Energy-Based Transmission Strategy Selection for Wireless Sensor Networks Yanbing Zhang and Huaiyu Dai Department of Electrical and Computer Engineering NC State University Raleigh, N.C., USA {yzhang, Huaiyu_Dai}@ncsu.edu Abstract—Energy efficiency is one of the most critical concerns for wireless sensor networks. While cooperative transmission strategies have the potential to significantly improve the system performance, they also incur additional energy cost and system overhead. In this paper, Energy efficiency of relevant transmission strategies is studied both for wideband asymptotes and realistic system settings. Based on this analysis, general guidelines are presented for optimal transmission strategy selection in some typical scenarios, aiming at minimum energy consumption with a target BER. The proposed selection rules, especially those based on system-level metrics, are easy to implement for sensor applications. The framework provided here may also be readily extended to other scenarios or applications. Keywords-sensor networks; energy efficiency; virtual MIMO I. INTRODUCTION Energy efficiency is one of the most critical concerns for sensor applications [1]. Direct communications between sensor nodes and the (possibly) distant data collector is in general energy inefficient, as each node needs to transmit the highly redundant data. By allowing sensor nodes in close proximity to cooperate on communication, not only can the collected data be efficiently fused, but recent progress in wireless multi-input multi-output (MIMO) communications can be exploited to improve the system performance, which can equivalently be traded for energy efficiency. However, concerning the analysis of energy efficiency in wireless cooperative sensor networks, two additional factors should be given special considerations: the circuit energy consumption and the cooperation penalty [2][3]. The circuit power utilization increases linearly with the number of cooperative nodes, which is significant especially for short-range transmission. Furthermore, cooperative nodes must communicate among themselves to share information and coordinate transmission, which consumes extra energy and induces additional delay. Therefore, it may not always be better to enforce cooperative transmission and vice versa. Determination of the optimal transmission strategy depends on many interacting factors including system demand, network topology, and availability of channel information. In this paper, we take an initial step to quantify the switching thresholds among three representative transmission strategies: traditional non-cooperative transmission, space-time block coding (STBC), and spatial multiplexing (SM), the latter two of which fall within the cooperative transmission category yet are feasible to implement for sensor applications. The selection rules are decided such that the best energy efficiency is achieved with given system or link level demand or knowledge. This work was supported in part by the National Science Foundation under Grant CCF-0515164. The rest of this paper is organized as follows. Section II presents the system model and our assumptions on analysis. Energy efficiency of relevant transmission strategies is studied in Section III, which provides a basis for selection of energy- efficient signaling. Then in Section IV, general guidelines are proposed for optimal transmission strategy selection in some typical scenarios. Finally Section V concludes the paper. II. SYSTEM MODEL A. Channel Model We assume a hierarchical network structure, in which most plain sensor nodes are stringently limited in processing capability and power, while a few powerful mobile agents (MA) take over the burden of complicated network operation and signal processing. These mobile agents, furnished with superior communication and processing units, can traverse the network to collect data, and reach back to remote control centers through high-speed connections. Examples of mobile agents include manned/unmanned airplanes or vehicles, or specially designed light nodes that can hop around in the network. This architecture assumes certain advantages in energy efficiency over the traditional flat multi-hop ad hoc network [8]. In this paper, we further investigate the possible advantages of cooperative MIMO transmission in wireless sensor networks with mobile agents (SENMA), which can be similarly coined as M-SENMA. We assume that at some moment T N neighboring nodes in a SENMA intend to transmit to a MA equipped with R N antennas. Independent frequency nonselective Rayleigh fading is assumed for the channels between each node and the MA, on top of the common path loss 1 . The equivalent discrete- time MIMO system can be described as N HX Y + = , (1) where Y is the received signal at the MA; X contains the substreams transmitted by the nodes; H is an T R N N × channel matrix, whose entries are modeled as independent and identically distributed (i.i.d.) normalized complex Gaussian random variables; and N is the background noise, assumed to be circularly symmetric Gaussian with variance 0 N for each component. The common path loss is incorporated in the power of X. The optimal transmission strategy is decided at the MA, based on (available) relevant information at the system or link 1 Rayleigh fading is commonly assumed in MIMO and SENMA studies whenever rich scattering exists in environments. This can be justified when sensor nodes are distributed in a building or forest. In applications with line- of-sight communications, Ricean model can be exploited.