Spectrum is a limited and valuable resource. The escalating requirement for wireless communication and broadband services has augmented the attempts to improve the designs for wireless systems. These enhanced wireless systems offer substantial increase in data throughput and link range without the requirement of any additional bandwidth. This led to the development of MIMO Systems. In Multiple-Input Multiple-Output (MIMO) technology, multiple antennas are used at both the transmitter and receiver to improve the functioning of the wireless communication system. We accomplish this objective by exploiting the spatial domain of the transmission medium.
In this chapter, we describe the MIMO system model along with a brief discussion of its
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The detector then chooses one of the BM possible transmitted symbol vectors based on the available data. An optimal detector should return as x ̂ = x*.
3.3 MIMO System Model
The capacity of Single-Input Single-Output (SISO) wireless communication systems must be increased to fulfill the ever-growing demands of efficient transmission rate. This can be done by allocating additional bandwidth which is not always feasible due to the limited spectral resources [Alamouti 1998]. Recent studies have proved that using spatial multiplexing MIMO systems can boost the capacity of a wireless communication system significantly without the prerequisite of extra-bandwidth.
Multipath propagation is an essential component of all wireless communication system. Conventional radio systems rely on the strong primary signal and also make use of multipath mitigation techniques to overcome multipath propagation and interference. Beam forming technology or smart antenna technology is used for this purpose. A smart antenna is capable of routing transmitted beam by scheming the phase of the signal at each element of the antenna array to the receiver. Receiving diversity, this uses numerous antennas at the receiver side and merges all the received signals to improve the signal reliability. These techniques are used to reduce the effect of multipath propagation on the communication systems. MIMO makes use of multipath propagation to get better throughput, range and reliability [Berrou 1996]. In
In the Multihop Virtual Multiple Input Multiple Output (MIMO) the data are collected by multiple source nodes and transmitted to a remote sink by multiple hops [11]. In this, the cluster head sends message to sensor nodes in the cluster. Next the sensor nodes encode the data and sends to cluster head in the next hope according to the orthogonal Space Time Block Code [STBC]. It saves the energy and provides QoS provisioning.
The version of MIMO using single input multiple output has the advantage of being easy to implement, but the disadvantage is that the receiver requires processing. This causes battery drain.
In Fig. 1, the 4 nodes are considered. Among the four nodes 2 of the nodes (Node 1 and Node 2) are primary networks and 2 other nodes (Node A and Node B) are secondary networks. The two networks act in different frequency range. The primary network acts at a range of 2.4GHz - 2.4835GHz range. The secondary network acts at a range of 433MHz - 473MHz represents the block diagram of the proposed system. The use of different frequencies increases the number of users. Node 1 and Node 2 communicate at 2.4GHz and Node A and Node B communicate at 433.9MHz. The nodes are made mobile and this causes high interference. This is cancelled by channeling where the frequencies are slotted. Multi-hop cognitive radio technique occurs when the data is transmitted from one secondary node to another which is out of range via primary node. At that time the primary node which is of MIMO antenna switches itself to the secondary node frequency and transmits the data. Wireless MIMO systems with multiple antennas employed at both the transmitter and receiver have gained attention because of their promising improvement in terms of performance and bandwidth efficiency [8].
It’s very important to determine the device and application requirements based on bandwidth, protocols and frequency. In wireless network, bandwidth, protocols and sometime environmental conditions affect the speed of the channel so we need to calculate the aggregate throughputs before designing the network. Today, users carry Wi-Fi devices such as notebooks, laptops, tablets and Smartphone’s so total throughput must be calculated by estimating number of connections rather than the number of the seats. Some common wireless networking standards such as 802.11a/b/g/n invented in the IEEE association must be supported by wireless network. For better performance and for faster devices (802.11n devices), dual-ratio access points should be deployed. Table1 [3] illustrate the different IEEE standards and throughput.
For the downlink MIMO system configurations with two or four antennas has being considered. In 2x2 configurations there is baseline configuration with two antennas at the transmitter and two antennas at the receiver. There are different modes has been predicted for MIMO antenna system such as spatial multiplexing and transmit diversity and channel automatically select any scheme of choice.
IEEE802.11n made numerous changes to the 802.11 wireless standards that greatly increased the throughput as compared to earlier versions. 802.11n uses MIMO which is Multiple Input Multiple Output (also known as Multiple Antennas). MIMO makes use of multiple antennae to create multiple streams of communications between a transmitter and a receiver. The 802.11n amendment also introduced changes in the physical as well as MAC layers to make marked changes in the effectiveness of wireless networks. These changes included spatial-division multiplexing, space-time block coding, and transmitter beamforming.
In section (A) i attained the out value of the power received by inserting the path loss exponent(n), distance between the transmitter and receiver (d), close in reference distance(d0) in to the log-distance path loss equation. By observing the received output power, i can say that as the distance increases the out power is reduced.
It is obvious that the path loss increases by reducing the antenna gains. As in the aforementioned free-space model, the average received signal in all the other actual environments decreases with the distance between the transmitter and receiver, d, in a logarithmic manner. In fact, a more generalized form of the path loss model can be constructed by modifying the free-space path loss with the path loss exponent n that varies with the environments. This is known as the log-distance path loss model, in which the path loss at distance d is given as
OFDM provides the frequency selective channel which can able to divides the frequency band into multiple sub channels and each sub channel carries a different stream of symbols. There is flat frequency response throughput each sub channel when there is narrow bandwidth of each sub channel. Therefore OFDM able to transform a frequency selective channel into set of multiple flat-fading channels. Simultaneously when M transmit antennas used an OFDM transmitter, and N receive antenna used OFDM front end then L flat fading MIMO channel is formed from MIMO frequency selective channel with having dimensions equals to MxN. Earlier traditional space time codes were not optimal for takeout the additional
systems and channel models [7]. Single and multiple relay selection were investigated, and several SNR sub-optimum
During the last decade, MIMO techniques in wireless industry have gained a huge interest in the study. MIMO is treated as an extension of conventional smart antenna systems (SAS). In SAS, techniques of beamforming are deployed and the optimal antenna weighting vector that determines antenna radiation pattern is computed based on the optimal criterion such as maximum signal-to-interference plus noise ratio (SINR), minimum mean square error (MMSE) [8]. The ability to exploit and use the multipath propagation can be considered as one of the major advantages of MIMO systems. In contrast to transmit beamforming schemes, channel state information (CSI) is generally not required at the transmitter of MIMO systems. MIMO techniques for transmitting systems can be majorly divided into two categories: spatial multiplexing and space-time coding (spatial diversity techniques). In spatial multiplexing technique, it increases the data rate (throughput) over a MIMO dedicated
As a result of less power loss toward unwanted directions, the multipath and interference effects are reduced. Using wideband circularly
A Macrocell user operating in the same band as femtocell users may cause unacceptably high interference levels, if it is close to the femtocell base station supporting the aforementioned femtocell users, and far away from its own macrocell base station. Additionally, the fact that femtocells can be deployed in an ad hoc fashion anywhere within a macrocell, and can be removed as easily, adds to the critical importance of interference management. Notwithstanding the importance of this issue, the concerns listed above renders jointly optimal design of the two networks impractical due to the complexity and overhead associated with a large dynamic network. Consequently, a computationally manageable yet effective interference management strategy is needed. Interference management has been an important design element for multiuser systems in the past two decades. Judicious receiver design for interference limited systems, e.g., CDMA, and multiuser MIMO, proves useful for interference cancellation [3]. In addition to multiuser detection, transmit power control [4], and joint design of transmitters and receivers [5], [6] offer interference mitigation needed in interference limited systems. We note that while our approach does not involve explicit frequency partitioning between the tiers, i.e., relies solely on the space dimensions, allowing for greater flexibility, it is possible to have our scheme accompany a frequency partitioning scheme and increase the number
Cooperative communication is a new concept of research and it is a powerful technique to mitigate fading in wireless relaying layout. Concerning with the fading problem, this paper is focuses to give a better non-orthogonal space-time block code (STBC) scheme and assimilate it in the cooperative relaying nodes for upgrading performance of the system. Golden coded has also been incorporated in IEEE 802.16 (Wi-MAX) standard as a full rate full diversity space-time code and proven to present a ranking performance in a wireless MIMO (Multiple Input Multiple Output) scenario than any other code. At the receiver, maximum likelihood detection of different symbol is achieved through decoupling of the signal transmit from different antenna rather than joint detection. In this paper multihop wireless relay consisting of source, relay and destination each equipped with two antennas have been taken into account using decode-and-forward cooperative protocol strategy in relay nodes. The simulation results support the effectiveness of the proposed scheme by offering better SER performance and increased spectral efficiency than other codes.
The field of antennas is vigorous and dynamic, and over the last 60 years antenna technology has been an indispensable partner of the communication revolution. Antenna has been considered an important component in the development of modern wireless communication devices. In addition to receiving and transmitting energy, an antenna in an advanced wireless system is usually required to optimize the radiation energy in some directions and suppress in others. For wireless communication systems the antenna is one of the most critical components. A good design of the antenna can relax system requirements and improve overall system performance.