Improving Energy Efficiency Through Multimode Transmission in the Downlink MIMO Systems

Adaptively adjusting system parameters including bandwidth, transmit power and mode to maximize the "Bits per-Joule" energy efficiency (BPJ-EE) in the downlink MIMO systems with imperfect channel state information at the transmitter (CSIT) is considered in this paper. By mode we refer to choice of transmission schemes i.e. singular value decomposition (SVD) or block diagonalization (BD), active transmit/receive antenna number and active user number. We derive optimal bandwidth and transmit power for each dedicated mode at first. During the derivation, accurate capacity estimation strategies are proposed to cope with the imperfect CSIT caused capacity prediction problem. Then, an ergodic capacity based mode switching strategy is proposed to further improve the BPJ-EE, which provides insights on the preferred mode under given scenarios. Mode switching compromises different power parts, exploits the tradeoff between the multiplexing gain and the imperfect CSIT caused inter-user interference, improves the BPJ-EE significantly.Comment: 19 pages, 10 figures, EURASIP Journal on Wireless Communications and Networking; EURASIP Journal on Wireless Communications and Networking (2011) 2011:20

Energy-efficient power allocation for point-to-point MIMO systems over the rayleigh fading channel

It is well-established that transmitting at full power is the most spectral-efficient power allocation strategy for point-to-point (P2P) multi-input multi-output (MIMO) systems, however, can this strategy be energy efficient as well? In this letter, we address the most energy-efficient power allocation policy for symmetric P2P MIMO systems by accurately approximating in closed-form their optimal transmit power when a realistic MIMO power consumption model is considered. In most cases, being energy efficient implies a reduction in transmit and overall consumed powers at the expense of a lower spectral efficiency

Massive MIMO Systems with Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits

The use of large-scale antenna arrays can bring substantial improvements in energy and/or spectral efficiency to wireless systems due to the greatly improved spatial resolution and array gain. Recent works in the field of massive multiple-input multiple-output (MIMO) show that the user channels decorrelate when the number of antennas at the base stations (BSs) increases, thus strong signal gains are achievable with little inter-user interference. Since these results rely on asymptotics, it is important to investigate whether the conventional system models are reasonable in this asymptotic regime. This paper considers a new system model that incorporates general transceiver hardware impairments at both the BSs (equipped with large antenna arrays) and the single-antenna user equipments (UEs). As opposed to the conventional case of ideal hardware, we show that hardware impairments create finite ceilings on the channel estimation accuracy and on the downlink/uplink capacity of each UE. Surprisingly, the capacity is mainly limited by the hardware at the UE, while the impact of impairments in the large-scale arrays vanishes asymptotically and inter-user interference (in particular, pilot contamination) becomes negligible. Furthermore, we prove that the huge degrees of freedom offered by massive MIMO can be used to reduce the transmit power and/or to tolerate larger hardware impairments, which allows for the use of inexpensive and energy-efficient antenna elements.Comment: To appear in IEEE Transactions on Information Theory, 28 pages, 15 figures. The results can be reproduced using the following Matlab code: https://github.com/emilbjornson/massive-MIMO-hardware-impairment

Delay aware optimal resource allocation in MU MIMO-OFDM using enhanced spider monkey optimization

In multiple users MIMO- OFDM system allocates the available resources to the optimal users is a difficult task. Hence the scheduling and resource allocation become the major problem in the wireless network mainly in case of multiple input and multiple output method that has to be made efficient. There is various method introduced to give an optimal solution to the problem yet it has many drawbacks. So we propose this paper to provide an efficient solution for resource allocation in terms of delay and also added some more features such as high throughout, energy efficient and fairness. To make optimal resource allocation we introduce optimization algorithm named spider monkey with an enhancement which provides the efficient solution. In this optimization process includes the scheduling and resource allocation, the SNR values, channel state information (CSI) from the base station. To make more efficient finally we perform enhanced spider - monkey algorithm hence the resource allocation is performed based on QoS requirements. Thus the simulation results in our paper show high efficiency when compared with other schedulers and techniques