Access Point Switch ON/OFF Strategies for Green Cell-Free Massive MIMO Networking

Abstract

The combination of user-centric network densification and distributed massive multiple-input multiple-output (MIMO) operation has recently brought along a new paradigm in the wireless communications arena, referred to as cell-free massive MIMO networking. In these networks, a large number of distributed access points (APs), coordinated by a central processing unit (CPU), cooperate to coherently serve a large number of mobile stations (MSs) in the same time/frequency resource. Similar to what has been traditionally done with conventional cellular networks, cell-free massive MIMO networks will be dimensioned to provide the required quality of service (QoS) to MSs under heavy traffic load conditions, and thus they might be underutilized during low traffic load periods, leading to an inefficient use of both spectral and energy resources. Aiming at the implementation of green cell-free massive MIMO networks, this paper proposes and analyzes the performance of different AP switch ON/OFF (ASO) strategies designed to dynamically turn ON/OFF some of the APs based on the number and/or location of the active MSs in the network. The proposed framework considers line-of-sight (LOS) and non-line-of-sight (NLOS) links between APs and MSs, the use of different antenna array architectures at the access points (APs), suitably characterized by array-dependent spatial correlation matrices, and specific power consumption models for APs, MSs and fronthaul links between the APs and the CPU. Numerical results show that the use of properly designed ASO strategies in cell-free massive MIMO networks clearly improve the achievable energy efficiency. Moreover, they also reveal the existing trade-offs among the achievable energy efficiency, the available network-state information, and the hardware configuration (i.e., number of APs, number of transmit antennas per AP, and number of MSs). INDEX TERMS AP ON/OFF switching, green networking, cell-free massive MIMO, zero-forcing precoding.

Energy-Efficient Access-Point Sleep-Mode Techniques for Cell-Free mmWave Massive MIMO Networks With Non-Uniform Spatial Traffic Density

“…Remarkably, these mathematical expressions are able to account for the fact that there is a limited number of active RF chains at each of the APs in the network. • In contrast to previous works on switch on/off algorithms for cell-free massive MIMO networks (see, for instance, [25], [26]), this study contemplates a realistic model to describe a non-uniform distribution of mobile stations (MSs), thus capturing the heterogeneous nature of spatial traffic density in practical wireless networks [27]. • Aside from recasting existing adaptive ASO techniques to the scenario at hand, novel ASO strategies are implemented that rely on statistical goodness-of-fit (GoF) tests, and govern the process of (de)activating APs in such a way that the distribution of the resulting active AP matches the non-uniform spatial distribution of MSs.…”

“…This is the rational behind the GoF methods presented next. The performance provided by these ASO schemes will be benchmarked against that provided by three of the ASO strategies previously proposed in [25], that have been suitably adapted to the mmWave scenario. :…”

“…For those cases in which M A < K, instead, a set of M A virtual MSs is first generated by relying on the k-means clustering method and the previously described procedure is then applied to the virtual MSs to select the set of active APs. A detailed explanation of this ASO strategy can be found in [25]. It is important to note at this point that the pace at which the APs would have to be switched on/off under this strategy would be so high that it would be hardly implementable in practice.…”

“…Typically, these strategies are combined with specific forms of user association and cell zooming (i.e., cell breathing) see [21]- [24]) that boost their performance. Very recent research in [25] has shown that the application of switch on/off algorithms in the context of cell-free massive MIMO, whereby APs are dynamically (de)activated, has proved effective in optimizing the energy efficiency of the network. However, this work, which was framed in a sub-6 GHz context, relied on the assumption of having homogenously distributed users in the spatial domain, a condition seldom met in practice.…”

Cell-Free Massive MIMO : Scalability, Signal Processing and Power Control

“…Uplink processing MMSE [59,124,145,146] ZF [147] Power allocation and load balancing [148] Max-min power control [149] Pilot power control [150] Sequential linear MMSE [120] mmWave Limited fronthaul capacity [151] Power control [152] Channel modeling [153] Energy efficiency [154] Energy Efficiency [116,132,[155][156][157] Imperfect Fronthaul [158][159][160][161][162][163][164] Low Resolution ADCs [163,[165][166][167] Hardware Impairments [164,[168][169][170] Non-orthogonal [171][172][173][174][175] Multiple Access…”