Multi-objective and Financial Portfolio Optimization of Carrier-Sense Multiple Access Protocols with Cooperative Diversity

This paper presents a trade-off design and optimization of a class of wireless carrier-sense multiple access protocols where collision-free transmissions are assisted by the potential cooperative retransmissions of inactive terminals with a correct copy of the original transmission. Terminals are enabled with a decode-and-forward relaying protocol. The analysis is focused on asymmetrical settings, where terminals experience different channel and queuing statistics. This work is based on multi-objective and financial portfolio optimization tools. Each packet transmission is thus regarded not only as a network resource, but also as a financial asset with different values of return and risk (or variance of the return). The objective of this financial optimization is to find the transmission policy that simultaneously maximizes return and minimizes risk in the network. The work is focused on the characterization of the boundaries (envelope) of different types of trade-off performance regions: the conventional throughput region, sum-throughput vs. fairness, sum-throughput vs. power, and return vs. risk regions. Fairness is evaluated by means of the Gini-index, which is a metric commonly used in economics to measure income inequality. Transmit power is directly linked to the global transmission rate. The protocol is shown to outperform non-cooperative solutions under different network conditions that are here discussed. Multi-Objective and Financial Portfolio Optimization of Carrier-Sense Multiple Access Protocols with Cooperative Diversity Ramiro Samano-Robles and Atilio Gameiro 1 Research Centre in Real-time and Embedded Computing Systems, Porto, Portugal 2 Instituto de Telecomunicações, Campus Universitário, Aveiro, 3810-193, Portugal. emails:[email protected], [email protected] Abstract. This paper addresses a trade-off design and optimization of a class of wireless carrier-sense multiple access (CSMA) protocols where collision-free transmissions are assisted by the potential cooperative retransmissions of inactive terminals with a correct copy of the original transmission. Terminals are enabled with a decode-and-forward (DF) relaying protocol. The analysis is focused on asymmetrical settings, where terminals explicitly experience different channel and queuing statistics. This work is based on multi-objective and financial portfolio optimization tools. Each packet transmission is thus considered not only as a network resource, but also as a financial asset with different values of return and risk (or variance of the return). The objective of this financial optimization is to find the transmission policy that simultaneously maximizes return and minimizes risk in the network. The work is focused on the characterization of the boundaries (envelope) of different types of trade-off performance regions: the conventional throughput region, sumthroughput vs. fairness, sum-throughput vs. power, and return vs. risk regions. Fairness is evaluated by means of the Gini-index, which is a metric commonly used in economics to measure income inequality. Transmit power is directly linked to the global transmission rate. The protocol is shown to outperform non-cooperative solutions under different network conditions that are discussed in detail in the main body of the paper. This paper addresses a trade-off design and optimization of a class of wireless carrier-sense multiple access (CSMA) protocols where collision-free transmissions are assisted by the potential cooperative retransmissions of inactive terminals with a correct copy of the original transmission. Terminals are enabled with a decode-and-forward (DF) relaying protocol. The analysis is focused on asymmetrical settings, where terminals explicitly experience different channel and queuing statistics. This work is based on multi-objective and financial portfolio optimization tools. Each packet transmission is thus considered not only as a network resource, but also as a financial asset with different values of return and risk (or variance of the return). The objective of this financial optimization is to find the transmission policy that simultaneously maximizes return and minimizes risk in the network. The work is focused on the characterization of the boundaries (envelope) of different types of trade-off performance regions: the conventional throughput region, sumthroughput vs. fairness, sum-throughput vs. power, and return vs. risk regions. Fairness is evaluated by means of the Gini-index, which is a metric commonly used in economics to measure income inequality. Transmit power is directly linked to the global transmission rate. The protocol is shown to outperform non-cooperative solutions under different network conditions that are discussed in detail in the main body of the paper.