Mohammad Reza Nakhai

Cognitive Radio game for secondary spectrum access problem

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 primarys 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 systems 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.

Interference-limited resource allocation for cognitive radio in orthogonal frequency-division multiplexing networks

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 systems 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.

Effect of Channel Uncertainty on the Mutual Information of MIMO Fading Channels

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.

Energy-Efficient Uplink Resource Allocation in LTE Networks With M2M/H2H Co-Existence Under Statistical QoS Guarantees

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.

Closed-form capacity expressions of orthogonalized correlated MIMO channels

Space-time block codes are known to orthogonalize the multiple-input multiple-output (MIMO) wireless channel, thus reducing the space-time vector detection to a simpler scalar detection problem. The capacity over orthogonalized ergodic correlated Rayleigh and Ricean flat-fading MIMO channels has so far only been given in integral form. This letter derives a closed form capacity expression over such channels, hence avoiding numerical integrations or Monte Carlo simulations.

Cognitive Radio Transmission Based on Direct Sequence MC-CDMA

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.

Cognitive Radio Game: A Framework for Efficiency, Fairness and QoS Guarantee

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. We develop the optimum resource allocation strategies which guarantee a level of QoS, defined by minimum rate and the target bit error rate (BER), for the primary system. Using the game theoretic axiom of fairness, i.e., Nash bargaining solutions (NBS), we show that by allocating a priority factor to all players an efficient and fair resource allocation can be achieved. We show how the priority factors are assigned in this scheme and outline a method to select the users who are allowed to share a specific sub-channel.

Power Aware Cooperative Routing in Wireless Mesh Networks

In this letter, we focus on transmission side diversity and energy efficient routing in a wireless mesh network of cellular base stations. Our aim is to design a cooperative routing algorithm which takes the active radio electronic power consumption into consideration when constructing the minimum power route from source to destination. We introduce the concept of supernode with improved power efficiency and propose a power aware cooperative routing algorithm. Simulation results show a significant performance improvement over well known power saving routing schemes.

Power-efficient downlink transmission in multicell networks with limited wireless backhaul

This article shows that division of a cell into tiers of smaller cells reduces power consumption. However, using the same frequency-time resources within multiple divided cells causes strong intercell interference. Given this circumstance, three beamforming techniques for multicell networks are presented to tackle the resultant challenging intercell interference environment. The schemes minimize the total transmit power across the coordinating base stations while simultaneously considering the quality of service of each user so that the latter is not unduly affected. Since the beamforming approaches require the circulation of information, an energy-efficient backhaul protocol is demonstrated.

Block QR decomposition and near-optimal ordering in intercell cooperative multiple-input multiple-output-orthogonal frequency division multiplexing

Here, the authors investigate dirty paper coding (DPC) in intercell cooperative multiple-input multiple-output-orthogonal frequency division multiplexing (MIMO-OFDM). Based on the multidimensional structure of intercell cooperative MIMO-OFDM, the DPC model has been modified by introducing a block QR decomposition (BQRD) algorithm which transforms the multiuser channel to a block lower triangular structure. The overall error performance of the proposed BQRD-based DPC is dominated by the error performance of the last precoded user. To improve the last users performance, it was, first, shown that, in a system with U active users, the channel gain matrix remains unchanged for any user acting as the last user among all (U−1)! possible permutations of the other users. Then, a greedy algorithm that directly computes U channel gain matrices and obtains a near-optimal precoding order for the last user is proposed. The proposed greedy ordering scheme reduces the computational complexity by a factor of U!/2 compared with the brute force search. Our simulation results confirm that the performance of the greedy ordering scheme approaches that of the brute force search. Furthermore, the authors show that the proposed BQRD-based DPC expands the multiuser rate region and increases the sum rate over block diagonalisation based zero forcing method.