Energy-Spectral Efficiency Trade-Off in Virtual MIMO Cellular Systems

Abstract

Abstract-Virtual multiple-input multiple-output (V-MIMO) technology promises significant performance enhancements to cellular systems in terms of spectral efficiency (SE) and energy efficiency (EE). How these two conflicting metrics scale up in large cellular V-MIMO networks is unclear. This paper studies the EE-SE trade-off of the uplink of a multi-user cellular V-MIMO system with decode-and-forward type protocols. We first express the trade-off in an implicit function and further derive closed-form formulas of the trade-off in low and high SE regimes. Unlike conventional MIMO systems, the EE-SE trade-off of the V-MIMO system is shown to be susceptible to many factors including protocol design (e.g., resource allocation) and scenario characteristics (e.g., user density). Focusing on the medium and high SE regimes, we propose a heuristic resource allocation algorithm to optimize the EE-SE tradeoff. The fundamental performance limits of the optimized V-MIMO system are subsequently investigated and compared with conventional MIMO systems in different scenarios. Numerical results reveal a surprisingly chaotic behavior of V-MIMO systems when the user density scales up. Our analysis indicates that low frequency reuse factor, adaptive resource allocation, and user density control are critical to harness the full benefits of cellular V-MIMO systems.Index Terms-Energy efficiency, spectral efficiency, virtual MIMO, adaptive resource allocation.

5G green cellular networks considering power allocation schemes

“…η=0.38, the RF circuit power for an antenna P dyn = 83W and the fixed power consumption in a BS is P sta = 45.5W [46,47]. Figure 4 illustrates the energy efficiency of MIMO random cellular networks versus the number of transmitting antennas N t and the intensity ratio of MSs to BSs λ M /λ B , where "WF" denotes the waterfilling power allocation scheme and "AV" represents the average power allocation scheme.…”

Linear Processing Design of Amplify-and-Forward Relays for Maximizing the System Throughput

“…Recently, energy efficient (EE) resource allocation for MIMO cooperative communication has become attractive, such as [22][23][24][25][26][27]. Reference [22] considers the energy efficient joint source-relay power allocation problem for MIMO AF relaying system.…”

“…Then, the authors in [22] propose a relaxation method according to the Jensen inequality to solve the pseudo-convex problem. [23] studies the energy-spectral efficiency (EE-SE) trade-off of the uplink of a multi-user cellular virtual MIMO system. Finally, a heuristic resource allocation algorithm is proposed to optimize the EE-SE tradeoff in [23].…”

“…[23] studies the energy-spectral efficiency (EE-SE) trade-off of the uplink of a multi-user cellular virtual MIMO system. Finally, a heuristic resource allocation algorithm is proposed to optimize the EE-SE tradeoff in [23]. The energy-efficient resource allocation for OFDMA cellular networks with user cooperation is studied by [24].…”

Energy Efficiency Optimization for Uplink Multiuser MIMO Systems

“…According to information theory [5][6], with the increasing of serving mobile users, the system can obtain a higher multiplex gain at the cost of diversity gain. In order to exploit the channel capacity, there exists an optimal user number to make a tradeoff between the diversity gain and multiplexing gain.…”