This paper studies beamforming techniques for energy efficiency maximization (EEmax) in multiuser multiple-input single-output (MISO) downlink system. For this challenging nonconvex problem, we first derive an optimal solution using branch-and-reduce-and-bound (BRB) approach. We also propose two low-complexity approximate designs. The first one uses the well-known zero-forcing beamforming (ZFBF) to eliminate inter-user interference so that the EEmax problem reduces to a concave-convex fractional program. Particularly, the problem is then efficiently solved by closed-form expressions in combination with the Dinkelbach's approach. In the second design, we aim at finding a stationary point using the sequential convex approximation (SCA) method. By proper transformations, we arrive at a fast converging iterative algorithm where a convex program is solved in each iteration. We further show that the problem in each iteration can also be approximated as a second-order cone program (SOCP), allowing for exploiting computationally efficient state-of-the-art SOCP solvers. Numerical experiments demonstrate that the second design converges quickly and achieves a near-optimal performance. To further increase the energy efficiency, we also consider the joint beamforming and antenna selection (JBAS) problem for which two designs are proposed. In the first approach we capitalize on the perspective reformulation in combination with continuous relaxation to solve the JBAS problem. In the second one, sparsity-inducing regularization is introduced to approximate the JBAS problem, which is then solved by the SCA method.Numerical results show that joint beamforming and antenna selection offers significant energy efficiency improvement for large numbers of transmit antennas.
Index TermsMISO broadcast channel, energy efficiency, Dinkelbach method, mixed-integer programming, sequential convex approximation, second-order cone programming, fractional programming, antenna selection. 4 and mean squared error minimization [6]. Huang et al. [17] aimed at finding the Pareto boundary in MISO interference channel. Apart from the Dinkelbach's approach, [18] considered EEmax with userspecific signal-to-interference-plus-noise ratio (SINR) constraints by proposing ZFBF power allocation and zero-gradient based joint beamforming and power allocation strategy in multi-user MIMO downlink 1053-587X (c)
G radio for millimeter-wave (mm-wave) and beyond-5G concepts at 0.1-1 THz can exploit angle and delay measurements for localization through an increased bandwidth and large antenna arrays, but they are limited in terms of blockage caused by obstacles. Reconfigurable intelligent surfaces (RISs) are seen as a transformative technology that can control the physical propagation environment in which they are embedded by passively reflecting radio waves in preferred directions and actively sensing this environment in receive and transmit modes. While such RISs have mainly been intended for communication purposes, they can provide great benefits in terms of performance, energy consumption, and cost for localization and mapping. These benefits as well as associated challenges are the main topics of this article.
ApplicationsThe interaction between the digital and physical worlds relies on high-definition situational awareness, i.e., the ability of a device to determine its own location as well as that of objects and other devices in the operating environment. Applications include automated vehicles and robots, in general, as well as health care, highly immersive virtual and augmented reality, and new human-to-machine interfaces. Situational awareness can be achieved with a variety of technologies, depending on the application and requirements, including lidar, inertial measurement units, and cameras. Additional technologies include radio-based ones such as satellite positioning, radar, ultrawideband, cellular, and Wi-Fi. Such technologies are attractive because they can have dual communication and sensing functionalities and are often less susceptible to environmental factors, such as poor lighting.Since 4G, dedicated localization reference signals have been considered part of communications system design and standardization. These can enable location accuracy levels on the order of 10 m. With 5G, the use of larger bandwidths and higher carrier frequencies, in combination with antenna arrays in user equipment (UE) and base stations (BSs), is expected to further improve location accuracy to roughly 1 m. Within beyond-5G systems, the trend is to operate at much higher frequencies
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