of a large number of subchannels. Two of the proposed algorithms can achieve near optimal performance including a transfer of residual power between subsets at the expense of a very small extra cost. By simulations, we show that the two near optimal schemes, while greatly reducing complexity, perform best in two separate and distinct SNR regions
PLC for the smart grid: state-of-the-art and challenges
This paper aims to review systems and applications for power line communications (PLC) in the context of the smart grid. We discuss the main applications and summarise state-of-the-art PLC systems and standards. We report efforts and challenges in channel and noise modelling, as well as in state-of-the-art transmission technology approaches
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