Cross-layer energy-efficiency optimization for multiuser full-duplex decode-and-forward indoor relay networks at 60 GHz

The impact of overhead on spectral efficiency for different cooperative relaying schemes is quantitatively analyzed in [1], in which half-duplex (HD) relaying is assumed for all cooperative nodes. With the recent development of cancellation methods for full-duplex (FD) relays or radios, FD has become feasible in practical implementations, providing a higher spectral efficiency than HD. In this paper, we model the residual self-loop interference and cross-talk interference caused by imperfect channel estimation, which is an extra overhead for FD compared with that of HD. Then, we analyze the overhead, outage probability and spectral efficiency of three typical cooperative relaying schemes (timer-based best-select, distributed space-time-coded relaying and M-group) operating in FD mode. Finally, numerical results are provided to compare the outage probability and spectral efficiency of HD and FD relaying.

Cell discontinuous transmission (DTX) has been proposed as a solution to reduce the energy consumption of cellular networks. This paper investigates the impact of network traffic load on the spectral and energy efficiency of cellular networks with DTX. The signal-to-interference-plus-noise ratio (SINR) distribution as a function of traffic load is derived first. Then, the sufficient condition for ignoring thermal noise and simplifying the SINR distribution is investigated. Based on the simplified SINR distribution, the network spectral and energy efficiency as functions of network traffic load are derived. It is shown that the network spectral efficiency increases monotonically in traffic load, while the optimal network energy efficiency depends on the ratio of the sleep-mode power consumption to the active-mode power consumption of base stations. If the ratio is larger than a certain threshold, the network energy efficiency increases monotonically with network traffic load and is maximized when the network is fully loaded. Otherwise, the network energy efficiency first increases and then decreases in network traffic load. The optimal load can be identified with a binary search algorithm. The power ratio threshold depends solely on the path loss exponent α, e.g., 56% for α = 4. All these analytic results are further validated by the numerical simulations.

Research into cutting-edge systems that can satisfy the rising needs for greater data rate and increased reliability is becoming more and more necessary as wireless communication technologies continue to evolve. To enhance the spectral and energy efficiencies, this study examine the performance of massive multiple input multiple output (mMIMO) communication systems using wavelet-order orthogonal frequency division multiplexing (W-OFDM). Also, a communication system was created based on W-OFDM Massive MIMO using MATLAB to model its operation. The simulated system's various stages of operation was examined through detailed analysis and its performance was compare with prior studies and practical networks on OFDM. Key performance metrics, specifically the data throughput, was evaluated to assess the effectiveness and viability of the system. The simulation results indicates that W-OFDM can achieve up to 35% reduction in peak-to-average-power-ratio (PAPR) compared to the traditional OFDM, with a 20% improvement in BER performance under Rayleigh fading conditions. Also, the spectral efficiency of W-OFDM mMIMO outperforms convectional OFDM by 15%, making it a viable technology for future communication networks requiring high data rates and reliability. This implies that, the analytical evaluation confirms that W-OFDM mMIMO provides substantial benefits for improving energy and spectral efficiencies in wireless communication systems, addressing the challenges of increased user demands for high spectrum. This study contributes to the understanding of MIMO systems' performance optimization, highlighting the importance of antenna configuration and cell distance. Comprehensive analysis of spectral efficiency and energy efficiency trade-offs in MIMO systems and identification of optimal antenna configuration for maximum energy efficiency, addressing some of the challenges of future wireless communication systems.

Underlay in-band device-to-device (D2D) multicast communication, where the same content is disseminated via direct links in a group, has the potential to improve the spectral and energy efficiencies of cellular networks. However, most of the existing approaches for this problem only address either spectral efficiency (SE) or energy efficiency (EE). We study the tradeoff between SE and EE in a single cell D2D integrated cellular network, where multiple D2D multicast groups (MGs) may share the uplink channel with multiple cellular users. We explore SE-EE tradeoff for this problem by formulating the EE maximization problem with constraint on SE and maximum available transmission power. A power allocation algorithm is proposed to solve this problem and its efficacy is demonstrated via extensive numerical simulations. The tradeoff between SE and EE as a function of density of D2D MGs, and maximum transmission power of an MG is characterized.

We consider a point-to-point wireless commu-nication with a multilevel quadrature amplitude modulation (M-QAM) and energy constraints. In this context, this paper addresses the problem of the spectral and energy efficiency trade-off for a realistic system model. Our researches focus on the power amplifier model, which depends on transmission power, drain efficiency and peak-to-average ratio (PAR). While they have been extensively studied in previous research, far too little attention has been paid to the influence of PAR and drain efficiency in the spectral and energy efficiency trade-off. This study provides new insights into the estimation of the system energy consumption and the choice of the optimal spec-tral efficiency while introducing a realistic system model based on a hardware-dependent power amplifier energy. Furthermore, we investigate the influence of PAR and drain efficiency parameters on this trade-off. Our study reveals that this hardware-dependent system model plays a significant role in energy saving, and that the induced reduction of spectral efficiency goes in the direction sought by embedded systems. Moreover, our research underlines the importance of considering the drain efficiency exponent as having a real impact on the energy consumption.

Energy efficiency is a basic need of the fifth-generation (5G) wireless networks, because the energy sources and capability of the battery are very narrow against the huge demand. Massive MIMO is a great invention of 5G cellular network with a large number of antennas. In this research, the prime aim is to maximize the energy efficiency and spectral efficiency simultaneously of massive MIMO system. Spectral and energy efficiency are formulated with fixed power, number of users, number of antennas with the impact of multiple users and without the impact of multiple users, the ratio of number of antennas and number of users. Trade-off also has been analyzed among the co-located, distributed and hybrid massive MIMO with the Nakagami-m fading channel, which can subtract the co-channel interference in a system and compared with each other. From the simulation results, it is seen that the energy efficiency of distributed massive MIMO is higher than the other two with the variation of fixed power, number of user and the ratio of number of antenna and number of user with respect to spectral efficiency. The energy efficiency of co-located massive MIMO is higher than the other two with the variation of number of antenna.

We study the effect of imperfect channel estimation (ICE) on the error probability performance of M-level quadrature amplitude modulation ( M-QAM) with maximal-ratio combining and equal-gain combining diversity formats in Nakagami fading channels. We provide a novel formulation of the bit-error rate (BER) of M-QAM with ICE in terms of the signal constellation-dependent effective signal-to-noise ratios (SNRs) or amplitudes, which allows us to derive the general, accurate, and easy-to-evaluate BER formulas for square and rectangular diversity M-QAM with channel estimation errors. Our result shows that the performance loss caused by ICE may be manifested by the signal decision space distortion and a scaling of the effective SNR. Using our analytical result, we evaluate the performance of M-QAM with pilot-symbol assisted modulation and present some insightful findings

With the ubiquitous data-rate demand in cellular networks, total power consumption is growing rapidly. Thus, it is essential to design the future networks with energy and spectral efficient strategies. Using heterogeneous networks (HetNets) is one possible way of improving spectral and energy efficiencies in cellular networks. In this paper, under coverage ratio and area spectral efficiency constraints, we consider deploying strategies with low power small cells in order to improve the spectral and energy efficiencies of the conventional macrocell only cellular network. To compare the efficiencies of different scenarios, we employ area spectral efficiency and power consumption per bit criterion. As a result, we observe that deploying microcells increases both energy and spectral efficiencies.

In fifth-generation cellular networks (5G), a large multiple-input multiple-output (MIMO) technique is critical for optimizing the trade-off between energy efficiency (EE) and spectral efficiency (SE). The challenges for the next generation depend on increasing the high data traffic in the wireless communication system for both EE and SE. The trade-off between EE and SE in downlink massive MIMO systems has been investigated in this paper using the first derivative of transmit antennas and transmit power. The EE-SE trade-off has been investigated using a multi-objective optimization problem to reduce transmit power. The EE and SE based on constraint maximum transmits power allocation and a number of antennas by computing the first derivative of transmit power to maximize the trade-off EE - SE has been improved. The optimal trade-off between EE and SE can be obtained based on the first derivative by selecting the optimal antennas with a low cost of transmit power showing good simulation results. Therefore, based on an optimal optimization problem is flexible to make trade-offs between EE-SE for distinct preferences.

10 - Improving energy efficiency in next-generation IoT networks with beam adjustment technique

Due to the increased energy consumption of cellular access networks, energy efficiency of the systems should be considered jointly with spectral efficiency to obtain the overall performance metrics and trade-offs. Downlink coordinated multipoint (CoMP) joint transmission aided cell switch off schemes can mitigate inter-cell interference and increase energy efficiency by using the active cells to serve the users in the switched off cell. However, the performance of this newly proposed scheme is heavily dependent on the accuracy of the selected CoMP joint transmission set. In this paper, we model the multi-point channel estimation enabled via channel state information reference symbols (CSI-RS) introduced in 3GPP release 10 systems and simulate possible scenarios that would lead to inaccurate transmission set clustering: multi-point channel estimation errors and possible CoMP system delays due to CSI transfers, node processing delays and network topology limitations. In order to mitigate the effects of channel estimation errors and system delay, we propose a framework for multi- point channel estimation in CoMP systems using a time-varying interpolation filter which tracks each multipath delay tap separately for every measured point. Possible performance gains with different filter lengths are demonstrated. Simulation results are presented to show the effectiveness of the proposed scheme. In addition, proof of concept is provided for CoMP adaptive time-varying multi-point estimation filter designs, where the UEs which are being served by higher cluster degrees need to enlarge the estimation filter memory spans only for the points which are more likely to be included in the joint transmission set.

Not only high spectral efficiency (SE) but also high energy efficiency (EE) are required for future wireless communication systems. Radio orbital angular momentum (OAM) provides a new perspective of mode multiplexing to improve SE. However, there are few studies on the EE performance of OAM mode multiplexing. In this paper, we investigate the SE and EE of a misaligned uniform concentric circle array (UCCA)-based multi-carrier multimode OAM and multiple-input multiple-output (MCMM-OAM-MIMO) system in the line-of-sight (LoS) channel, in which two transceiver architectures implemented by radio frequency (RF) analog synthesis and baseband digital synthesis are considered. The distance and angle of arrival (AoA) estimation are utilized for channel estimation and signal detection, whose training overhead is much less than that of traditional MIMO systems. Simulation results validate that the UCCA-based MCMM-OAM-MI-MO system is superior to conventional MIMO-OFDM system in the EE and SE performances.

In this paper, the power allocation problem for downlink massive multiple-input multiple-output (MIMO) systems with inter-user interference is investigated considering the tradeoff between energy efficiency (EE) and spectral efficiency (SE). The minimum mean-square-error channel estimate and the rigorous closed-form expression of achievable downlink rate are first derived. Then, the multi-objective optimization problem (MOP) is formulated subject to maximum total transmission power constrain, where conflicting EE and SE are maximized simultaneously. To obtain the solution set characterized as a Pareto set, the MOP is transformed into a single-objective problem (SOP) using weighted sum method. We further convert the SOP into a convex optimization problem by adding an additional interference constraint, and the optimal power allocation algorithm is proposed by using dual method to balance EE and SE efficiently. Simulation results demonstrate the effectiveness of the proposed algorithm and illustrate the fundamental tradeoff between EE and SE for different parameter settings.

In this paper, we study upper and lower bounds on the achievable sum-rate of an uncorrelated multiple-input multiple-output (MIMO) multiple access channel (MAC) for Gaussian input signals and with channel estimation error at the receiver. We prove that the gap between the mutual information bounds does not exceed a certain value for arbitrary input covariance matrices and at any input transmit power. We also prove that in a MIMO MAC with uniform input power utilization over the transmit antennas, the gap between the mutual information bounds increases monotonically as the input power of each user increases. Furthermore, we show that the gap between the bounds is maximum when beamforming is applied at the transmitters of all users. We also derive the transmit directions that maximize the mutual information lower and upper bounds when delayed feedback is available from the receiver to the transmitters, and characterize the power allocation of this system in terms of its beamforming range. Numerical simulations are conducted to corroborate our theoretical results and quantify the effect of imperfect channel estimation.

In this paper, the tradeoff relationship between the spectral efficiency (SE) and energy efficiency (EE) of homogenous cellular networks in which the BSs are arbitrarily distributed is investigated. The network performance metrics of SE and EE are assessed subject to a downlink transmission outage constraint in interference-limited operational environments. The EE is expressed in closed form as a function of SE, based on which the performance bounds of the network are derived. Unlike the traditional inverse relationship between SE and EE, it is found in this paper that there exists an operational regime for which both the SE and EE increase while satisfying the outage requirement, and the density of base stations (BSs) simultaneously sharing the spectrum is optimal. The difference in the performance achieved for the SE when operating in the EE maximizing mode as compared with the SE maximizing mode strongly depends on the received signal-to-interference ratio (SIR) threshold. In the SE-EE tradeoff regime, the analytical tools from microeconomics theory are applied to determine the optimal BS density with respect to the utility achieved by the network operator via balancing the SE and EE objectives. Numerical results show that, by tuning a preference factor toward either the SE or EE metrics, it is feasible to realize Pareto optimal performance.