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

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 new low-cost discrete bit loading using greedy power allocation

In this paper we consider a low cost bit loading based on the greedy power allocation (GPA). Compared to the standard GPA, which is optimal in terms of maximising the data throughput, three suboptimal schemes are suggested, which perform GPA on subsets of subchannels only. 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 subsets at the expense of a very small extra cost. By simulations, we show that the two near optimal schemes 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

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