Figure 1. Cooperative Communication Setup
Multiple-Input-Multiple-Output systems (MIMO) are regarded as one of the most promising research areas of wireless communication systems In wireless communication, where elevated data broadcast rates are essential for the needs, i.e. data, voice and video. At user end the capacity resolves the excellence of the communication systems. Transmission techniques of MIMO are two types, one is diversity gain and second one is multiplexing gain. Fading mitigation and transmitted signal performance can be improved by diversity gain. Under prosperous dispersion environment multiplexing gain offers the high broadcast rates. Cooperative relaying is an expertise technology that can improve the performance of a wireless system via a number of mechanisms such as increased spatial diversity. In this paper, a review of the prominent results like improving the user throughput and cell average throughput using relays in Cooperative – Multiple –Input-Multiple-Output systems (CMIMO) have been analyzed.
MIMO technology is a significant feature of all advanced cellular wireless communication systems[5]. Cooperative communication has recently known as a promising technique to conflict fading wireless networks. Space time coding is a favorable approach which combines multiple antennas in the sender side with signal processing and coding techniques. The utilization of multiple antennas at both ends of wireless link is a progressive method for achieving lager throughput. This technique is known as Spatial Multiplexing (SM) and has an effective growth in spectral efficiency [3, 4].
Wireless Communication systems like cellular mobile communications, internet, and multimedia services require very high capacity to accomplish the need of high data rates. These systems must achieve the preferred spectrum availability, often in severe channel environments. They need to overawed signal scattering and multipath effects [9, 11].
To obtain a higher data rate at an acceptable Bit Error Rate By (BER), larger bandwidth is required. To palliate severe fading channel conditions, a higher transmitted power level is required. MIMO communication systems have the latent to provide increased capacity and reliability without increasing the bandwidth or transmitted power. MIMO systems exploit time and spatial diversities by employing multiple antennas at the transmitter and receiver [10, 13].
MIMO uses huge number of antennas. This will offer more significant developments in both the throughput and energy efficiency. As the number of antennas increase without limit, the effects of uncorrelated noise and small - scale fading can be removed completely [7].
Relays receive and retransmit the signals between base stations and mobiles can be used to increase throughput extend coverage area of cellular networks.
This paper is modeled as firstly system level simulation analysis of cooperative MIMO and non-supportive Multiple -Input-Multiple-Output structure is compared. At all base station locality huge numeral of antennas is organized in system altitude replication. This analysis provides user throughput and cell regular throughput performance that can be realized by using relays in cooperative MIMO.
The rest of paper is arranged as follows, section 1 explains in detail about cooperative, non-cooperative, and relays. The explanation about the existing system is discussed in section 2. Section 3 describes about the proposed method. The simulation results are presented in section 4. Finally, the paper is concluded.
The concept of cooperative communications is first introduced by Sendonaris et al. [8]. Cooperative communication, in which each wireless user transmits not only its own information, but also act as an assisting agent called relay, for other user. As an example two user cooperative communications setup, for cellular networks, is shown in Figure 1. Hereby using this new scheme of transmission, destination can be provided with several independent copies of the same transmitted signal. The number of copies depend on the number of cooperating users.
Figure 1. Cooperative Communication Setup
Non-Cooperative communication is the multiple access channels, where users send straightforwardly to a common destination, without waiting for one another.
Relay channel was first introduced by Van der Meulen [12]. The job of relay is to receive signal from the source and forward it to the destination, like repeaters as revealed in Figure 2. In cooperative communication, the node acting as a relay, not only forwards other users information, but has its own information to send as well.
Figure 2. Relay Communications
Fixed relays store the data received from the Base Station (BS) and forward to the Mobile Stations (MSs), simultaneously
Mobile relays are more flexible in accepting varying traffic patterns and adapting to different propagation environments.
Relaying protocols, Amplify and forward, Decode and forward have been introduced.
The data from the sender will be broadcasted to relay and target concurrently. The energy received by relay will get improved and then it will be promoted to the target. This is also identified as non-regenerative relaying proposal. This process is mostly used for continuous signals.
The data from the sender will be on the way to convey and convey to destination. Relay detects the signal and deciphers the signal collected from the source and rebroadcasts it to the objective. Dispensation of non continuous signals is the main application for this method.
In existing system cooperative and non-cooperative system are considered, i.e. with relay and without relay by which the power gain of the system will be small. Non cooperative signal will be mostly based on smart antenna occasionally and the antennas which we take can be or cannot be compatible. The main negative aspect of these smart antennas is that they are far more complex than traditional antennas (MIMO). This means those problems may be harder to analyze. The location of smart antennas is desired to be considered for optimal operation. Due to the directional beam that 'swings' from smart antenna locations that are most favorable for a traditional antenna is not for a smart antenna.
Using the code sequence on 4×4 MIMO system based particular OFDM with reduced BER without using diversity loss and side information loss with less amount of fading. So on adding more relays the signal quality will be efficient.
In MIMO wireless systems signal processing of space-time is a companion with the spatial dimension ingrained in deploy of numerous spatially disseminate antennas.
This means assorted antennas are worn at dissimilar points. In MIMO wireless communication systems, for developing the wireless communications MIMO is regarded as a sensible enlargement to the smart antennas. Signal between the transmitter and receiver can take various ways to reach the receiver. So, dissimilar paths are occurred between the transmitter and receiver due to number of recipients that are noticeable to the side in the direct path.
These various paths reach the receiver at dissimilar times due to different paths; this causes the delay for the receiver to receive the signal. This delay at receiver introduces the interference. These additional paths are useful in the case of MIMO.
These various paths enlarge the signal to noise ratio, by this strong suit of the radio link is also increased.
In cooperative communication adjacent mobile users with single antenna share their antennas for cooperative transmission.
So the authors initially approach with multi relay process for getting the good signal quality in the meantime of antenna approach, so the reliable function of the process is as shown in Figure 3. By using relays Bit Error Rate and noise in the channel will be reduced.
Figure 3: Path Process of Relays
Between the transmitter and receiver maximum diversity gain is occurred due to unconnected signal paths. Frequency of the MIMO channel is entitled as H. Number of transmit antennas are entitled as Nt . Number of receiving antennas are entitled as Nr . RF carrier frequency is entitled as fc . OFDM subcarrier spacing is entitled as ∆f Number of OFDM subcarriers are entitled as Ns. Subcarriers conceal s data at each broadcast antenna. Number of subcarriers omitted is entitled as Ng . Size of IFFT/FFT is N (N = Ng + Ns ). In MIMO communication system transmitter has numerous antennas and also receiver has numerous antennas. Transmit and receive antennas at the transmitter and receiver are combined so that quality of service for the each MIMO user is increased significantly and also improves the user throughput and cell average throughput.
The system level replication is done using Matlab [6]. The system simulation pattern is fairly based upon LTE replication baseline constraints [1]. In the simulation, it is supposed that the entire system spectrum is obtainable for downlink information broadcast in all subframes. The disposable system throughput for an explicit TDD [2] can be easily derived.
Figure 4 and Figure 5 establishe the UE throughput capacity and Cumulative Distribution Function (CDF) for noncooperative and cooperative huge MIMO with 15 broadcast antennas positioned in each eNodeB, respectively.
Figure 4. UE Throughput Capacity for Cooperative MIMO with 15 Transmits Antennas
Figure 5. UE Throughputs CDF for Non-cooperative MIMO with 15 Transmit Antennas
As the number of users increase, capacity and CDF increases. In 15 transmit antenna, the performance is considered through capacity. Capacity is calculated as power that the power allocates a source to find the resource means area, in which the level increases as the performance is increased. Throughput is decreasing the level of the noise that noise is going is to be calculated as relay or a channel, in which the channel noise will be reduced so that I, E block coding blocks the way through capacity and generates signal through Cumulative Distribution Function (CDF). So the user throughput for Non cooperative is 3.4 Mbps and for cooperative, it is 8.4 Mbps
Figure 6 and Figure 7 show the UE throughput and capacity and Cumulative Distribution Function (CDF) for noncooperative and cooperative massive MIMO with 20 transmit antennas deployed in each eNodeB, respectively.
Figure 6. UE Throughput Capacity for Cooperative Massive MIMO with 20 Transmits Antennas
Figure 7. UE Throughputs CDF for Non-cooperative MIMO with 20 Transmit Antennas
Capacity is calculated as power that is allocated to a source to find the resource means area, in which the level increases as the performance is increased. Throughput decreases the level of the noise that noise is going is to be calculated as relay or a channel, in which the channel noise will be reduced so that I, E block coding, blocks the way through capacity and generates signal through Cumulative Distribution Function (CDF). Here increasing the antenna means decreasing of throughput, i.e. decreasing of noise. User throughput, for Non cooperative is 5.3 Mbps and cooperative is 9.5 Mbps.
4.3 50 Transmit Antennas
Figure 8 and Figure 9 shows the UE throughput and capacity and for non-cooperative and Cumulative Distribution Function (CDF) cooperative massive MIMO with 50 transmit antennas deployed in each eNodeB, respectively.
Figure 8. UE Throughput Capacity for Cooperative Massive MIMO with 50 Transmits Antennas
Figure 9. UE Throughput CDF for Non-cooperative MIMO with 50 Transmits Antennas
Capacity is calculated as power and that a power allocates a source to find the resource means area, in which the level increases as the performance is increased. Throughput decreases the level of the noise which is going is to be calculated as relay or a channel. The channel noise will be reduced here so that I, E block coding, blocks the way through capacity and generates signal through Cumulative Distribution Function (CDF). Here increasing the antenna means decreasing of throughput, i.e. decreasing of noise. User throughput for Non cooperative is 5.2 Mbps and for cooperative is16.6 Mbps.
The exceeding three cases reveal that the cooperative massive MIMO can drastically progress User throughput and cell edge users' system performance. The calculations of simulations are listed in Table 1.
Table 1. System Simulation Performance
In this research work, user throughput and cell average throughput for cooperative and for non cooperative is observed. Using relays in cooperative communication improves the capacity of cell average users and increases the user throughput. Relays in cooperative MIMO communication provides better throughput, reduce the time for signal broadcast from sender to receiver, and also reduces the bit error rate. By reducing the bit error rate transmitted signal quality is high. Conclusion of this work describes the usage of relays in cooperative communication improves the signal quality by decreasing the bit error rate, improves the signal transmission speed so by this cell average throughput and user throughput are improved for cell users.
The system replications bestowed in this work give the possible system performance that may be attained by using relays in cooperative MIMO arrangements in sensible 5G arrangements. Future analyses are on Power minimization in cooperative MIMO communication systems when large number of relays are used based upon best relay selection for transmission and also for spectrum sensing.