By intelligent networking, all the end devices would be aware of the location and features of BSs/APs in their vicinity, and all of the BSs/APs would be aware of the locations, features, and QoS requirements of devices in their vicinity. Robust interference management/optimization techniques can be applied to maximize the efficiency of the wireless network. Central processing units will be fast enough to manage and switch the resources (bandwidth, time, power) among multiple end-users, and data processing will be conducted at the base-band processing units (BPUs). Figure 3 depicts some of the major components in the 6G system architecture, that will cause a major paradigm shift towards the realization of 6G standards. The air interface is the main component that causes a major improvement in the wireless generations. Orthogonal frequency division multiplexing (OFDM) played a major role in the development of 4G, as code division multiple access (CDMA) was the key player in 3G. Similarly, the development of the new air interface will be an essential component of 6G system architecture.
IRS can reduce the hardware complexity at the receiver and the transmitter by reducing the number of antennae installed at them, thereby, reducing the radio frequency (RF) chains at the transmitter and the receiver. IRS can replace the conventional relays system due to its advantages in terms of power, spectral efficiency, and reduced hardware complexity [56]. IRS can be used in the deep-fade and non-line-of-sight (NLOS) communication environment. The principle by which SINR is enhanced at the receiver is optimally controlling the phases of the incident ray at multiple elements of the IRS, to produce useful beamforming at the receiver [56]. Degradation factors such as noise and interference have no impact on the IRS. All these features of the IRS make it a promising technique for the B5G/6G communication systems.
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A new dimensional property of the electromagnetic waves (EW) was discovered in the 1990s termed as the orbital angular momentum (OAM). This discovery promised the transmission of multiple data streams over the same spatial channel. An EM wave carrying the OAM has the phase rotation factor of \(\exp (-jl\phi )\), where l is OAM state number represented in integer and \(\phi\) is transverse azimuth angle [57,58,59]. The main advantage of OAM over other beamforming techniques is that OAM can have an unlimited number of orthogonal modes, which allows the EW to multiplex multiple data streams over the same spatial channel, thereby, enhancing the spectral efficiency and transmission capacity. OAM support a high number of user in mode division multiple access (MDMA) scheme without utilizing extra resources (i.e., frequency, time, and power). The flexibility of OAM to be used in narrowband and wideband frequency hopping scheme makes it an attractive scheme for low probability of interception (LPI) applications. OAM-based MIMO systems have advantages over the conventional MIMO systems in terms of capacity and long-distance line-of-sight (LoS) coverage [60]. Therefore, OAM has great potential for applications in 6G wireless networks.
Researchers believe that AI will play a defining role in the IoTs and IoBNTs driven world [65]. The potential shift from 5G to the 6G will be to determine an efficient way to transmit data. The ideal system will be the one that is free from human intervention at all [66].
In previous wireless generations, wireless systems were using either fixed duplexing (TDD/FDD) such as in the case of 1G, 2G, 3G, and 4G or flexible duplexing in the case of 5G [86,87,88]. Whereas, with the progress in the development of duplexing technologies, 6G is expected to use full free duplex in which all users are allowed to use complete resources simultaneously. Users can use all resources (i.e., space, time, and frequency) in a free duplex mode that eventually improves latency and throughput.
Presently, government bodies are monitoring the spectrum and allocating the spectrum to the operators. The owner of the spectrum has the full right to use that spectrum. Any other operator cannot use the spectrum allocated to some other operator. This is only due to the non-development of efficient spectrum monitoring or spectrum managing techniques at present. Therefore, as AI and blockchain are anticipated as key technologies in 6G, robust spectrum monitoring and spectrum management strategies are expected to be developed for the 6G roll-out. The network resources can be dynamically controlled by AI-aided 6G systems. Therefore, free spectrum sharing will become a reality in 6G.
In the context of free spectrum sharing techniques, NOMA is proposed to be a promising multiple access candidate for B5G/6G communication systems. In NOMA, a complete resource block (frequency band and time slot) is assigned to all users simultaneously, whereas the users are distributed in the power domain. The weakest user receives the maximum power from the BS, whereas the strong users apply the SIC to the composite NOMA signal to cancel out the messages of the weak users and finally extract their own messages. However, the number of SIC increases exponentially with the increase in the number of users, which increases the complexity of the NOMA system. User cooperation in NOMA can be used to alleviate outage problems of weak users and to provide diversity at the expense of more time slots. However, the number of SICs even becomes larger with the number of cooperating time slots. Space-time block coding-based NOMA (STBC-NOMA) is proposed as an alternative to reduce the number of time slots while keeping the same diversity order [89].
Apart from imperfect SIC, the imperfection in the channel state information (CSI) also affects the performance of NOMA systems. We present a comparative analysis of the impact of imperfect CSI on the performance of non-cooperative NOMA, conventional cooperative NOMA (CCN), STBC-aided cooperative NOMA, and conventional orthogonal multiple access (OMA) schemes in Fig. 7. For a fair comparison between all schemes, we use the same total power budget for all of them. The channel from BS to the users and between users is considered as flat-fading Rayleigh channel. Fig. 7a shows the average capacity of the weakest user vs. the total number of users for OMA, non-cooperative NOMA, STBC-NOMA [90, 91], and conventional cooperative NOMA (CCN) [40] schemes with perfect CSI. Fig. 7b and Fig. 7c depict that with perfect channel state information (pCSI), CCN outperforms OMA, non-cooperative NOMA, and STBC-NOMA schemes. However, with the impairments of imperfect CSI (ipCSI), the performance of CCN is severely degraded, where the impact of ipCSI on the STBC-NOMA is much lesser than that of CCN. As shown in Fig. 7c, with the ipCSI = -15 dBm, the STBC-NOMA outperforms the CCN scheme, whereas the impact of ipCSI on the OMA scheme is negligible. These schemes can be further explored in the future for providing massive connectivity with band-limited applications.
The next-generation wireless communication system will consist of massive self-organizing and self-healing robots. All these intelligent robots/devices will require high computation power. Therefore, the need for energy will be increasing with the increase in intelligent robots. Currently, traditional GPUs are not meeting the energy efficiency requirements of next-generation wireless networks communication networks. In such a scenario, an energy-efficient and scalable intelligent network design will be required. The industry has moved towards IoTs, IoEV and IoBTs [107, 109]. We have sensors deployed everywhere. There is a sensor in our door, in our air conditioner, in our car, on the TV, in the refrigerator, in offices. All these sensors need energy-efficient communication.
In this paper, we covered various aspects of 6G wireless networks with different perspectives. We provided a vision for B5G/6G communications, 6G network architecture, KPI requirements, key enabling technologies, their use-cases, and network dimensions that will landmark the next generation communication systems. Furthermore, a way out is discussed how these potential technologies will meet the KPI requirements for these systems. Finally, the opportunities and research challenges such as hardware complexity, variable radio resource allocation, pre-emptive scheduling, power efficiency, the coexistence of multiple RATs, and security, privacy and trust issues for these technologies on the way to the commercialization of next-generation communication networks are presented. 2ff7e9595c
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