Recent analysis by manufacturers and network operators has shown that current wireless networks are not very energy efficient, particularly the base stations by which terminals access services from the network. In response to this observation the Mobile Virtual Centre of Excellence (VCE) Green Radio project was established in 2009 to establish how significant energy savings may be obtained in future wireless systems. This article discusses the technical background to the project and discusses models of current energy consumption in base station devices. It also describes some of the most promising research directions in reducing the energy consumption of future base stations.

Recently, energy efficiency in wireless networks has become an important objective. Aside from the growing proliferation of smartphones and other high-end devices in conventional human-to-human (H2H) communication, the introduction of machine-to-machine (M2M) communication or machine-type communication into cellular networks is another contributing factor. In this paper, we investigate quality-of-service (QoS)-driven energy-efficient design for the uplink of long term evolution (LTE) networks in M2M/H2H co-existence scenarios. We formulate the resource allocation problem as a maximization of effective capacity-based bits-per-joule capacity under statistical QoS provisioning. The specific constraints of single carrier frequency division multiple access (uplink air interface in LTE networks) pertaining to power and resource block allocation not only complicate the resource allocation problem, but also render the standard Lagrangian duality techniques inapplicable. We overcome the analytical and computational intractability by first transforming the original problem into a mixed integer programming (MIP) problem and then formulating its dual problem using the canonical duality theory. The proposed energy-efficient design is compared with the spectral efficient design along with round robin (RR) and best channel quality indicator (BCQI) algorithms. Numerical results, which are obtained using the invasive weed optimization (IWO) algorithm, show that the proposed energy-efficient uplink design not only outperforms other algorithms in terms of energy efficiency while satisfying the QoS requirements, but also performs closer to the optimal design.

In this paper, we study the effect of channel estimation error at the receiver on the mutual information of a multiple-input-multiple-output (MIMO) channel obeying correlated Rayleigh fading. We assume that perfect knowledge of the channel correlation is available at the receiver and find upper and lower bounds on the mutual information for Gaussian input signals. We prove that for a generic input covariance matrix, the gap between these two bounds at high transmit powers does not exceed a certain value, which depends on the number of nonzero eigenvalues of the receive correlation matrix. We also show that in a system with uncorrelated transmit antennas and correlated receive antennas and with uniform power distribution over the transmit antennas, these bounds are asymptotically tight for a large number of transmit antennas. We show that when the correlation information is available at the transmitter, the transmitting strategy that maximizes the mutual information lower bound is to transmit toward the directions of the eigenvectors of the transmit correlation matrix. We further derive upper and lower bounds on the mutual information of a MIMO multiple-access channel with imperfect channel estimation at the receiver. We also prove that when the input power at each user is uniformly distributed over its transmit antennas, the bounds on the mutual information are asymptotically tight for Gaussian input signals, and this tightness increases when the number of users increases. Numerical simulations are conducted to corroborate theoretical results.

In this paper we develop a framework for resource allocation in a secondary spectrum access scenario, where a group of cognitive radios (CR) access the resources of a primary system. We assume the primary system is a cellular OFDM-based network operating in uplink. We develop an optimum resource allocation strategy, using cooperative game theory, which guarantees the primary's required QoS and allocates an achievable rate at a given bit error rate for the secondary, when possible. The proposed cognitive radio game (CRG) is a network-assisted resource management method, where users (both primary and secondary) inform the primary system's BS of their channel state information and power limitation and the base station calculates the optimum sub-channel and power allocation for all users. Using Game theoretic axiom of fairness, i.e., Nash Bargaining Solutions (NBS), we develop an alternative efficient and fair resource allocation and compare its performance with the proposed CRG method. We use Sequential Quadratic Programming (SQP) to solve the proposed non-linearly constrained CRG optimization problem.

Efficient and fair resource allocation strategies are being extensively studied in current research in order to address the requirements of future wireless applications. A novel resource allocation scheme is developed for orthogonal frequency-division multiplexing (OFDM) networks designed to maximise performance while limiting the received interference at each user. This received interference is in essence used as a fairness metric; moreover, by defining different interference tolerances for different sets of users, the proposed allocation scheme can be exploited in various cognitive radio scenarios. As applied to the scheme, the authors investigate a scenario where two cellular OFDM-based networks operate as primary and secondary systems in the same band, and the secondary system benefits by accessing the unused resources of the primary system if additional capacity is required. The primary system benefits either by charging the secondary system for the use of its resources or by some form of reciprocal arrangement allowing it to use the secondary system's licenced bands in a similar manner, when needed. Numerical results show our interference-limited scheduling approach to achieve excellent levels of efficiency and fairness by allocating resources more intelligently than proportional fair scheduling. A further important contribution is the application of sequential quadratic programming to solve the non-convex optimisation problems which arise in such scenarios.

In this paper, we propose a cognitive cellular system based on DS MC-CDMA to coexist with a number of narrow-band legacy systems in the same frequency range. If the bandwidth and the frequency location of each narrow-band system are known to this cognitive MC-CDMA, it is possible to mitigate their interfering effect in the cognitive receivers by adaptive transmission. We will develop an algorithm for calculating the adaptive transmission parameters and show that it combats interference in the channel effectively.