Underlay Cognitive Radio with Full or Partial Channel Quality Information

Underlay cognitive radios (UCRs) allow a secondary user to enter a primary user's spectrum through intelligent utilization of multiuser channel quality information (CQI) and sharing of codebook. The aim of this work is to study two-user Gaussian UCR systems by assuming the full or partial knowledge of multiuser CQI. Key contribution of this work is motivated by the fact that the full knowledge of multiuser CQI is not always available. We first establish a location-aided UCR model where the secondary user is assumed to have partial CQI about the secondary-transmitter to primary-receiver link as well as full CQI about the other links. Then, new UCR approaches are proposed and carefully analyzed in terms of the secondary user's achievable rate, denoted by $C_2$, the capacity penalty to primary user, denoted by $\Delta C_1$, and capacity outage probability. Numerical examples are provided to visually compare the performance of UCRs with full knowledge of multiuser CQI and the proposed approaches with partial knowledge of multiuser CQI.Comment: 29 Pages, 8 figure

On the energy efficiency-spectral efficiency trade-off over the MIMO rayleigh fading channel

Along with spectral efficiency (SE), energy efficiency (EE) is becoming one of the key performance evaluation criteria for communication system. These two criteria, which are conflicting, can be linked through their trade-off. The EE-SE trade-off for the multi-input multi-output (MIMO) Rayleigh fading channel has been accurately approximated in the past but only in the low-SE regime. In this paper, we propose a novel and more generic closed-form approximation of this trade-off which exhibits a greater accuracy for a wider range of SE values and antenna configurations. Our expression has been here utilized for assessing analytically the EE gain of MIMO over single-input single-output (SISO) system for two different types of power consumption models (PCMs): the theoretical PCM, where only the transmit power is considered as consumed power; and a more realistic PCM accounting for the fixed consumed power and amplifier inefficiency. Our analysis unfolds the large mismatch between theoretical and practical MIMO vs. SISO EE gains; the EE gain increases both with the SE and the number of antennas in theory, which indicates that MIMO is a promising EE enabler; whereas it remains small and decreases with the number of transmit antennas when a realistic PCM is considered

Energy-Efficiency Based Resource Allocation for the Scalar Broadcast Channel

Until recently, link adaptation and resource allocation for communication system relied extensively on the spectral efficiency as an optimization criterion. With the emergence of the energy efficiency (EE) as a key system design criterion, resource allocation based on EE is becoming of great interest. In this paper, we propose an optimal EE-based resource allocation method for the scalar broadcast channel (BC-S). We introduce our EE framework, which includes an EE metric as well as a realistic power consumption model for the base station, and utilize this framework for formulating our EE-based optimization problem subject to a power as well as fairness constraints. We then prove the convexity of this problem and compare our EE-based resource allocation method against two other methods, i.e. one based on sum-rate and one based on fairness optimization. Results indicate that our method provides large EE improvement in comparison with the two other methods by significantly reducing the total consumed power. Moreover, they show that near-optimal EE and average fairness can be simultaneously achieved over the BC-S channel

Maximising Average Energy Efficiency for Two-User AWGN Broadcast Channel

Energy consumption has become an increasingly important aspect of wireless communications, from both an economical and environmental point of view. New enhancements are being placed on mobile networks to reduce the power consumption of both mobile terminals and base stations. This paper studies the achievable rate region of AWGN broadcast channels under Time-division, Frequency-division and Superposition coding, and locates the optimal energyefficient rate-pair according to a comparison metric based on the average energy efficiency of the system. In addition to the transmit power, circuit power and signalling power are also incorporated in the energy efficiency function, with simulation results verifying that the Superposition coding scheme achieves the highest energy efficiency in an ideal, but non-realistic scenario, where the signalling power is zero. With moderate signalling power, the Frequency-division scheme is the most energy-efficient, with Superposition coding and Time-division becoming second and third best. Conversely, when the signalling power is high, both Timedivision and Frequency-division schemes outperform Superposition coding. On the other hand, the Superposition coding scheme also incorporates rate-fairness into the system, which allows both users to transmit whilst maximising the energy efficiency

Energy Efficiency Analysis of Idealized Coordinated Multi-Point Communication System

Coordinated multi-point (CoMP) architecture has proved to be very effective for improving the user fairness and spectral efficiency of cellular communication system, however, its energy efficiency remains to be evaluated. In this paper, CoMP system is idealized as a distributed antenna system by assuming perfect backhauling and cooperative processing. This simplified model allows us to express the capacity of the idealized CoMP system with a simple and accurate closed-form approximation. In addition, a framework for the energy efficiency analysis of CoMP system is introduced, which includes a power consumption model and an energy efficiency metric, i.e. bit-per-joule capacity. This framework along with our closed-form approximation are utilized for assessing both the channel and bit-per-joule capacities of the idealized CoMP system. Results indicate that multi-base-station cooperation can be energy efficient for cell-edge communication and that the backhauling and cooperative processing power should be kept low. Overall, it has been shown that the potential of improvement of CoMP in terms of bit-per-joule capacity is not as high as in terms of channel capacity due to associated energy cost for cooperative processing and backhauling

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

Energy-Efficiency Based Resource Allocation for the Orthogonal Multi-User Channel

Energy efficiency (EE) is emerging as a key design criterion for both power limited, i.e. mobile devices, and power-unlimited, i.e. cellular networks, applications. Whereas, resource allocation is a well-known technique for improving the performance of communication systems. In this paper, we design a simple and optimal EE-based resource allocation method for the orthogonal multi-user channel by adapting the transmit power and rate to the channel condition such that the energy-per-bit consumption is minimized. We present our EE framework, i.e. EE metric and node power consumption model, and utilize it for formulating our EE-based optimization problem with or without constraint. In both cases, we derive explicit formulations of the optimal energy-per-bit consumption as well as optimal power and rate for each user. Our results indicate that EE-based allocation can substantially reduce the consumed power and increase the EE in comparison with spectral efficiency-based allocation

Iterative Slepian-Wolf Decoding and FEC Decoding for Compress-and-Forward Systems

While many studies have concentrated on providing theoretical analysis for the relay assisted compress-and-forward systems little effort has yet been made to the construction and evaluation of a practical system. In this paper a practical CF system incorporating an error-resilient multilevel Slepian-Wolf decoder is introduced and a novel iterative processing structure which allows information exchanging between the Slepian-Wolf decoder and the forward error correction decoder of the main source message is proposed. In addition, a new quantization scheme is incorporated as well to avoid the complexity of the reconstruction of the relay signal at the final decoder of the destination. The results demonstrate that the iterative structure not only reduces the decoding loss of the Slepian-Wolf decoder, it also improves the decoding performance of the main message from the source

Near-Optimal Energy-Efficient Joint Resource Allocation for Multi-Hop MIMO-AF Systems

Energy efficiency (EE) is becoming an important performance indicator for ensuring both the economical and environmental sustainability of the next generation of communication networks. Equally, cooperative communication is an effective way of improving communication system performances. In this paper, we propose a near-optimal energy-efficient joint resource allocation algorithm for multi-hop multiple-input-multiple-output (MIMO) amplify-and-forward (AF) systems. We first show how to simplify the multivariate unconstrained EE-based problem, based on the fact that this problem has a unique optimal solution, and then solve it by means of a low-complexity algorithm. We compare our approach with classic optimization tools in terms of energy efficiency as well as complexity, and results indicate the near-optimality and low-complexity of our approach. As an application, we use our approach to compare the EE of multi-hop MIMO-AF with MIMO systems and our results show that the former outperforms the latter mainly when the direct link quality is poor