After the read, you will know what is MIMO and what is Massive MIMO.
MIMO
In radio, multiple-input and multiple-output, or MIMO is a method for multiplying the capacity of a radio link using multiple transmission and receiving antennas to exploit multipath propagation. MIMO has become an essential element of wireless communication standards including IEEE 802.11n (Wi-Fi), IEEE 802.11ac (Wi-Fi), HSPA+ (3G), WiMAX, and Long Term Evolution (4G LTE).
More recently, MIMO has been applied to power-line communication for 3-wire installations as part of ITU G.hn standard and HomePlug AV2 specification.
Classification of MIMO
According to the number of antennas of base stations and mobile phones, it can be divided into four types: SISO, SIMO, MISO, and MIMO. Their English meanings are as follows:
- SISO
Single Input Single Output (Single Input Single Output)
- SIMO
Single Input Multiple Output (Single Input Multiple Output)
- MISO
Multiple Input Single Output (Multiple Input Single Output)
- MIMO
Multiple Input Multiple Output (Multiple Input Multiple Output)
MIMO Technology
MIMO technology means that the capacity and spectrum utilization rate of the communication system can be doubled without increasing the bandwidth.
It can be defined as the existence of multiple independent channels between the transmitting end and the receiving end, which means that there is sufficient spacing between the antenna elements.
Therefore, the correlation of the signal between the antennas is eliminated, the signal link performance is improved, and the signal link performance is increased. Data throughput.
Research shows that under Rayleigh fading channel environment. OFDM systems will use MIMO technology to increase capacity.
Adopting the MIMO system is an effective way to improve spectrum efficiency. Multipath fading is the main factor affecting communication quality, but MIMO systems can effectively use the impact of multipath to increase system capacity.
The system capacity is limited by interference, and the system capacity cannot be increased by increasing the transmission power. However, the MIMO structure can obtain high system capacity without increasing the transmission power.
Therefore, combining MIMO technology with OFDM technology is the development trend of the next generation of wireless local area networks.
In the OFDM system, the use of multiple transmit antennas is actually to apply multiple transmit antenna technology on each sub-channel as needed. Each sub-channel corresponds to a multi-antenna subsystem and an OFDM system with multiple transmit antennas.
The equipment under development consists of two sets of IEEE802.11a transceivers, two transmitting antennas and two receiving antennas (2×2), and a MIMO system responsible for the processing process.
It can achieve a maximum transmission rate of 108Mbit/s and support APs and customers. The transmission rate between the terminals is 108Mbit/s; when the client does not support this technology (in the case of the IEEE802.11a client), the communication rate is 54Mbit/s.
MIMO System
MIMO wireless communication system is one of the key technologies for future mobile and wireless communication systems. An obvious feature of the MIMO system is that it has extremely high spectrum utilization efficiency. On the basis of making full use of existing spectrum resources, it can obtain two gains in reliability and effectiveness by using space resources. The cost is to increase the transmitter and receiver. End processing complexity.
MIMO Key Module
1. MIMO system channel model modeling
The performance of the MIMO system depends to a large extent on the channel model. Although there are already standardized wireless propagation models, and many kinds of MIMO channel models have been provided on the basis of a large amount of actual measurement and theoretical research work, they have not yet been adopted by the ITU. Approved standardized MIMO channel model (3GPP has developed a channel model standard for MIMO).
Therefore, understand and master the characteristics of wireless MIMO channels in indoor and outdoor environments, establish static models and specific dynamic models of MIMO channels, and select appropriate system structures and design excellent signal processing algorithms to realize the potentially huge channels of MIMO systems Capacity and achieving the expected performance are crucial.
2. MIMO system capacity
Compared with the traditional single-antenna system, the MIMO system has greatly improved both in performance and data transmission rate.
The first to conduct an in-depth analysis of the channel capacity of the MIMO system is Telestar and Foschini, which are respectively for Gaussian noise The study of the capacity of the MIMO system under the following shows that under the assumption that the antennas are independent of each other, the multi-antenna system is significantly improved than the single-antenna system.
Considering a wireless transmission system with M transmit antennas and N receiving antennas, when the receiving end can accurately know the channel transmission characteristics, Foschini’s research shows:
When M=N, the channel capacity that increases in proportion to N is obtained. Under the same transmission power and transmission bandwidth, the channel capacity of this system is about 40 times higher than that of the single-in-single-out (SISO) system.
3. MIMO antenna array design
Generally, the base station antennas are set up relatively high, and the near-field scattering around the antenna array is relatively weak. Therefore, in order to obtain irrelevant signals on different array elements, it is often necessary to maintain at least 10 times the wavelength spacing between the array elements.
When the number of antennas is large, there may be obstacles to the erection of the base station line array. For mobile terminals, since the near-field scatterers are abundant, it is generally believed that the antenna array element spacing is more than 1/2 wavelength to make the signal correlation weak enough.
The polarized antenna array can use mutually orthogonal polarization states at the same spatial position to realize the uncorrelation of the array elements, so the size of the antenna array can be relatively reduced.
4. Signal processing of MIMO system
The array antenna communication system in a fading environment faces co-channel interference and inter-symbol interference. In order to approximate the capacity of a multi-antenna system, a good signal processing technique is required.
High-performance, low-complexity signal detection methods or joint detection methods have always been a hot topic for researchers.
5. The complexity of the MIMO system
Since the signal in the MIMO system is extended to space-time two-dimensional, compared with a single-antenna system, the complexity of its channel estimation, channel equalization, decoding, and detection links will increase with the number of antennas or signal modulation order. Increased sharply, and the amount of algorithm calculations will directly affect processing delay, device power consumption and standby time.
At the same time, in practical applications, a key factor limiting the MIMO system is the expensive cost brought about by multiple radio frequency links.
To reduce the computational complexity of software, provide simpler and more effective signal processing methods and various space-time coding and decoding schemes for MIMO systems.
Antenna selection is a very critical technology for reducing hardware costs. It can greatly reduce processing complexity and hardware costs while maintaining the advantages of MIMO technology. It is a research focus to push MIMO systems into practical use.
6. Diversity and multiplexing of the MIMO system
The essence of the MIMO system is to provide diversity gain and multiplexing gain. The former ensures the transmission reliability of the system, and the latter increases the transmission rate of the system.
It is worth discussing to maximize the gain of the system by using the two modes of MIMO system diversity and multiplexing reasonably.
7. (Multi-cell) multi-user MIMO system
In theory, the capacity domain of the multi-user MIMO system has been solved, but how to make the capacity domain meet the requirements of various users for the transmission rate is still not well solved.
Furthermore, in the broadcast channel, due to the inter-antenna and inter-user interference in the MIMO system, how to design the transmission vector to eliminate the co-channel interference between users, and how to control the system capacity and the specific QoS power of each user when the power is limited The optimization problem and the related technology when there are multi-cell multi-user systems are still the research focus.
Basic principles of MIMO technology
MIMO technology refers to the use of multiple transmitting antennas and receiving antennas at the transmitting end and the receiving end so that signals are transmitted and received through multiple antennas at the transmitting end and the receiving end, thereby improving communication quality.
It can make full use of space resources and achieve multiple transmissions and multiple receipts through multiple antennas. Without increasing spectrum resources and antenna transmission power, it can double the system channel capacity, showing obvious advantages and being regarded as the next generation of mobile the core technology of communication.
The essence of MIMO technology is to provide the system with spatial diversity gain and spatial multiplexing gain.
Massive MIMO
The rapid popularization of smart terminals has pushed the demand for mobile data services to a higher level, resulting in a serious shortage of spectrum resources. The main challenges of large-scale technology include pilot pollution, beamforming, precoding, and high-performance signal detection.
Technical advantages
Massive MIMO technology uses a large number of antennas to serve a relatively small number of users, which can effectively improve spectrum efficiency.
Research institutions at home and abroad have conducted in-depth research on large-scale technologies around throughput, transmission power efficiency, precoding, and receiver design.
On the other hand, energy consumption efficiency is another key performance indicator. Massive MIMO can not only effectively increase the system channel capacity, but also significantly improve the energy efficiency of the wireless system.
MIMO vs Massive MIMO
Performance comparison between massive MIMO and traditional MIMO
Compared with traditional MIMO, massive MIMO has many characteristics.
Pilot pollution has become a key limiting factor for massive MIMO technology. This is because as the number of base station antennas increases, users in adjacent cells use the same set of (or non-orthogonal) training sequences in uplink channel estimation, resulting in The channel estimation result at the base station is not the channel between the local user and the base station, but the estimation polluted by the training sequence sent by users in other cells.
In addition, problems such as channel measurement, modeling and estimation, beamforming/precoding and detection design, and hardware complexity will also limit the implementation of massive MIMO systems.
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