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 . 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.
Right now the future of MIMO isn’t secure. Because devices won’t be interoperable, the cost to change over will be prohibitive. The standards based Wi-Fi gear like routers would benefit from MIMO technology. This would include the Belkin, Linksys and Netgear routers.
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 .
In the recent years, wireless technologies have taken a new dimension in the ways society lives. Wireless broadband is available to everyone. Whether the users are at home, driving the car, sitting in the park, and it would even work while people are a pleasure boat ride in the middle of a lake. And because of this, the need to have information at any time and be connected in all places, all the time has been satisfied.
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.
The increase in the transmission speed in the IEEE 802.11n standard is achieved, firstly, due to the doubling of the channel width from 20 to 40 MHz, and secondly, due to the implementation of MIMO technology. MIMO (Multiple Input Multiple Output) technology involves the use of multiple transmit and receive antennas. (Mitchell, 2017)
A measure of quality of service in a wireless connection is made using SINR (Signal to noise interference ratio).For the performance evaluation let us consider a an overall network t to be composed of two-tier 19 macrocells, with many femtocells randomly deployed over the macrocells. Then the macro user would be interfered from neighbouring macro cell's (18) and all of the adjacent femtocells. Due to small transmit power, only femtocells which would be located in the 1-tier macrocell area gives interference to macro user. The estimation of the received SINR of a macro user m on subcarrier k, when the macro user is interfered from neighboring macrocells and all the adjacent Femtocells  would be given by where P_(M,K) and P_(M^1,K) is transmit power of serving macro-cell M and neighbouring macrocell M’ on subcarrier k, respectively. G_(M,m,K) is channel gain between macro user m and serving macrocell M on subcarrier k. Channel gain from neighbouring macro cells are denoted by G_(M1,m,K) Similarly, P_(F,K) is transmit power of neighbouring femtocell F on subcarrier k. .
systems and channel models . Single and multiple relay selection were investigated, and several SNR sub-optimum
In the last few years, number of mobile users/wireless users has been increased explosively all over the world. The demands for wireless communication network has been increased day by day and it cannot be satisfied with wired networks because it has been seen that communication channels are more contaminated than wired networks. The main characteristics of the wireless communication are the multipath reception. We can receive signal not only through Line of Sight but also reception can be made through a large number of reflected radio waves that arrive at the receiver at different times. The difference in arrival time is caused due to trees, vehicles, buildings, rocks etc.
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 . In addition to multiuser detection, transmit power control , and joint design of transmitters and receivers ,  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
MIMO techniques are mostly used to accelerate system throughput over disruptive wireless communication channels. It is well known fact that with the number of transmit antenna M and number of receive antenna N, the capacity of MIMO systems increases linearly with a factor of MN. The receiver decodes the received signal vectors into actual information, a narrow band flat fading MIMO is designed as:
In this type of MIMO system the processing of signals occurs at the receiver only. Receiver processing system is mostly beneficial in the uplink scenario as the signal processing is restricted to the receiver and as at the mobile station no MIMO signal would be required. In case of uplink scenario, there is a single data stream which is demultiplexed into the N number of substream, and each substream is further modulated and passed it into N number of transmitters.
I .Temporal diversity: In this case replicas of the transmitted signal are provided across time by a combination of channel coding and time interleaving strategies.
Massive MIMO Wireless Network convergence means using one pipe to deliver all forms of communication services like video, audio and data communication within network. Convenience and flexibility is offered by using multiple communication modes in a single
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.