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

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

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

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

A Computationally Efficient Discrete Bit-Loading Algorithm for OFDM Systems Subject to Spectral-Compatibility Limits

International audienceThis paper considers bit-loading algorithms to maximize throughput under total power and spectral mask constraints in interference-free OFDM systems. The contribution is twofold. First, we propose a simple criterion to switch between two wellknown algorithms from the literature: the conventional Greedy and Greedy-based bit-removing (with maximum allowable bit loading initialization) algorithms. Second, we present a new lowcomplexity loading algorithm that exploits the bit vector obtained by rounding the water-filling algorithm solution to the associated continuous-input rate maximization problem as an efficient initial bit vector of the Greedy algorithm.We theoretically prove that this bit vector has two interesting properties. The first one states that it is an efficient bit vector, i.e., there is no movement of a bit from one subcarrier to another that reduces the total used power. The second one states that the optimized throughput, starting from this initial bit vector, is achieved by adding or removing bits on each subcarrier at most once. Simulation results show the efficiency of the proposed algorithm, i.e., the achievable throughput is maximized with significant reduction of computation cost as compared to many algorithms in the literature

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

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

Adaptive Spread Spectrum Multicarrier Multiple Access over Wirelines

In this paper, we investigate the dynamic resource allocation adapted to spread spectrum multicarrier multiple access (SS-MC-MA) systems in a multiuser power line communication (PLC) context. The developed adaptive system is valid for uplink, downlink, as well as for indoor and outdoor communications. The studied SS-MC-MA system is based on classical multicarrier modulation like DMT, combined with a spread-spectrum (SS) component used to multiplex several information symbols of a given user over the same subcarriers. The multiple access task is carried out using a frequency division multiple access (FDMA) approach so that each user is assigned one or more subcarrier sets. The number of subcarriers in each set is given by the spreading code length as in classical SS-MC-MA systems usually studied in the wireless context. We derive herein a new loading algorithm that dynamically handles the system conguration in order to maximize the data throughput. The algorithm consists in an adaptive subcarrier, code, bit and energy assignment algorithm. Power spectral density constraint due to spectral mask specications is considered as well as nite order modulations. In that case, it is shown that SS-MC-MA combined with the proposed loading algorithm achieves higher throughput than DMT in a multiuser PLC context. Because of the nite granularity of the modulations, some residual energy is indeed wasted on each subcarrier of the DMT spectrum. The combining of a spreading component with digital multitone (DMT) allows to merge these amounts of energy so that one or more additional bits can be transmitted in each subcarrier subset leading to signicant throughput gain. Simulations have been run over measured PLC channel responses and highlight that the proposed system is all the more interesting than the SNR is low

Allocation de débit à faible complexité dans les systèmes OFDM en présence de contraintes spectrales

National audienceCet article traite de la maximisation du débit dans les systèmes OFDM soumis à des contraintes de limitation de la puissance. Nous proposons un algorithme d'allocation glouton dans lequel le vecteur de bits initial est la discrétisation par arrondi de la solution "Water-Filling" du problème continu associé. Nous montrons théoriquement que ce vecteur est "efficace", c'est-àdire qu'il n'existe pas de mouvement d'un bit d'une sous-porteuse à l'autre qui réduise la puissance totale utilisée. Les résultats de simulation montrent l'efficacité de l'algorithme proposé : le débit réalisable est maximisé avec une réduction significative du coût de calcul par rapport à des algorithmes de référence de la littérature

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