Green communications have been emerged as a demanding concept for improving the network energy efficiency (EE). In this paper, a pricing-based approach is investigated to achieve energy-efficient power allocation in relay-assisted multiuser networks. We introduce a network price to the power consumption as a penalty for the achievable sum rate, and study its impact on the tradeoff between the EE and the spectral efficiency (SE). It is hard to directly solve the problem as it is non-convex, and thus a concave lower bound on the pricing-based utility is applied to transform the problem into a convex one. Through dual decomposition, a q-price algorithm is proposed for iteratively tightening the lower bound and finding the optimal solution. In addition, an optimal price that enables green power allocation is defined and found from the viewpoint of maximizing EE. We further analyze the optimal power allocation strategies of the pricing-based approach in a two-user case under different noise operating regimes, yielding on-off, water-filling, and channel-reversal approaches, etc. Finally, the performance of the proposed approach is evaluated by computer simulations, and we characterize the interaction between the EE and SE for various network parameters when the network is designed from the energy-efficient perspective.Index Terms-Green communications, multiuser relay networks, energy efficiency, power allocation.

In this work, the feasibility of spectrum sharing between a multiple-input multiple-output (MIMO) radar system (RS) and a MIMO cellular system (CS), comprising of a full duplex (FD) base station (BS) serving multiple downlink and uplink users at the same time and frequency is investigated. While a joint transceiver design technique at the CS's BS and users is proposed to maximise the probability of detection (PoD) of the MIMO RS, subject to constraints of quality of service (QoS) of users and transmit power at the CS, null-space based waveform projection is used to mitigate the interference from RS towards CS. In particular, the proposed technique optimises the performance of PoD of RS by maximising its lower bound, which is obtained by exploiting the monotonically increasing relationship of PoD and its non-centrality parameter. Numerical results show the utility of the proposed spectrum sharing framework, but with certain trade-offs in performance corresponding to RS's transmit power, RS's PoD, CS's residual self interference power at the FD BS and QoS of users.Index Terms-Multiple-input multiple-output (MIMO), fullduplex (FD), spectrum sharing, MIMO radar, quality-of-service (QoS), transceiver design, convex optimization.

The rapid growth of energy consumption due to the strong demands of wireless multimedia services, becomes a major concern from the environmental perspective. In this paper, we investigate a novel energy-efficient resource allocation scheme for relay-assisted multiuser networks to maximize the energy efficiency (EE) of the network by jointly optimizing the subcarrier pairing permutation formed in one-to-many/many-toone manner, subcarrier allocation, as well as the power allocation altogether. By analyzing the properties of the complex mixedinteger nonlinear programming (MINLP) problem, which is generally very difficult to solve in its original form, we transform the problem into an equivalent convex problem by relaxing the integer variables using the concept of subcarrier time sharing, and by applying a successive convex approximation (SCA) approach. Based on the dual decomposition method, we derive an optimal solution to the joint optimization problem. The impact of different network parameters, namely number of subcarriers and number of users, on the attainable EE and spectral efficiency (SE) performance of the proposed design framework is also investigated. The numerical results are provided to validate the theoretical findings and to demonstrate the effectiveness of the proposed algorithm for achieving higher EE and SE than the existing schemes.

In this paper, an energy efficiency maximization (EEM) optimization problem for the multiuser multicarrier energy-constrained amplify-and-forward (AF) multi-relay network is formulated under the total source transmit power budget and energy-causality constraints. We consider that each relay node is solely powered by the source nodes, employing energy harvesting time-switching (EHTS) protocol to harvest the energy through the ambient radio-frequency (RF) signal transmitted from the source nodes under the simultaneous wireless information and power transfer (SWIPT) paradigm. First, we propose a subcarrier and energy causality-based multi-relay selection policy. Second, we jointly optimize the parameters that control the energy efficiency (EE) of the system namely multi-relay selection, subcarrier pairing, user allocation, power allocation, and RF EHTS time block, that renders the problem to be a mixed integer non-linear programming problem (MINLP) which remains NP-hard to solve. Hence, we remodel the problem to a tractable quasi-concave form by applying a string of convex transformations. Later, we propose an iterative EEM algorithm to optimize the multi-parameter problem. Further, a suboptimal and best relay selection algorithm is studied by trading-off between complexity and performance. The effectiveness of the proposed algorithms is demonstrated by simulation results.

In this paper, we investigate a full duplex (FD) multiuser non-orthogonal multiple access (NoMA) communication system, based on the optimization of received signalto-interference-plus-noise ratio (SINR) per unit power. Since the communication system operates in FD mode, co-channel interference (CCI) and self-interference (SI) dominate the system's performance. Accordingly, to combat the CCI, we adopt a gametheoretic approach and propose users clustering algorithms and to suppress the SI, we formulate an optimization problem to maximize the power-normalized SINR (PN-SINR). While the user clustering optimization problem is constrained by i) the successive interference cancellation (SIC) constraint and ii) two binary constraints for the allocations of UL and DL users, the PN-SINR problem is constrained by i) total transmit power budget at the base station and uplink (UL) users, ii) the fundamental condition for the implementation of successive interference cancellation in NoMA, and iii) the minimum fairness condition for UL users. The original PN-SINR problem is non-convex and hence is converted into an equivalent subtractive-form problem, after which we propose an iterative algorithm to find the optimal power allocation policy. Properties of all the proposed algorithms are thoroughly investigated and numerical results are provided. Based on the channel conditions and suppression level of SI and CCI, the superiority of the proposed FD-NoMA system over half duplex NoMA and FD orthogonal multiple access systems is verified.

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An intelligent reflecting surface (IRS) is an emerging technology in the next-generation (B5G and 6G) wireless communications with the aim of improving the spectral/energy efficiency of the wireless networks. In this paper, we focus on multiple IRS-aided multiuser multiple-input single-output (MISO) downlink network, where each IRS is deployed near to the cell boundary of the cellular network in order to help the downlink transmission to the cell-edge users. To achieve the significant performance benefits provided by the rate-splitting (RS) transmission in multiuser scenario, two-layer hierarchical rate splitting (2L-HRS) technique is deployed at the base station (BS) to serve all the users. Furthermore, we propose an On-Off scheme for controlling the IRSs with practical phase shifts. In order to analyze the performance of the users, we derive the closed-form expressions of outage probability for both cell-edge users and near users. By extensive Monte Carlo simulations, we demonstrate that the proposed design framework outperforms the corresponding one-layer RS (1L-RS), the multiuser linear precoding (MU-LP) and 2L-HRS without IRS. In addition, we reveal the advantages of introducing RS-based IRS in improving the cell-users' performance. The impact of channel estimation errors due to imperfect channel state information, and the various network's parameters, such as the number of reflecting elements and the number of cell-users, on the network performance is demonstrated.INDEX TERMS Intelligent reflecting surface (IRS), rate splitting (RS), multiple-input single-output (MISO), downlink, multiuser.KESHAV SINGH (Member, IEEE) received the M.Sc. degree in information and telecommunications technologies from Athens Information Technology, Greece, in 2009, and the Ph.D. degree in communication engineering from

The networking paradigm of spectrum sharing is a promising technology to solve the spectrum paucity that has resulted from the exponential increase in the number of wireless devices and ubiquitous services. In light of the novel concept of Authorized/Licensed Shared Access, in this work, we consider the spectrum sharing between a collocated multiple-input-multipleoutput (MIMO) radar and a full-duplex (FD) MIMO cellular communication system consisting of a FD base station (BS) serving multiple downlink and uplink users simultaneously, without hindering the detection probability of the radar. The main objective is to develop an optimization technique at the cellular system for jointly designing the transceiver for the cellular BS and power allocation vectors for uplink users that can maximize the detection probability of radar, while guaranteeing a pre-defined quality-of-service for each user and power budget for the uplink users and BS. The original problem is non-convex and thus, we convert the non-convex problem into a secondorder cone and propose an iterative algorithm to find the optimal solution. Numerical results are then provided to demonstrate the feasibility of the spectral coexistence and show a scalable tradeoff in performance of both systems.