Energy-constrained modulation optimization

By Shuguang Cui, Andrea J. Goldsmith, Ahmad Bahai. IEEE Transactions on Wireless Communications, 2005

1,562 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/dece80f4d9cd1264794765cad6b2c584a4e456fb

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In Electrical and Electronic Engineering

Citations in the corpus

Distributed compression-estimation using wireless sensor networks (2006, methodology): “Energy models for uncoded M-QAM transmissions are available in [13], [ 14 ], and [21].”
Energy efficiency in wireless sensor networks: A top-down survey (2014, background): “[67] showed that the energy consumption required to meet a given Bit Error Rate (BER) and delay requirement can be minimised by optimising the transmission time.”
Cross-Layer Design for Lifetime Maximization in Interference-Limited Wireless Sensor Networks (2006, methodology): “The power consumption values of the transmitter circuit (other than the amplifier) and the receiver circuit are modeled as constants P ct and P cr , respectively [5].”
Cross-layer optimization for energy-efficient wireless communications: a survey (2009, background): “In [31], these ideas are extended to a detailed energy consumption analysis specifically for both uncoded and coded M-ary quadrature amplitude modulation (M-QAM) and multiple frequency shift keying (MFSK) in AWGN channels.”
Power scheduling of universal decentralized estimation in sensor networks (2006, methodology): “In addition, we adopt uncoded QAM transmission [ 19 ], [20] of the quantized bits.”
Energy Harvesting Wireless Communications: A Review of Recent Advances (2015, background): “the formulations in [73], [127] are considerably different, their conclusions are the same: since keeping systems powered “on” consumes circuit energy, transmissions should be “bursty,” i.”
Wireless sensor network survey (2008, background): “Modulation optimization: In [111], a detailed analysis of the tradeoff in transmission energy, circuit energy, transmission time, and constellation size for both uncoded and coded M-QAM and M-FSK is studied.”
Voluntary Energy Harvesting Relays and Selection in Cooperative Wireless Networks (2010, background): “The model can be refined further by also accounting for receive energy consumption and transmit circuit inefficiencies [23].”
Energy-Efficient Hybrid Analog and Digital Precoding for MmWave MIMO Systems With Large Antenna Arrays (2015, methodology): “Based on the energy consumption model in [33], [34], the energy efficiency η can be defined as”
Near-Field Communications: A Tutorial Review (2023, methodology): “According to the circuit power consumption model in [112], [113], the total consumed power is calculated as follows: Ptot = ζ −1 eff p+ Pcirc, (155)”
Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks (2004, neutral): “where with the drain efficiency [9] of the RF power amplifier and the peak-to-average ratio (PAR), which is dependent on the modulation scheme and the associated constellation size [6].”
End-to-End Energy Modeling and Analysis of Long-Haul Coherent Transmission Systems (2014, background): “The power consumption of a current-steering DAC has a static component (scales independent of DAC bandwidth or sampling frequency but dependent on DAC resolution) and a dynamic component (scales with DAC sampling frequency and DAC resolution) [47].”
Optimal energy management policies for energy harvesting sensor nodes (2008, background): “, reducing the number of bits to transmit ([2], [3]), by choosing the best modulation strategy ([4]), by using efficient transmission scheduling to take advantage of charge recovery phenomenon ([5]), by exploiting power saving modes (sleep/listen) periodically ([6]), using energy efficient routing (”
A survey of energy-efficient wireless communications (2013, neutral): “It is also shown in [27] that by optimizing the transmission time and the modulation parameters, up to 80% savings in energy is achievable compared with a non-optimized strategy for uncoded systems.”
Energy-Efficient Cooperative Relaying over Fading Channels with Simple Relay Selection (2008, methodology): “This is justifiable as the radio transmission is the dominant component of energy consumption for long range transmissions [22].”