A New Cooperative MIMO Scheme Based on SM for Energy-Efficiency Improvement in Wireless Sensor Network

Abstract

Improving the energy efficiency in wireless sensor networks (WSN) has attracted considerable attention nowadays. The multiple-input multiple-output (MIMO) technique has been proved as a good candidate for improving the energy efficiency, but it may not be feasible in WSN which is due to the size limitation of the sensor node. As a solution, the cooperative multiple-input multiple-output (CMIMO) technique overcomes this constraint and shows a dramatically good performance. In this paper, a new CMIMO scheme based on the spatial modulation (SM) technique named CMIMO-SM is proposed for energy-efficiency improvement. We first establish the system model of CMIMO-SM. Based on this model, the transmission approach is introduced graphically. In order to evaluate the performance of the proposed scheme, a detailed analysis in terms of energy consumption per bit of the proposed scheme compared with the conventional CMIMO is presented. Later, under the guide of this new scheme we extend our proposed CMIMO-SM to a multihop clustered WSN for further achieving energy efficiency by finding an optimal hop-length. Equidistant hop as the traditional scheme will be compared in this paper. Results from the simulations and numerical experiments indicate that by the use of the proposed scheme, significant savings in terms of total energy consumption can be achieved. Combining the proposed scheme with monitoring sensor node will provide a good performance in arbitrary deployed WSN such as forest fire detection system.

An energy‐efficient cooperative MIMO transmission with data compression in wireless sensor networks

“…Then the energy consumption of long‐haul cooperative transmission is considered and shown as where the E lh denotes the energy consumption per bit in the long‐haul phase. According to Refs , , , and E lh can be calculated by utilizing the link budget relationship as shown below: where is the average energy per bit required for a given BER at receiver, α equals ξ / η –1, with ξ being the peak to average ratio (PAR) and η being the drain efficiency of the RF power amplifiers, d is the transmission distance, G t and G r are the transmitter and receiver antenna gains, respectively, λ is the carrier wavelength, M l is the link margin, and N f is the receiver noise figure. P c and R b denote the power consumption of the circuit block and the transmission bit rate, respectively.…”

“…After considering the energy consumption per bit for detection E d , the total energy consumption can be expressed as where E d ( total ) = E d × N i is the energy consumption for detection and E d can be calculated according to Ref. .…”

“…The simulation is given for energy comparison, and the parameters are as follows: M l =40 dB, N f =10 dB, G t G r =5 dBi, η = 0.35, E J =1.215 nJ, N i =20 kb, nJ/bit/signal, c = 2, ρ max =2/ π , and D max =10 m. Also, some indirectly used parameters are same as the ones in CMIMO‐SM, which can be obtained from Ref. due to space limitation. For fair comparison, the same setup M t = M r =2 with BPSK is used.…”

Lifetime and energy optimization in multi‐hop wireless sensor networks with spatial modulation based cooperative MIMO

“…According to Ref. , the energy consumption of CMIMO‐SM in the one‐hop situation includes local phase and long‐haul phase energy consumption. When M t nodes try to cooperative with each other at the transmitter and M r nodes try to receive the data at the receiver, the total energy consumption of the local phase can be expressed as where and represent the local transmission energy cost per bit on the transmitter and the receiver, respectively.…”

“…By extending and developing the work in Ref. , this letter proposes an only‐forwarding multi‐hop scenario wherein the hop length is allocated and the number of hops is selected to achieve the minimum energy consumption and longest lifetime.…”