Spectral-energy efficiency tradeoff in Cognitive Radio networks with peak interference power constraints

Haider, Fourat; Wang, Cheng-Xiang; Hong, Xuemin; Harald,; Yuan, Dongfeng; Hepsaydir, Erol

doi:10.1109/icct.2011.6157898

Cited by 8 publications

(13 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Equation (8) indicates that obtaining an explicit expression of E MIMO boils down to finding an explicit formula for f −1 (C MIMO ). However, due to the random Rayleigh channel realizations in (2), f −1 (C MIMO ) cannot be straightforwardly formulated.…”

Section: Energy Efficiency Analysis Of Mimo Channelsmentioning

confidence: 99%

“…(9) Proof : According to (8), when S MIMO is small (correspondingly P is small), the value of E MIMO is dominated by the circuit power P c . In contrast, E MIMO is more sensitive and needs a more accurate expression when P is large.…”

Section: A Ee Ub For Iid Mimo Channelsmentioning

confidence: 99%

“…The first attempt to analyze the relation of EE and SE is given in [4], where an EE approximation is derived according to the first and the second derivatives of the capacity equation. Using the same approximation method, the work is then extended to relay networks in [5] and [6], where a full duplex mode at the relay is considered in [5] and half duplex considered in [6]; the work is also extended to virtual-MIMO networks in [7] and cognitive radio networks in [8]. These approximations of EE are accurate in the low SE region but largely inaccurate otherwise.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the Relation Between Energy Efficiency and Spectral Efficiency of Multiple-Antenna Systems

Jiang

Dianati

Imran

et al. 2013

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

Abstract-Motivated by increased interests in energy efficient communication systems, the relation between energy efficiency (EE) and spectral efficiency (SE) for multiple-input multipleoutput (MIMO) systems is investigated in this paper. To provide insight into the design of practical MIMO systems, we adopt a realistic power model, as well as consider both independent Rayleigh fading and semicorrelated fading channels. We derive a novel and closed-form upper bound for the system EE as a function of SE. This upper bound exhibits a great accuracy for a wide range of SE values, and thus can be utilized for explicitly assessing the influence of SE on EE, and analytically addressing the EE optimization problems. Using this tight EE upper bound, our analysis unfolds two EE optimization issues: Given the number of transmit and receive antennas, an optimum value of SE is derived such that the overall EE can be maximized; Given a specific value of SE, the optimal number of antennas is derived for maximizing the system EE.

show abstract

Section: Energy Efficiency Analysis Of Mimo Channelsmentioning

confidence: 99%

Section: A Ee Ub For Iid Mimo Channelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On the Relation Between Energy Efficiency and Spectral Efficiency of Multiple-Antenna Systems

Jiang

Dianati

Imran

et al. 2013

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…Unfortunately, the joint optimization of energy efficiency and spectral efficiency is difficult to achieve as the improvement of one often is at the expense of the other. Therefore, it is important to investigate the different tradeoffs between the two performance indicators to decide upon the minimum energy consumption that is required to achieve the target spectral efficiency [3].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Subcarrier-and-Bit Allocation in Multi-User OFDMA Systems

Haider

Wang

Haas

et al. 2012

2012 IEEE 75th Vehicular Technology Conference (VTC Spring)

Self Cite

View full text Add to dashboard Cite

Abstract-Energy efficiency is becoming increasingly important for wireless communication systems in order to minimize carbon footprint of wireless networks and to increase the battery life of mobile terminals. The spectral-energy efficiency trade-off is of primary significance to determine how much energy per bit is required in a wireless communication system to achieve a specific spectral efficiency. In this paper, we study energyefficient resource allocation scheme for Orthogonal FrequencyDivision Multiple Access (OFDMA) systems with multiple users. The trade-off between spectral and energy efficiencies is analyzed under the constraint of maintaining the fairness among users. We first formulate the energy-efficient optimization problem as an integer fractional programming. We then apply an iterative fractional method to simplify the problem to integer linear programming (ILP) problem. Simulation results demonstrate that the impact of user's quality of service (QoS) is minor on the energy efficiency when a large spectral efficiency is required.

show abstract

“…The EE-SE trade-off in the low SE regime has been studied for single-input single-output [30], [31], MIMO [32], [33], multi-user [34], multi-hop [35], and cooperative communication systems [36]- [39]. Moreover, the trade-off in the high SE regime has been studied for multiaccess [31], [39], [40], MIMO [33], [41], and MIMO broadcast systems [42]. To our best knowledge, the EE-SE trade-off of large scale V-MIMO systems has never been studied.…”

mentioning

confidence: 99%

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

Hong

Yu²,

Wang³

et al. 2013

IEEE J. Select. Areas Commun.

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Spectral-energy efficiency tradeoff in Cognitive Radio networks with peak interference power constraints

Cited by 8 publications

References 20 publications

On the Relation Between Energy Efficiency and Spectral Efficiency of Multiple-Antenna Systems

On the Relation Between Energy Efficiency and Spectral Efficiency of Multiple-Antenna Systems

Energy-Efficient Subcarrier-and-Bit Allocation in Multi-User OFDMA Systems

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

Contact Info

Product

Resources

About