This paper introduces a novel channel inversion (CI) precoding scheme for the downlink of phase shift keying (PSK)-based multiple input multiple output (MIMO) systems. In contrast to common practice where knowledge of the interference is used to eliminate it, the main idea proposed here is to use this knowledge to glean benefit from the interference. It will be shown that the system performance can be enhanced by exploiting some of the existent inter-channel interference (ICI). This is achieved by applying partial channel inversion such that the constructive part of ICI is preserved and exploited while the destructive part is eliminated by means of CI precoding. By doing so, the effective signal to interference-plus-noise ratio (SINR) delivered to the mobile unit (MU) receivers is enhanced without the need to invest additional transmitted signal power at the MIMO base station (BS). It is shown that the trade-off to this benefit is a minor increase in the complexity of the BS processing. The presented theoretical analysis and simulations demonstrate that due to the SINR enhancement, significant performance and throughput gains are offered by the proposed MIMO precoding technique compared to its conventional counterparts.

Index Terms-Energy efficiency (EE), non-orthogonal multiple access (NOMA), simultaneous wireless information and power transfer (SWIPT), time switching (TS).

Spectral efficiency (SE) and energy efficiency (EE) are the main metrics for designing wireless networks. Rather than focusing on either SE or EE separately, recent works have focused on the relationship between EE and SE and provided good insights into the joint EE-SE tradeoff. However, such works have assumed that bandwidth are fully occupied regardless of the transmission requirements and therefore are only valid for this scenario. In this paper, we propose a new paradigm for EE-SE tradeoff, namely the resource efficiency (RE) for orthogonal frequency division multiple access (OFDMA) cellular network in which we take into consideration different transmission-bandwidth requirements. We analyse the properties of the proposed RE and prove that it is capable of exploiting the tradeoff between EE and SE by balancing consumption power and occupied bandwidth; hence simultaneously optimizing both EE and SE. We then formulate the generalized RE optimization problem with guaranteed quality of service (QoS) and provide a gradient based optimal power adaptation scheme to solve it. We also provide an upper bound near optimal method to jointly solve the optimization problem. Furthermore, a low-complexity suboptimal algorithm based on uniform power allocation scheme is proposed to reduce the complexity. Numerical results confirm the analytical findings and demonstrate the effectiveness of the proposed resource allocation schemes for efficient resource usage.

Heterogeneous network (HetNet) deployment is considered a de facto solution for meeting the ever increasing mobile traffic demand. However, excessive power usage in such networks is a critical issue, particularly for the mobile operators. Characterizing the fundamental energy efficiency (EE) performance of HetNets is therefore important for the design of green wireless systems. In this paper, we address the EE optimization problem for downlink two-tier HetNets comprised of a single macrocell and multiple pico-cells. Considering a heterogeneous realtime and non-real-time traffic, transmit beamforming design and power allocation policies are jointly considered in order to optimize the system energy efficiency. The EE resource allocation problem under consideration is a mixed combinatorial and nonconvex optimization problem, which is extremely difficult to solve. In order to reduce the computational complexity, we decompose the original problem with multiple inequality constraints into multiple optimization problems with single inequality constraint. For the latter problem, a two-layer resource allocation algorithm is proposed based on the quasiconcavity property of EE. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation algorithm can efficiently approach the optimal EE. Index Terms-Green radio (GR), energy efficiency (EE), heterogeneous network (HetNet), resource allocation.

No abstract

Impulsive noise (IN) is one of the most dominant factors responsible for degrading the performance of power-line communication systems. One of the common techniques for mitigating IN is blanking which is applied at the front end of the receiver to zero the incoming signal when it exceeds a certain threshold. Determining the optimal blanking threshold (OBT) is, however, key for achieving the best performance. Most reported work to find the OBT is based on the availability of the long-term characteristics of IN at the receiver. In this paper, we consider orthogonal frequency-division multiplexing (OFDM)-based power-line communications and propose a method for finding the OBT without requiring any knowledge about the IN. We show that there is a direct relationship between the OBT and the peak-to-average power value of the OFDM symbol and utilize it to identify the OBT. The results reveal that the proposed technique not only eliminates the need to prior knowledge about the characteristics of IN but also achieves a gain between 0.5-2.5 dB depending on the accuracy of the signal peak-to-average estimate. It will also be shown how the performance of the proposed method can be further enhanced by employing some basic signal per processing at the transmitter.Index Terms-Blanking, impulsive noise, Middleton class-A noise, orthogonal frequency-division multiplexing (OFDM), peak-to-average power (PAPR), power-line communications (PLC), signal-to-impulsive-noise ratio (SINR), signal-to-noise ratio (SNR).

No abstract

This paper presents the capacity analysis of unmanned aerial vehicles (UAVs) communications supported by flying intelligent reflecting surfaces (IRSs). In the considered system, some of the UAVs are equipped with an IRS panel that applies certain phase-shifts to the incident waves before being reflected to the receiving UAV. In contrast to existing work, this letter considers the effect of imperfect phase knowledge on the system capacity, where the phase error is modeled as a von Mises random variable with parameter κ. Analytical results, corroborated by Monte Carlo simulations, show that the achievable capacity is dependent on the phase error, however, the capacity loss becomes negligible at high signal-to-noise ratio (SNR) and when κ ≥ 6.