a simple phase lock summing circuit which is very easy to implement.EGC can engage in the reception of diversity with coherent modulation. As in EGC the diversity branches are combined with equal gain but they have conjugate phase. Maximum ratio combining technique requires summing circuits, weighting and co-phasing. Each of the signals from different branches are weighted and co-phased with a gain factor which is proportional to the SNR before summing or combining. The applied weighting to the diversity branches has to be adjusted according the SNR. Techniques used in MIMO system In wireless communication system MIMO is used to provide better performance as compared with others conventional systems. The multiple data stream is provided in …show more content…
V-BLAST algorithm at the receiver is used to mitigate the interference between different streams and try to generate the original data stream at the receiver. V-BLAST used optimal combining and interference cancellation technique. The signal which is having the best SNR is retrieved at the receiver. In the figure shown below which illustrates the good performance achieved at the receiver. V-BLAST technique is referred as non-linear technique as it generates the best signals for cancellation. Transmitter Processing Only In this technique of MIMO system, the signals processing occurs at the transmitter only as the signal processing is restricted at the transmitter therefore it is more beneficial for downlink scenario, because no signals is required at the mobile station. In case of downlink system there is N number of antennas at the receiver with having N number of data stream and each of it is multiplexed and output. There were three techniques used by the MIMO system with antenna processing at the transmitter and having a simple receive structure which is the transient zero forcing scheme, Filter bank method and transmit MMSE. All the interference has been cut by the transmit zero forcing technique whereas the filter bank method is used to minimise the signal to interference ratio in all sub-channels. Processing at Both the Receiver and
There are many different types of filters that can be used for decimating, including: cascaded comb-integrator (CIC); direct form polyphase finite impulse response (FIR); half-band FIR; symmetric polyphase FIR filters; transposed direct form II infinite impulse response (IIR) and quasi-linear IIR filters amongst others. As well as using these different configurations, hybrid types can be used for more efficient implementations designed either for better magnitude response, lower power consumptions or
Dual band (DSB) signal comprising on the lower sideband, and a single sideband (SSB) signal may be generated by filtering or by using a single sideband mixer.
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].
The COM-3011 operates by first mixing the received signal with 125 MHz, thus the data is now contained on it. The centre frequency is chosen by mixing a user specified radio synthesiser frequency with the 125 MHz together. For example to obtain a centre frequency of 100 MHz, the user would specify 225 MHz or -25 MHz. The bandpass filter will reduce the bandwidth to 40 MHz or 20 MHz either side of centre frequency [12]. This sample is the duplicated and the second part delayed by 90 degrees to form an in-phase and quadrature features.
these subcarriers to a higher frequency band. Except for a multiplying constant (1=N), the above
In MIMO system there is multiple antennas is provided at the transmitter side as well as receiver side. Using multiple antennas at the transmitter and the receiver side could able to increase spectral efficiency, produces higher capacity and provides more data rates for wireless communication. In MIMO system there is SU-MIMO that is called single user MIMO in which when there is data rates need to be increased for single user then it is known as SU-MIMO, and if there is individual stream is allocated to multiple users; then it is called multiuser MIMO (MU-MIMO).
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.
As illustrated above, a hybrid active noise cancelling system is a constitution of feedforward and feedback mechanism with adaptive filters. The red area in block diagram is the feedforward section and the green is the feedback section. To understand this system more thoroughly, we will need to look at the feedforward and the feedback system individually.
Chin-Liang Wang and Yuan Ouyang ( 2005) introduce a Selected mapping method .The Selected mapping method approach provides good performance for peak to average power ratio reduction reduction, but it requires a bank of Inverse Fast Fourier Transforms to generate a set of candidate transmission signals, and this requirement usually results in high computational complexity. The author suggests low-complexity conversions to replace the Inverse Fast Fourier Transform blocks in the conventional Selected mapping method method. Two novel Selected mapping method schemes were proposed with much lower complexity than the conventional one; the first method uses only one Inverse Fast Fourier Transform block to generate the set of candidate signals, while the second one uses two Inverse Fast Fourier Transform blocks. Computer simulation results show that, as compared to the conventional Selected mapping method scheme, the first proposed approach has slightly worse peak to average power ratio reduction reduction performance and the second proposed one reaches almost the same peak to average power ratio reduction reduction performance. Chin Liang wang continues his investigation by oversampling two times of the Ortogonal Frequancy Division Multiplexing signals by applying peak search and partial interpolation method. The proposed scheme with two times
Impedance matching is one of the most eminent part of the RF circuits. It is utilized for the purpose of transferring maximum
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
Further, I plan to make use of this SDR based transmitter for Cognitive Radio Communications, that is, developing a dynamic transceiver which can intelligently detect unused channels and broadcast on the best channel thus avoiding interference. Mobile devices are dealing with an increasingly complicated
A gradient algorithm is proposed where the gradient of clipping noise mean square error is calculated and optimization of signal to clipping noise ratio is done in place of peak to average power ratio and order of complexity is O(N). A truncated IDFT algorithm is proposed where in place of calculating entire IDFT values, it calculates on maximal IDFT element thus reducing complexity of optimization process. The basic idea is to divide the group in two halves of N/2 and leave the half with lesser energy and move in similar way till we reach the maximum energy element, however this scheme may not always give correct maximal IDFT element, it also costs in lower peak to average power ratio reduction.
As Reed (Reed, 2002) and others have stressed out, that the benefits of SDR approach go way beyond the multimode operations. Other benefits stem from the flexibility that comes with programmability. For instance, it can simplify design by allowing reuse of a common RF front end with new designs or modes of operation available through software changes. It also enables improvements to radio performance and functionality through application of digital signal processing (DSP) to implement adaptive beamforming, interference mitigation, and numerous other techniques either proven or in development. As the SDR approach has gained traction, a variety of hardware and software tools for development and exploration have become available. These tools are broadly accessible with reasonable cost and ease-of-use enabling new opportunities for engineering education and research. Examples include National Instruments (NI) universal software radio peripheral (USRP)/ NI LabVIEW software , the Ettus Research USRP/ GNU’s Not Unix (GNU) Radio, WARP , the Lyrtech SDR Platform and the IMEC SDR Platform. For researchers, these platforms can provide a starting point for development of prototypes operating on live signals. Such prototypes can effectively demonstrate the practical viability of an implementation and are a step toward end deployment.