MIMO Smart Antenna Technology In 4G
After the read, you will know:
First, the structure and research progress of the MIMO smart antenna transceivers with multiple inputs and multiple outputs
Second, the advantages of the MIMO smart antennas
Third, MIMO smart antenna technology in future mobile communication systems
Fourth, MIMO smart antenna summary
MIMO Smart antennas are usually called adaptive antenna arrays, which can form specific antenna beams to achieve directional transmission and reception and are mainly used to complete spatial filtering and positioning.
It uses the positional relationship between the elements in the antenna array, that is, uses the phase relationship of the signal to overcome multiple access interference and multipath interference. This is the essential difference between it and traditional diversity technology.
The MIMO system refers to a communication system that simultaneously uses multiple antennas at the transmitting end and the receiving end. It effectively uses random fading and possible multipath propagation to double the service transmission rate.
Its core technology is space-time signal processing, which uses a combination of multiple time domains and spatial domains distributed in space for signal processing. Therefore, it can be seen as an extension of smart antennas.
The MIMO smart antenna system has multiple antennas at the transmitting end/or receiving end of the mobile communication link. According to whether the signal processing is located at the transmitting end or the receiving end of the communication link, the MIMO smart antenna technology is defined as multiple-input single-output (MISO), Single Input Multiple Output (SIMO), and Multiple Input Multiple Output (MIMO), and other methods.
First, the structure and research progress of MIMO smart antenna transceivers with multiple inputs and multiple outputs
The space-time processing technologies in the MIMO system mainly include beamforming, space-time coding, and space multiplexing. Beamforming is a key technology in MIMO smart antennas, which improves the signal-to-noise ratio by directing the main energy to the desired user. Beamforming can effectively suppress co-channel interference, and the key is to determine the beamforming weight.
1. Transmission scheme of the MIMO system
The transmission scheme of the MIMO system is mainly divided into two types: the transmission scheme that maximizes the data rate (spatial multiplexing SDM) and the transmission scheme that maximizes the diversity gain (space-time coding STC). The maximum data rate transmission scheme mainly realizes spatial multiplexing by transmitting independent signals on different antennas.
The space-time coding scheme refers to the joint coding of the data stream at the transmitting end to reduce the symbol error rate caused by channel fading and noise. It increases the redundancy of the signal through joint coding at the transmitting end, so that the signal is received The end gains diversity gain, but the space-time coding scheme cannot increase the data rate.
(1) Space-time coding
A large number of transmission mechanisms are given in some documents. These mechanisms can respectively maximize the spectrum efficiency, the highest rate, and the signal-to-noise ratio (SNR). They all rely on channel state information (CSI, Channel State Information). The known extent of the transmitter and receiver. The CSI can be obtained at the receiving end through channel estimation, and then the transmitting end can be notified through feedback.
For transmission mechanisms that do not require CSI at the transmitting end, space-time coding can be introduced, or spatial multiplexing gain can be used to take advantage of the space dimension. Space-time coding is mainly divided into space-time trellis codes and space-time block codes. The received signal is detected by the maximum likelihood (ML, Maximum Likelihood) decoder.
The earliest space-time code is STTC (Space-Time Trellis Code). In this way, the receiver needs a multi-dimensional Viterbi algorithm. The diversity that STTC can provide is equal to the number of transmit antennas, and the coding gain provided depends on the complexity of the codeword without sacrificing bandwidth efficiency.
Space-Time Block Code (STBC, Space-Time Block Code) can provide the same diversity gain as STTC, but it has no coding gain. Also, since STBC only needs linear processing when decoding, STBC is usually used. Space-time coding technology generally assumes that CSI is completely known at the receiving end. When CSI is unknown at both ends, unitary space-time coding and differential space-time coding are proposed.
(2) Spatial reuse
Spatial multiplexing refers to the transmission of independent signals at the transmitting end, and decoding using methods such as ZF, MMSE, ML, and V-BLAST at the receiving end. It can maximize the average transmission rate of the MIMO system and can sacrifice some data rates to obtain higher diversity gain.
(3) Combination of space multiplexing and space-time coding
Combine space multiplexing and space-time coding to maximize the average data rate under the condition that each data stream obtains the minimum diversity gain.
At present, there are mainly two schemes that combine spatial multiplexing and space-time coding, link coding, and adaptive MIMO systems using block code mapping. The link coding scheme refers to a coding scheme that uses space-time coding internally and traditional channel error correction codes (TCM, convolutional codes, and RS codes) externally. This scheme can not only provide diversity gain but also increase system capacity.
Because the correlation between channels will affect the spectrum efficiency of the multi-antenna system when the channel is in an ideal state or the correlation between channels is small, the transmitter adopts a spatial multiplexing transmission scheme, and when the correlation between channels is large, space-time coding is used. Launch plan.
2. MIMO receive diversity technology
The decoding algorithms of the MIMO system at the receiving end mainly include the ZF algorithm, MMSE algorithm, decision feedback decoding algorithm, maximum likelihood decoding algorithm, and layered space-time processing algorithm (bell labs layered space-time, BLAST).
Among them, the zero-forcing algorithm and the MMSE algorithm are linear algorithms, while the decision decoding algorithm, the maximum likelihood decoding algorithm, and the layered space-time processing algorithm are non-linear algorithms.
At the receiving end of the SIMO or MIMO communication link, the receiver or equalizer uses the multipath signal to reconstruct the transmitted signal. In the non-frequency selective SIMO channel, the optimal receiving mechanism is Maximum Ratio Combining (MRC);
For frequency-selected SIMO channels, the optimal receiving mechanism is ML detection, but it is non-linear, and its complexity is exponentially related to the number of antennas (linear decoders can be used instead, but performance will decrease).
The ZF equalizer can eliminate the inter-symbol interference ISI (InterSymbol Interference) through the inverse of the channel but at the cost of amplifying the noise.
The MMSE receiver can make a trade-off between noise amplification and ISI cancellation. Decision Feedback Equalizer (DFE), a sub-optimal nonlinear mechanism based on decision feedback, can be used to improve the performance of linear equalizers. It eliminates part of the ISI generated by the previous symbol from the current symbol through a feedback filter.
ML and linear equalization can be extended to MIMO channels. The problem related to MIMO receivers is the existence of multi-stream interference (MSI, Multistream). MSI can cause mutual interference between multiple data streams.
Non-linear continuous cancellation equalizer or V-BLAST equalizer can convert MIMO channels into parallel channels, but this mechanism may have error propagation.
3. Beamforming technology in the MIMO system
(1) The system model of the eigen beamforming MIMO system is r=Hs+n, and the channel matrix H is subjected to singular value decomposition. If the channel information is known at the transmitting end, the eigen beamforming at the transmitting end and linear processing at the receiving end can be used to transform the MIMO. The channel is divided into parallel sub-channels.
If the transmitter does not know the channel state information, in a multi-user environment, a random beamforming method can be used to achieve multi-user diversity.
(2) Combination of beamforming and space-time coding In most cases, it is reasonable to assume that part of the CSI information is known at the transmitting end, so a hybrid mechanism combining space-time coding and beamforming is proposed.
Space-time coding and beamforming are two different transmit diversity technologies. Space-time coding is an open-loop diversity technology, and no channel information is needed at the transmitting end;
Array beamforming is a closed-loop diversity technology, which uses channel feedback information for spatial filtering or interference suppression. The accuracy of channel feedback will seriously affect the effect of beamforming.
When the sender obtains part of the channel state information (such as channel average or channel covariance matrix), the transmission strategy (beamforming or space-time coding) can be selected according to the channel information.
The weight of beamforming is determined by the feedback channel information under the condition of ensuring that the receiving end meets the requirements of signal-to-noise ratio and bit error rate. It points out that combining power allocation, beamforming and space-time coding to jointly optimize the transmitter without adding equipment. Under the condition of complexity and loss of transmission rate, it provides better performance than traditional space-time coding.
In short, the performance metrics that describe the characteristics of the MIMO smart antenna transceiver are Mean Square Error (MSE), SNR, Bit Error Rate (BER), reachable throughput, required to transmit power, and Channel capacity, transmission, and reception mechanisms are optimized according to these criteria.
The design of its transceiver should pay special attention to the following 4 key parameters:
(1) The reliability of CSI at the transmitting end and receiving end;
(2) The characteristics of the transmitted signal (modulation, multiplexing, and training information);
(3) Performance measurement to be optimized;
(4) Computational complexity.
Second, the advantages of MIMO smart antennas
In mobile communication systems, multipath and multipath delay extension are the main problems in mobile communication. Multipath propagation will cause severe signal fading, and delay spread will cause intersymbol interference, which will seriously affect the quality of communication links.
At the same time, co-channel interference is the main limiting factor for the capacity of mobile communication systems, which will affect the reuse of effective network resources (frequency, time) by users.
MIMO Smart antennas can improve link quality by using multipath, increase system capacity by reducing mutual interference, and allow different antennas to transmit different data. In short, the advantages of smart antennas can be summarized as follows:
1) Increasing coverage. Coherent reception of signals by the antenna array at the receiving end can produce array or beamforming gain, which is proportional to the number of receiving antennas.
2) Power reduction/cost reduction Smart antennas optimize the transmission of specific users, which can reduce the transmission power, thereby reducing the cost of the amplifier.
3) Improving link quality/increasing reliability.
The forms of diversity include time diversity, frequency diversity, code diversity, and space diversity.
When using MIMO smart antennas to sample the spatial domain, spatial diversity occurs. In a non-frequency selective fading MIMO channel, the maximum spatial diversity order is equal to the product of the number of transmitting antennas and the number of receiving antennas.
Multiple transmit antennas can generate transmit diversity by using a special modulation and coding mechanism, and the receive a diversity of multiple receive antennas depends on the combination of independent fading signals.
4) Increase spectrum efficiency
Accurately controlling the transmission power through different methods will reduce co-channel interference, thereby increasing the number of users using the same resources.
Realization of space division multiple access (SDMA) through beamforming can achieve resource multiplexing, thereby increasing data rate and spectrum efficiency.
This gain is also called spatial multiplexing gain.
In the MIMO system, multiple independent spatial dimensions are used to simultaneously transmit data. In an uncorrelated Rayleigh fading MIMO channel, the channel capacity is proportional to the minimum number of transmitting and receiving antennas.
MIMO Smart antennas are usually designed to focus on one of the above-mentioned gains, such as beamforming, diversity gain, and multiplexing gain. The trade-off between these gains has recently become the focus of research.
Third, smart antenna technology in future mobile communication systems
Future mobile communication systems require signal processing technologies that can be adapted to various communication environments.
Therefore, the initial stage of future MIMO smart antenna design must carefully consider the compromise between performance and complexity.
1. Reconfigurability of the physical layer
In order for the mobile communication transceiver to work in an environment where multiple parameters are continuously changing, it is necessary to adopt a reconfigurable adaptive technology in the transceiver to adjust the structure to obtain the best performance.
The reconfigurability in the MIMO smart antenna transceiver can be regarded as the intelligent switching of the transceiver structure in various environments.
2. Optimization between different layers
The interaction between the high levels defined by the OSI (Open System Interconnection) model can improve the performance of the entire system. The smart antenna is designed by combining the parameters of the physical layer, the link layer, and the network layer, that is, the design takes into account the relationship between the layers, rather than considering a single layer.
Practice shows that it is inefficient to consider the performance evaluation of the design method of one layer alone. For example, when scheduling is introduced, the gain obtained by space-time coding will decrease or even disappear.
The information exchanged between different layers of OSI can be classified as follows:
(1) CSI: It is necessary to estimate the channel impulse response, positioning information, vehicle speed, signal strength, interference strength, interference model, etc.
(2) QoS-related parameters: including time delay, throughput, bit error rate, packet error rate (PER, Packet Error Rate), etc.
(3) Physical layer resources: including space processing mechanism, number of antenna arrays, loss of battery power, etc.
It is very important to consider optimization criteria between layers.
In the actual system, the link quality of the smart antenna not only depends on the data detection method adopted but also depends on the specific coding mechanism and the medium access control (MAC, Medium Access Control) function adopted at the link layer. The performance of the protocol stack used in the upper layer.
Therefore, the above factors should be considered comprehensively when designing, rather than considering a single factor alone. For delay-insensitive services, smart antenna technology such as V-BLAST has been combined with the Hybrid Automatic Repeat Request (H-ARQ) mechanism.
3. Multi-user diversity
In multi-user communication, a communication method called opportunity mechanism has been paid attention to. The basic idea is to multiplex by assigning channels to users who are most likely to complete continuous transmission.
This can maximize the throughput of the system. For reflective spatial channels, the opportunistic beamforming method will point to users with the highest SNR;
On the other hand, in the case of sufficient scattering, the opportunity mechanism will allocate channels to those users with the highest instantaneous capacity. The opportunity mechanism can generate multi-user diversity, which can be a supplement to code diversity, time diversity, frequency diversity, or space diversity.
But affecting the design of the MAC protocol, MAC will abandon the conflict detection mechanism and turn to the multi-user mechanism.
4. Actual performance evaluation
In the future mobile communication system, the use of smart antennas mainly depends on the results of two studies:
(1) In the design stage of the future system, the characteristics of smart antennas and mobile communication environments, such as propagation characteristics, antenna array configuration, business mode, interference situation, and signal bandwidth effectiveness, must be considered to ensure compatibility;
(2) According to the key parameters related to the future system, the actual performance of the MIMO smart antenna is evaluated through the optimization compromise between link-level simulation and system-level simulation.
Fourth, summary
The use of multi-antenna technology in 3G based on CDMA technology can effectively reduce multiple access interference, and space-time processing can greatly increase the capacity of the CDMA system.
The rational use of MIMO smart antenna technology will greatly improve the performance of future mobile communication systems.
Besides the MIMO smart antenna technology in 4G article, you may also be interested in the below articles.
4G vs 5G: What is the difference between 4G and 5G?
How to Choose the Best Antenna for Lora?