Modeling Smart Antennas in Synchronous Ad Hoc Networks Using OPNET’s Pipeline Stages

Smart antennas have been proposed as a physical layer device that can increase the capacity of ad hoc networks. The effectiveness of smart antennas depends on whether access mechanisms create the conditions that enable receivers to adapt to both desired signals and interfering signals and enable transmitters to discern where they must avoid causing interference. The ease of implementing solutions and modeling the antennas are both affected by whether the access schemes are asynchronous or synchronous. Asynchronous access mechanisms are more difficult since they allow new transmitters to begin transmissions during ongoing exchanges. Thus, past adaptation becomes irrelevant and current adaptation is done with insufficient information. Arbitrating the effects in simulation requires detailed models of antenna adaptation and the resulting power patterns. Synchronous access mechanisms, however, overcome these shortcomings because they force ongoing exchanges to conclude before new exchanges start and because they cause all new exchanges to occur simultaneously. Receivers can sample both the desired signals and the interfering signals to arrive at a weighting solution. Since conditions do not change after adaptation, the adaptation is more effective and simulation models can be more abstract. In this paper we describe how we built models of adaptive antennas in OPNET using a radio process model and the radio pipeline stages. We use this model in conjunction with our Synchronous Collision Resolution (SCR) medium access control protocol and evaluate the relative merits of different antenna technologies and capabilities. We found that those technologies that improve capture soonest in an exchange most improve the capacity. Introduction Directional and smart antennas have been proposed as a means to enhance performance of wireless ad hoc networks including increasing capacity, increasing the range of communications, reducing the susceptibility to detection, interception, and jamming, conserving energy, and resolving collisions. Properties of antennas that have been identified to support these benefits include: antenna directivity, increased gain, and a host of capabilities enabled with arrayed antennas and signal processing techniques including beam forming, null steering, diversity, spatial processing, and multiple input multiple output (MIMO). Direct modeling of these effects and the algorithms that make them work is prohibitive requiring detailed models of the environment, the antennas, and the scenario, their effect on the bit streams that are transmitted and then the results of the algorithms that operate on the bit streams. This level of detail is difficult to create for just the analysis of algorithms let alone to combine it with a comprehensive network model with multiple transceivers transmitting and receiving simultaneously. Abstractions that can capture the effectiveness of these techniques are necessary to assess their contribution to the performance of mobile ad hoc networks (MANETs). In this paper, we propose a modeling abstraction that accounts for directional and smart antenna effects when using synchronous access. We build these models into a radio process model and OPNET’s radio transceiver pipeline stages. Our presentation of this material begins with an overview of directional and smart antenna technologies. Next, we describe how smart antennas are modeled abstractly and then how we model them in OPNET. We describe the Synchronous Collision Resolution (SCR) approach to access and identify how it creates the conditions that enable smart antennas to be exploited and the models we described earlier to be valid. We conclude with a description of simulation experiments we conducted to study the effect of smart antenna performance on SCR capacity. Directional and Smart Antennas The mobility of nodes in ad hoc networks will cause the relative direction between nodes to change. Exploiting directional antennas in mobile ad hoc networks (MANET) will involve intelligence to discern where to point an antenna and mechanisms to subsequently point it in that direction. Antennas that can do this are considered smart. Smart antennas have varying levels of intelligence. This intelligence is frequently divided into three levels: switched beam, dynamic phased array, and adaptive array [1]. A review of the differences and the types of intelligence follows. Switched Beam Antennas In switched beam antennas, there is a predefined set of directions in which an antenna can be pointed. Use of these antennas in ad hoc networks requires MAC and possibly routing protocols to track which antenna sectors point toward other nodes. Dynamically Phased Arrays An array of antenna elements can be pointed in a direction by changing the phase of the signals emitted from each element so that they arrive on the wavefront in the preferred direction at the same time thus constructively interfering in the pointing direction and destructively interfering elsewhere. Any arrangement of antennas can be used; however, they must be calibrated to support beamforming. Weighting of the excitation signal at each antenna can be used to affect the shape and amplitude of the mainlobe and sidelobes. The enhancement in intelligence that comes with dynamically phased arrays is the ability to determine the direction of the arrival (DOA) of signals so that the antennas can adapt and immediately point toward the source. This capability does not require protocols to track network state.