Delta-OMA (D-OMA): a new method of mass multiple access in 6G. Part 1
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Annotation - A new method of multiple access, namely, delta-orthogonal multiple access (D-OMA - delta orthogonal multiple access), is presented for mass access in future 6G cellular networks. D-OMA is based on the concept of distributed large coordinated non-orthogonal multiple access with multicast support (NOMA) (non-orthogonal multiple access) using partially overlapping subbands for NOMA clusters. The effectiveness of this scheme is demonstrated in terms of throughput for different degrees of overlap of the NOMA subbands. D-OMA can also be used to provide enhanced security in wireless access networks in both uplink and downlink. It also discusses implementation issues and open problems for DOMA optimization.
Keywords - 5G (B5G) / 6G, extensive wireless capabilities, coordinated reception / transmission, orthogonal and non-orthogonal multiple access, bandwidth, wireless security
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1. Introduction
Each generation of cellular wireless systems is characterized by a new method of multiple access. In particular, the systems of the first generation (1G) were based on frequency division multiple access (FDMA), while the second, third and fourth generations were based on time division access (TDMA). , code division multiple access (CDMA - code division multiple access) and orthogonal frequency division (OFDMA - orthogonal frequency division multiple access), respectively. As for the 5th generation (5G) cellular communication, although many development and standardization efforts are still ongoing, it is clear that there will be no revolutionary multi-access technology, except for using an extremely wide spectrum range (up to 60 GHz) and the adoption of non-orthogonal multiple access (NOMA) in addition to orthogonal frequency division multiple access (OFDMA) [1] - [3]. The adoption of higher frequency bands in the 5G radio interface, such as millimeter-wave (mm-wave) bands, will cause serious propagation problems due to high path loss and beam directivity requirements. Here, an ultra-dense deployment of access points (AP - access point) can help a little, which, in turn, requires complex coordination and cooperation between distributed APs in order to minimize interference effects in the co-channel caused by overlapping service areas of neighboring cells.
Nevertheless, it is expected that 5G will provide three main unique services, namely: enhanced mobile broadband (eMBB - enhanced mobile broadband communication), ultra-reliable communication with low latency and mass communication of machine type (mMTC - massive machine type type communication) [4 ]. The goal of eMBB is to provide higher data rates and enhanced coverage (compared to LTE), while ultra-reliable, low-latency services will provide authenticated services for mission-critical applications, such as autonomous driving and health monitoring devices. The role of mMTC is to manage the flow of data to / from a huge number of wireless devices with a guaranteed level of performance.
While 5G cellular networks will include many distinctive improvements over 4G networks to provide increased transmission speeds with reduced latency, increased system reliability and performance, reduced terminal device sizes and energy-efficient hardware and network designs, the emergence of advanced technologies to stimulate its further development in the direction of 5G cellular networks (B5G - beyond 5G) or the so-called sixth generation (6G). Key targets for 6G cellular networks can be summarized as follows:
2. Bezsotovaya architecture for future wireless networks
Generally speaking, the concept of cellular network architecture will not be suitable for future wireless networks, especially in urban scenarios of superdense wireless access, in which multiple wireless devices are served simultaneously using multipoint transmissions and multipoint user associations (Fig. 1). Using very fast feedback channels between different BS / APs, the entire network will look like a distributed system without mass distributed multiple inputs with multiple outputs (MIMO array) from the perspective of the end device. In particular, all access points will be aware of all active devices in their vicinity. APs can be considered as remote radio heads (RRH), as in the case of cloud radio access networks (CRAN) [5]. Each device can be served by more than RRH, either by coordinating the transmission or by multiplexing. It may be useful to consider this cell-free architecture as a generic version of the well-known coordinated reception / transmission (CoMP), in which the cooperating APs jointly serve all devices within their coverage area (devices at the cell boundary and center of the cell). This can be achieved by using very fast centralized processing units that assign resources to various end devices, while data processing can be carried out in a so-called baseband unit pool (BBU), as in the case of CRAN. With full coordination between different RRHs, interference management can be performed optimally or almost optimally within some centralized or distributed optimization methodologies.
Such a network architecture will have to connect millions of devices (for example, mMTC devices) for which automatic services must be provided without direct human interaction. Traditional orthogonal multiple access (OMA) schemes will not be sufficient, and pure non-orthogonal multiple access (NOMA) methods will not have the flexibility to support a wireless connection for devices with different service requirements [6]. Therefore, it is necessary to develop new methods of multiple access / resource allocation and interference management for these networks without cells, taking into account the limited spectrum resources. In the next section, we propose a new method of mass multiple access in such a network, which uses the 6G network architecture without a cell to support a large-scale wireless connection.
3. Delta-orthogonal multiple access (D-OMA)
This section first briefly discusses the basic principle of NOMA versus the principle of OMA. It then discusses the potential use of massive in-band NOMA in a new, cell-free network architecture. Finally, a new D-OMA scheme is being discussed and evaluated.
A. OMA v. NOMA
OMA has been used for cellular generations from 1G to 4G. Due to the orthogonality between different carriers and the relatively high bandwidth requirements among them, orthogonal frequency division division access (OFDMA - orthogonal frequency-division multiple access) used in 4G networks may not provide an effective solution for future generation networks. Therefore, the NOMA technique was recently adopted by the standards of 3GPP version 16 (5G) [7]. NOMA typically uses the concept of superimposing many signals in the power domain within the same subband and using successive interference cancellation (SIC) at the receiver side to filter out unwanted interfering signals. Using NOMA, each individual OMA subband can serve several devices at the same time, and in this process most of the transmission power is provided to those who have lower line quality (Figure 2).
In particular, in the M-device / user of the NOMA cluster, for the downlink transmission, the AP will send x = PM m = 1 √ Pmsm so that PM m = 1 Pm ≤ Pt, where Pm is the transmit power allocated to the m-th NOMA device, sm is the signal to send to the mth device, and Pt is the maximum power budget assigned to the subband of a particular NOMA cluster. Then, the received signal at the mth device is defined as ym = hmx + wm, where hm is the complex channel gain between the AP and the mth device, wm is the additive white Gaussian noise (AWGN) plus the interference signal of other clusters. If the device channel gains within a particular cluster are ordered as h1 ≤. ,, ≤ hM, then the transmit power levels will be assigned to each device, so P1 ≥. ,, ≥ PM. At the receiver side, interfering signals from devices with higher received powers are removed by SIC operation until the desired signal is decoded. Accordingly, the achievable speed on the mth device within a specific NOMA cluster of size M is given by
Where
where Im and Nm represent intercluster interference (ICI) and AWGN power at the input of the mth device, respectively. As a rule, each sub-band will serve one NOMA cluster. Devices in a particular cluster will suffer from two types of interference, namely intra-NOMA interference (INI) caused by a residual unfiltered interference signal from NOMA caused by other NOMA devices in the same cluster, and intercluster interference (ICI) caused by using the same subband by other neighboring clusters. The NOMA cluster size can be considered as a design parameter to achieve a compromise between several factors, namely the data transfer rate for devices / users, the level of complexity in the NOMA receivers, the total power budget per NOMA cluster and the NOMA device resistance to error propagation based on INI , ICI and SIC
Fig. 1: 6G network architecture without cells.
Fig. 2: NOMA concept for serving multiple wireless devices in the same sub-band.
The end of the first part.
Friends, we will soon publish a continuation of the article, but for now, according to the established tradition, we are waiting for your comments and invite you to a practical course on the theory of network interaction from OTUS.
Annotation - A new method of multiple access, namely, delta-orthogonal multiple access (D-OMA - delta orthogonal multiple access), is presented for mass access in future 6G cellular networks. D-OMA is based on the concept of distributed large coordinated non-orthogonal multiple access with multicast support (NOMA) (non-orthogonal multiple access) using partially overlapping subbands for NOMA clusters. The effectiveness of this scheme is demonstrated in terms of throughput for different degrees of overlap of the NOMA subbands. D-OMA can also be used to provide enhanced security in wireless access networks in both uplink and downlink. It also discusses implementation issues and open problems for DOMA optimization.
Keywords - 5G (B5G) / 6G, extensive wireless capabilities, coordinated reception / transmission, orthogonal and non-orthogonal multiple access, bandwidth, wireless security
')
1. Introduction
Each generation of cellular wireless systems is characterized by a new method of multiple access. In particular, the systems of the first generation (1G) were based on frequency division multiple access (FDMA), while the second, third and fourth generations were based on time division access (TDMA). , code division multiple access (CDMA - code division multiple access) and orthogonal frequency division (OFDMA - orthogonal frequency division multiple access), respectively. As for the 5th generation (5G) cellular communication, although many development and standardization efforts are still ongoing, it is clear that there will be no revolutionary multi-access technology, except for using an extremely wide spectrum range (up to 60 GHz) and the adoption of non-orthogonal multiple access (NOMA) in addition to orthogonal frequency division multiple access (OFDMA) [1] - [3]. The adoption of higher frequency bands in the 5G radio interface, such as millimeter-wave (mm-wave) bands, will cause serious propagation problems due to high path loss and beam directivity requirements. Here, an ultra-dense deployment of access points (AP - access point) can help a little, which, in turn, requires complex coordination and cooperation between distributed APs in order to minimize interference effects in the co-channel caused by overlapping service areas of neighboring cells.
Nevertheless, it is expected that 5G will provide three main unique services, namely: enhanced mobile broadband (eMBB - enhanced mobile broadband communication), ultra-reliable communication with low latency and mass communication of machine type (mMTC - massive machine type type communication) [4 ]. The goal of eMBB is to provide higher data rates and enhanced coverage (compared to LTE), while ultra-reliable, low-latency services will provide authenticated services for mission-critical applications, such as autonomous driving and health monitoring devices. The role of mMTC is to manage the flow of data to / from a huge number of wireless devices with a guaranteed level of performance.
While 5G cellular networks will include many distinctive improvements over 4G networks to provide increased transmission speeds with reduced latency, increased system reliability and performance, reduced terminal device sizes and energy-efficient hardware and network designs, the emergence of advanced technologies to stimulate its further development in the direction of 5G cellular networks (B5G - beyond 5G) or the so-called sixth generation (6G). Key targets for 6G cellular networks can be summarized as follows:
- Connected networks: the proliferation of Internet of Things (IoT) and mMTC services each wireless device will be connected to one or more wireless access networks that will be served by multiple access points (APs) or base stations (BSs), which in turn will be connected to a common cloud network to access cloud services (for example, border computing and caching services). Examples of such applications / services are virtual reality, autonomous driving, smart city and smart grid applications, industrial control and intelligent manufacturing, surveillance and security, as well as numerous health monitoring services. Wireless devices will also have a peer-to-peer connection through single or multi-hop communication. In addition, ground-based cellular systems will be integrated with on-board (or non-ground / air / unmanned) networks with mobile BS / AP. Accordingly, the traditional models of cellular systems will not be enough to describe these new systems. In addition, these networks will be networks of applications and content, not just data networks. Therefore, new methods will be needed in terms of network planning and optimization.
- Energy minimization at the device and network levels: since users, machines, APs / BSs, and other network nodes will need to use advanced signal processing techniques, as well as process more data (for example, for artificial intelligence applications and services). Power consumption will increase significantly. . In addition, energy consumption in radio transmitters (for example, in power amplifiers, analog-digital and digital-analog converters) will need to be minimized at frequencies of millimeter and nanometer waves. With an ultra-dense deployment of access points, as well as a wide deployment of peripheral computing / caching servers in a wireless access network, this will create an urgent need for new concepts of energy saving, charging, collecting, and interaction between network nodes.
- Efficient use of the spectrum and / or its expansion: the new radio (NR) 5G extends the frequency range of 4G networks (0.6–6 GHz) to several higher frequency bands (millimeter waves in the 30–300 GHz range [mmW] and optical systems in free space [FSO - freespace optical]] in the range 200-385 THz). It will be necessary to develop new technologies for wireless access and backhaul, as well as coexistence (in the case of unlicensed spectrum) in these new bands.
2. Bezsotovaya architecture for future wireless networks
Generally speaking, the concept of cellular network architecture will not be suitable for future wireless networks, especially in urban scenarios of superdense wireless access, in which multiple wireless devices are served simultaneously using multipoint transmissions and multipoint user associations (Fig. 1). Using very fast feedback channels between different BS / APs, the entire network will look like a distributed system without mass distributed multiple inputs with multiple outputs (MIMO array) from the perspective of the end device. In particular, all access points will be aware of all active devices in their vicinity. APs can be considered as remote radio heads (RRH), as in the case of cloud radio access networks (CRAN) [5]. Each device can be served by more than RRH, either by coordinating the transmission or by multiplexing. It may be useful to consider this cell-free architecture as a generic version of the well-known coordinated reception / transmission (CoMP), in which the cooperating APs jointly serve all devices within their coverage area (devices at the cell boundary and center of the cell). This can be achieved by using very fast centralized processing units that assign resources to various end devices, while data processing can be carried out in a so-called baseband unit pool (BBU), as in the case of CRAN. With full coordination between different RRHs, interference management can be performed optimally or almost optimally within some centralized or distributed optimization methodologies.
Such a network architecture will have to connect millions of devices (for example, mMTC devices) for which automatic services must be provided without direct human interaction. Traditional orthogonal multiple access (OMA) schemes will not be sufficient, and pure non-orthogonal multiple access (NOMA) methods will not have the flexibility to support a wireless connection for devices with different service requirements [6]. Therefore, it is necessary to develop new methods of multiple access / resource allocation and interference management for these networks without cells, taking into account the limited spectrum resources. In the next section, we propose a new method of mass multiple access in such a network, which uses the 6G network architecture without a cell to support a large-scale wireless connection.
3. Delta-orthogonal multiple access (D-OMA)
This section first briefly discusses the basic principle of NOMA versus the principle of OMA. It then discusses the potential use of massive in-band NOMA in a new, cell-free network architecture. Finally, a new D-OMA scheme is being discussed and evaluated.
A. OMA v. NOMA
OMA has been used for cellular generations from 1G to 4G. Due to the orthogonality between different carriers and the relatively high bandwidth requirements among them, orthogonal frequency division division access (OFDMA - orthogonal frequency-division multiple access) used in 4G networks may not provide an effective solution for future generation networks. Therefore, the NOMA technique was recently adopted by the standards of 3GPP version 16 (5G) [7]. NOMA typically uses the concept of superimposing many signals in the power domain within the same subband and using successive interference cancellation (SIC) at the receiver side to filter out unwanted interfering signals. Using NOMA, each individual OMA subband can serve several devices at the same time, and in this process most of the transmission power is provided to those who have lower line quality (Figure 2).
In particular, in the M-device / user of the NOMA cluster, for the downlink transmission, the AP will send x = PM m = 1 √ Pmsm so that PM m = 1 Pm ≤ Pt, where Pm is the transmit power allocated to the m-th NOMA device, sm is the signal to send to the mth device, and Pt is the maximum power budget assigned to the subband of a particular NOMA cluster. Then, the received signal at the mth device is defined as ym = hmx + wm, where hm is the complex channel gain between the AP and the mth device, wm is the additive white Gaussian noise (AWGN) plus the interference signal of other clusters. If the device channel gains within a particular cluster are ordered as h1 ≤. ,, ≤ hM, then the transmit power levels will be assigned to each device, so P1 ≥. ,, ≥ PM. At the receiver side, interfering signals from devices with higher received powers are removed by SIC operation until the desired signal is decoded. Accordingly, the achievable speed on the mth device within a specific NOMA cluster of size M is given by
Where
where Im and Nm represent intercluster interference (ICI) and AWGN power at the input of the mth device, respectively. As a rule, each sub-band will serve one NOMA cluster. Devices in a particular cluster will suffer from two types of interference, namely intra-NOMA interference (INI) caused by a residual unfiltered interference signal from NOMA caused by other NOMA devices in the same cluster, and intercluster interference (ICI) caused by using the same subband by other neighboring clusters. The NOMA cluster size can be considered as a design parameter to achieve a compromise between several factors, namely the data transfer rate for devices / users, the level of complexity in the NOMA receivers, the total power budget per NOMA cluster and the NOMA device resistance to error propagation based on INI , ICI and SICFig. 1: 6G network architecture without cells.
Fig. 2: NOMA concept for serving multiple wireless devices in the same sub-band.
The end of the first part.
Friends, we will soon publish a continuation of the article, but for now, according to the established tradition, we are waiting for your comments and invite you to a practical course on the theory of network interaction from OTUS.
Source: https://habr.com/ru/post/442092/
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