Energy-efficient communication techniques typically focus on minimizing the transmission energy only, which is reasonable in long-range applications where the transmission energy is dominant in the total energy consumption. However, in short-range applications such as sensor networks where the circuit energy consumption is comparable to or even dominates the transmission energy, different approaches need to be taken to minimize the total energy consumption. Here, the circuit energy consumption includes the energy consumed by all the circuit blocks along the signal path: analog to digital converter (ADC), digital to analog converter (DAC), frequency synthesizer, mixer, lower noise amplifier (LNA), power amplifier, and baseband DSP. Some joint energy-minimizing techniques have been proposed for SISO systems, where multimode operation with optimized system parameters is investigated. This problem becomes more significant in MIMO systems since the circuit complexity of MIMO structures is much higher than that of SISO structures and it is not clear whether MIMO systems are more energy-efficient than SISO systems due to the high circuit complexity associated with the MIMO structure.
    In this Matlab design the energy consumption of simple MIMO systems and compare the value with that of reference SISO systems under the same throughput and bit-error rate (BER) requirement. The energy efficiency is compared over different transmission distances. Assuming that Alamouti diversity codes are used for the MIMO systems and rest of the design unless otherwise stated, all the statements about MIMO systems are referring to the ones coded with Alamouti diversity codes. Binary phase-shift keying (BPSK)-based systems show SISO systems may be more energy-efficient than MIMO systems when the transmission distance is short. By allowing the constellation size to be optimally chosen, the energy efficiency of MIMO systems can be dramatically increased. For the data transfer in sensor networks shows cooperation among sensors for information transmission and/or reception can reduce energy consumption, as well as transmission delay over some distance ranges.

Reference Paper-1: Energy-Efficiency of MIMO and Cooperative MIMO Techniques in Sensor Networks

Author’s Name: Shuguang Cui, Andrea J. Goldsmith, and Ahmad Bahai

Source: IEEE-Journal on Selected Areas in Communications

Year: 2004

Reference Paper-2: Energy-constrained Modulation Optimization

Author’s Name: Shuguang Cui, Andrea J. Goldsmith, and Ahmad Bahai

Source: IEEE-Transactions on Wireless Communications

Year: 2005

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