**1. Introduction**

Since the start of wireless communications, concerning to the network node physical layer, there are two main types of antenna which can be used as a way to make a certain behavior on transmission/reception: omnidirectional antennas which radiates and receives equally in all directions, and directional antennas which have the capability to radiate in a specific direction. Omnidirectional approaches can be straight and detrimentally impact on spectral efficiency of the system, restricting frequency reuse [1]. These limitations force system designers and network planners to develop progressively advanced and costly remedies. Lately, the requirements of broadcast antenna technology on the quality, capacity, and coverage of wireless systems have motivated the development in the fundamental design and role of the antenna in a wireless system. In pervasive environments, such as mobile ad hoc network (MANET) or wireless sensor networks, employing an omnidirectional approach is hard and an inconvenient way to create efficient

systems, because of the high burden of power of network nodes [2] that may result in destructive phenomena such as low battery depletion and interference. A single antenna may also be built to have certain fixed preferential transmission and reception directions to maximize its energy consumption in a specific direction conserving power in other directions [3]. Using directional antenna could lead to several advantages, in terms of reduction of packet delay or improvement of the overall routing process [4]. In wireless communications, when a single antenna is utilized both to the transmitter and receiver we talk about single input, single output (SISO) [5] systems. Therefore, nowadays, with regard to the latest antenna technologies, the concept of smart antenna systems has spread. SAS are intelligent systems equipped with high efficiency data processing unit. This sort of systems can boost the coverage area and the capability of a radio communication system. The coverage area is simply the area where the communication link between a mobile and the base station can be performed. The capability is a way of measuring the amount of users a system can support in certain area. A smart antenna system generally combines an antenna array with a digital signal processing capacity to transmit and receive in an adaptive, spatial manner. Quite simply, such a system can quickly change the directionality of its radiation patterns in response to its environment. This may considerably increase the performance characteristics (such as capacity) of a wireless system. The employment of SAS in wireless mobile environments allows a much more reliable medium utilization with regards to the classical omnidirectional strategy. For instance, spatial division multiple access (SDMA) attempts to raise the capacity of a system. Generally, smart antennas get into three major categories: single input, multiple output (SIMO), multiple input, single output (MISO), and multiple input, multiple output (MIMO). In SIMO technology, one antenna is used at the source, and two or more antennas are used at the destination. In MISO technology, several antennas are used at the transmitter, and one antenna is utilized at the destination. In MIMO technology, multiple antennas are used at both source and destination.

**Figure 1** illustrates an example of SISO and MIMO systems. In the SISO case, either the transmitter or the receiver uses a single antenna for the communication process; while in the MIMO, an antenna array is employed. In literature, it has been demonstrated how the use of directional antennas and the most recent smart antenna systems (SAS) technology is capable of significantly allowing high quality of service (QoS) requirements in spite of the omnidirectional systems that foresee

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technologies.

tion mode:

**2. Smart antenna systems**

channel feedback.

*Smart Antenna Systems Model Simulation Design for 5G Wireless Network Systems*

limited functionalities [6, 7]. However, these solutions are unlikely to satisfy the requirements for 5G wireless communication systems technology. For this purpose, the massive MIMO technology has been proposed as efficient solution for satisfying the requirements for 5G that certainly include very high antenna gain and very high data rate in order to achieve huge system performance [8–10]. The term massive, means that this kind of systems employs a large number of antenna elements (at least 50 antennas) in the hardware architecture; indeed, relating to the modern wireless networks, for achieving high communication benefits in terms of throughput, we need for a massive number of elements that is not less than 70–80 antennas [11]. This is mainly due to the fact that, theoretically, as the number of elements improves, the overall gain of the system also increases, and in fact, each single antenna element contributes to enhance the total gain. More specifically, from the antenna array theory, it is known that the overall gain is affected by the single element factor as well as the array factor, and this gain increases with the number of antenna elements. The massive MIMO are strongly recommended for beamforming environments by the most recent IEEE802.11n and IEEE802.11ac standards. Remember that we refer to a beamforming wireless network context when communications between nodes occur through the beamforming process; the beamforming is defined as the capability of a node to scan and drive the antenna beam pattern toward a certain area or a set of directions. One of the most critical aspects in wireless communication environments is represented by the fact of using an adequate network simulator that is able to well emulate and reproduce an appropriate real scenario. Unfortunately, most of the existing network simulators do not provide any support for directional and asymmetrical communications, and thus also for SAS and MIMO technology. In this field, only an extremely limited amount of network simulators allow to emulate these very complex technologies. Unfortunately, in such cases, with regard to these network simulators, the cost of the license allowing the end user to access to the 5G package modules could result very expensive [12]. In this chapter, we present a set of features extending the default functionalities provided by one of the most used open source network simulator, that is the Omnet++ simulator, with the goal to illustrate how it is possible to actualize the existing simulation instruments to be suitable also for 5G wireless network communication environments. The chapter is organized as follows: Sections 2 and 3 provide a theoretical overview about SAS and massive MIMO, respectively, while Sections 4 and 5 explain the implementation strategies in Omnet++ related in the aforementioned

As mentioned, SAS are intelligent systems that allow a good SDMA processing [13, 14]; examples of SAS are: digital beamforming systems, adaptive antenna systems, phased array, and others. Smart antennas are customarily categorized, however, as either switched beam or adaptive array systems. There could be a distinction between two major categories of smart antennas in terms of the opera-

• **Switched beam**: A finite number of fixed and predefined patterns without

• **Adaptive array**: An infinite number of patterns that are adjusted in real time

based on such parameters, for example, channel noise conditions.

*DOI: http://dx.doi.org/10.5772/intechopen.79933*

**Figure 1.** *SISO and MIMO structure example.*
