Guowang Miao

Distributed Interference-Aware Energy-Efficient Power Optimization

Power optimization techniques are becoming increasingly important in wireless system design since battery technology has not kept up with the demand of mobile devices. They are also critical to interference management in wireless systems because interference usually results from both aggressive spectral reuse and high power transmission and severely limits system performance. In this paper, we develop an energy-efficient power optimization scheme for interference-limited wireless communications. We consider both circuit and transmission powers and focus on energy efficiency over throughput. We first investigate a non-cooperative game for energy-efficient power optimization in frequency-selective channels and reveal the conditions of the existence and uniqueness of the equilibrium for this game. Most importantly, we discover a sufficient condition for generic multi-channel power control to have a unique equilibrium in frequency-selective channels. Then we study the tradeoff between energy efficiency and spectral efficiency and show by simulation results that the proposed scheme improves both energy efficiency and spectral efficiency in an interference-limited multi-cell cellular network.

Energy Efficient Design in Wireless OFDMA

Energy-efficient transmission is an important aspect of wireless system design due to limited battery power in mobile devices. We consider uplink energy-efficient transmission in OFDMA systems since mobile stations are battery powered. We account for both circuit and transmit power when designing energy-efficient communication mechanisms and emphasize energy efficiency over peak rates or throughput. Both link adaptation and resource allocation schemes are developed to optimize the overall bits transmitted per Joule of energy, which allows for maximum energy savings in a network. Our simulation results show that the proposed schemes significantly improve energy efficiency.

Energy-Efficient Uplink Multi-User MIMO

This paper addresses optimal energy-efficient design for uplink (UL) MU-MIMO in a single cell environment. The energy efficiency is measured by throughput per Joule, while both RF transmission power and device electronic circuit power are considered. We define the energy efficiency (EE) capacity for UL MU-MIMO and study the power allocation that achieves this capacity. First we assume all users consume a fixed amount of circuit power and show that user antennas should be used only when the corresponding spatial channels are sufficiently good and using them improves the overall network EE. Mobile devices may have improved circuit management capability and turn off circuit operations when some antennas are not used to reduce circuit power consumption. Therefore we further study energy-efficient UL MU-MIMO with improved circuit management and show that some antennas should not be used even when their channel states are good because turning them on consumes too much circuit power. Based on theoretical analysis, we further develop low-complexity yet globally optimal energy-efficient power allocation algorithms that converge to the optimum exponentially. Simulation results are provided to demonstrate the significant gain in network energy efficiency.

Interference-Aware Energy-Efficient Power Optimization

While the demand for battery capacity on mobile devices has grown with the increase in high-bandwidth multi-media rich applications, battery technology has not kept up with this demand. Therefore power optimization techniques are becoming increasingly important in wireless system design. Power optimization schemes are also important for interference management in wireless systems as interference resulting from aggressive spectral reuse and high power transmission severely limits system performance. Although power optimization plays a pivotal role in both interference management and energy utilization, little research addresses their joint interaction. In this paper, we develop energy-efficient power optimization schemes for interference-limited communications. Both circuit and transmit powers are considered and energy efficiency is emphasized over throughput. We note that the general power optimization problem in the presence of interference is intractable even when ideal user cooperation is assumed. We first study this problem for a simple two-user network with ideal user cooperation and then develop a practical non-cooperative power optimization scheme. Simulation results show that the proposed scheme improves not only energy efficiency but also spectral efficiency in an interference-limited cellular network.

Energy-Efficient Transmission in Frequency-Selective Channels

Energy efficiency is becoming increasingly important for small form factor mobile devices, as battery technology has not kept up with the growing requirements stemming from ubiquitous multimedia applications. This paper addresses link adaptive transmission for maximization of energy efficiency rather than throughput. We extend our previous results for flat fading OFDMA to frequency-selective channels. Different from existing water-filling power allocation schemes that maximize throughput subject to overall transmit power constraints, our scheme adapts both overall transmit power and its allocation according to the states of all subchannels and circuit power consumption to maximize energy efficiency. We demonstrate the existence of a unique globally optimal link adaptation solution and provide iterative algorithms to obtain this optimum. Simulation results show at least a 15% improvement in energy utilization when frequency selectivity is exploited.

Low-Complexity Energy-Efficient OFDMA

Energy efficient communications in wireless communications is very important as mobile devices are battery-constrained. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget, due to the RF power requirements for reliable communications over long distances. Our previous work in this area demonstrated significant energy savings in uplink cellular OFDMA transmissions, with iterative approaches maximizing the instantaneous bits-per-Joule energy efficiency. In this paper, we use a time-averaged bits-per-Joule metric to develop low-complexity schemes. Specifically, we obtain closed-form solutions for energy-efficient link adaptation in frequency-selective channels. We also derive closed-form approaches for the maximum arithmetic and geometric mean energy-efficient schedulers. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions.

Interference management for multiple device-to-device communications underlaying cellular networks

We study the problem of interference management for device-to-device (D2D) communications where multiple D2D users may coexist with one cellular user. The problem is to optimize the transmit power levels of D2D users to maximize the cell throughput while preserving the signal-to-noise-plus-interference ratio (SINR) performance for the cellular user. This is the so-called multi rate power control problem. We investigate the problem under two assumptions, the availability of the instantaneous or average channel state information (CSI) at the base station. In the first case, D2D transmit power levels adapt to fast fading, whereas in the second case, they only adapt to slow fading. In the latter assumption, the cellular user has a maximum outage probability requirement. With numerical results, we study the trade-off between the signaling overhead, that is frequent CSI feedbacks, and the overall system performance, that is the maximum achievable cell capacity, for D2D communications underlying cellular networks.

Base-Station Sleeping Control and Power Matching for Energy–Delay Tradeoffs With Bursty Traffic

In this paper, we study sleeping control (SC) and power matching (PM) for a single cell in cellular networks with bursty traffic. The base station (BS) sleeps whenever the system is empty and wakes up when N users are assembled during the sleep period. The service capacity of the BS in the active mode is controlled by adjusting its transmit power. The total power consumption and average delay are analyzed, and based on this, the impact of parameter N and transmit power on the energy-delay tradeoff is studied. It is shown that, given the average traffic load, the more bursty the traffic is, the less total power consumed, although the delay performance of more bursty traffic is better only under certain circumstances. The optimal energy-delay tradeoff is then obtained through joint SC and PM optimization. The relationship between the optimal control parameters and the asymptotic performance are also provided. Moreover, the influence of the traffic autocorrelation is explored, which shows less impact on the system performance compared with that of the burstiness. Numerical results show the energy saving gain of the joint SC and PM scheme, as well as the impact of burstiness on the optimal energy-delay tradeoff.

Energy Efficient Pilot and Link Adaptation for Mobile Users in TDD Multi-User MIMO Systems

In this paper, we develop an uplink pilot and downlink link adaptation approach to improve the energy efficiency (EE) of mobile users in time division duplexing (TDD) multi-user multiple input and multiple output (MU-MIMO) systems. Assuming reciprocity between uplink and downlink channels, the downlink transmission is based on uplink channel estimation. While more uplink pilot power ensures more accurate channel estimation and better downlink performance, it incurs higher energy consumption of mobile users. This paper reveals the relationship and tradeoff among pilot power, channel estimation, and downlink link adaptation that achieves the highest energy efficiency for mobile users. We show that the energy efficiency of different users can be decoupled because the downlink average throughput of each user is independent of the pilot powers of other users and energy-efficient design can be done on a per-user basis. Based on the analysis, we propose an uplink pilot and downlink link adaptation algorithm to improve the EE of mobile users. Simulation results are finally provided to demonstrate the significant gain in energy efficiency for mobile users.

Energy-efficient scheduling for downlink multi-user MIMO

Multi-user MIMO is the enabling technology for LTE-Advanced systems to meet IMT-Advanced targets. The gain of multi-user MIMO is achieved partially through advanced user-grouping, user-scheduling, and precoding. Traditionally, multiuser MIMO scheduling focuses solely on spectral-efficiency [1]. That is, the scheduler will strike to balance the cell-edge user spectral-efficiency as well as the cell-average spectral-efficiency. Similar to spectral-efficiency, energy-efficiency is becoming increasingly important for wireless communications. The energy efficiency is measured by a classical measure, “throughput per Joule”, while both RF transmit power and device electronic circuit power consumptions are considered. In this paper, an energy-efficient proportional-fair scheduling is proposed for downlink multi-user MIMO systems. To specific, the scheduling algorithm is proposed to balance cell-edge energy-efficiency and the cell-average energy-efficiency. The energy-efficient proportional-fair metric is defined and the optimal power allocation maximizing the performance measure is identified. System level evaluation suggests that multi-user MIMO could improve the energy-efficiency of a wireless communication system significantly.