Reconfigurable intelligent surface aided coordinated multipoint transmission for the simultaneous wireless information and power transfer non‐orthogonal multiple access network

In this article, the bit error rate (BER) performance of a tightly packed reconfigurable intelligent surface (RIS) assisted communication system is analyzed in terms of the level of spatial correlation. In conventional models, channels are assumed to be independent and identically distributed and continuous phase shifts are available for phase compensation. However, in practice, as RIS reflecting units are arranged in more compact form (less than 0.5λ$$ \lambda $$) due to space constraints, correlation effects among the reflecting elements are to be considered. Further, discrete phase shifters are widely used to meet practical deployment limitations. These practical constraints severely affect the error performance of the system. It necessitates that the impact of spatial correlation and discrete phase shifts on the BER performance of the system is to be analyzed. The instantaneous signal to noise ratio is the square of the sum of correlated random variables. In order to analyze the BER performance accurately, the exact statistical distribution for the sum of spatially correlated random variables is to be chosen. In this work, appropriate distribution fitting is chosen based on the level of spatial correlation. Numerical BER expressions are derived with the chosen statistical distributions. The analysis on the impact of spatial correlation and discrete phase shifter on BER performance would be more beneficial for design and practicing engineers in the field of 6G wireless communications.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

BER analysis of tightly packed planar RIS system using the level of spatial correlation and discrete phase shifter

Thirumavalavan¹,

Hariharan²,

Thiruvengadam³

2022

“…11 This, in turn, adds an additional level of freedom, and thus, enables a larger number of users. [12][13][14][15] Accordingly, NOMA has the potential capabilities to support the proliferation of IoT network while meeting the unprecedented requirements of B5G networks. 16 Furthermore, due to the fact the users with weaker channels are served with higher power levels, NOMA can guarantee long-term fairness between the communicating devices in terms of the achieved quality of services (QoS).…”

Section: Introductionmentioning

confidence: 99%

“…Unlike conventional OMA mechanisms, multiple NOMA‐based users can be concurrently served over the same resource block using the power‐domain multiplexing techniques 11 . This, in turn, adds an additional level of freedom, and thus, enables a larger number of users 12‐15 . Accordingly, NOMA has the potential capabilities to support the proliferation of IoT network while meeting the unprecedented requirements of B5G networks 16 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Joint bandwidth and power resource allocation technique in multi‐carrier non‐orthogonal multiple access‐based cognitive Internet of Things networks

Al‐Obiedollah

Arabiat

Al-Ajlouni

et al. 2022

The recent development of the Internet of Things (IoT) devices offers an intelligent concept for integrating massive number of interconnected wireless devices. However, supporting such massive number of IoT connections (hundreds of billions) requires an efficient and dynamic spectrum access strategy. Accordingly, the integration of non‐orthogonal multiple access (NOMA) in the cognitive radio (CR) systems, referred to as a multi‐carrier NOMA CR‐enabled system, is envisioned as a potential spectrum‐efficient networking paradigm that can support massive energy‐efficient IoT connectivity in B5G networks while maintaining the quality of services (QoS) of the IoT devices. However, the power consumption issue of the multi‐carrier NOMA CR‐based system becomes as one of key challenges, especially when considering the expected massive connectivity. Accordingly, several power‐aware optimization frameworks have been considered to address this issue. While most of the existing CR‐based multi‐carrier NOMA power allocation mechanisms only optimize the allocated per‐user power, this article proposes a novel joint bandwidth and power allocation problem over each available idle channel with the aim of minimizing the overall transmission power under a set of QoS constrains. Specifically, the bandwidth of each channel is adaptively subdivided into two variable‐width sub‐channels, each is capable to serve a group of CR users using power‐domain NOMA. This novel design is formulated as a joint optimization problem that is shown to be a non‐convex. Therefore, an iterative algorithm with a second‐order cone programming is deployed to handle the non‐convexity of the problem, and thus, determine the solution of it. Simulation results reveal that the developed variable bandwidth adaptive power allocation mechanism outperforms the conventional equal sub‐channel allocation in terms of the required transmission power, which significantly improves the energy efficiency in the system.

Two‐timescale optimization approach for coordinated multi‐point design in unmanned aerial vehicle‐assisted cellular networks

Abdelhakam

Elmesalawy

Ibrahim

et al. 2022

Thanks to their mobility, flexibility, and adaptive altitude, unmanned aerial vehicles (UAVs) have been admitted for several applications in wireless communication systems. In particular, UAVs can function as aerial base stations (BSs) to increase cellular network capacity and provide persistent coverage. Due to the line-of-sight channels between UAVs and user equipments (UEs), strong co-channel interference may be generated in the network. In this article, a joint transmission coordinated multi-point technique is considered in the downlink cellular network to effectively manage the interference brought by UAVs. A two-timescale optimization approach is proposed to prevent exchanging absurd messages and channel information between the transmission points. The objective of the proposed method is to maximize the sum rate of the network subject to the constraints on UEs' quality of service as well as per-ground BS and per-UAV total transmitted power. The proposed approach is decomposed into long-term and short-term problems. The long-term problem aims to jointly optimize the UEs' clusters, the UAVs' locations, and the initial transmit beamforming vectors based on large-scale channel gain. This problem is a mixed-integer nonlinear programming optimization problem, which is nondeterministic polynomial hard. Meanwhile, the short-term problem requires obtaining the transmit beamforming vectors according to the overall channel vector. This problem is also a non-convex optimization problem. To address these challenges, two algorithms are proposed based on difference of convex functions programming and successive convex approximation technique to deal with these two problems. Extensive simulations show that the performance of the proposed approach outperforms the comparable algorithms.