Wessam Ajib

Performance Analysis of Amplify-and-Forward Cooperative Networks with Relay Selection over Rayleigh Fading Channels

A performance analysis for cooperative diversity system with best relay selection over Rayleigh fading channels is presented. We obtain analytical expressions for the probability density function (PDF), cumulative density function (CDF), and the moment generating function (MGF) of end-to-end SNR of the system under study. Using these expressions we derive closed- form expressions for the average symbol error rate (SER), the outage probability and the average end-to-end SNR gain obtained form relay selection. Using numerical simulations and calculation of the mathematical expressions, the performances of different cases are evaluated and compared to show the significant advantages of the relay selection in a cooperative communication.

Performance analysis of cooperative diversity with relay selection over non-identically distributed links

A performance analysis for cooperative diversity systems with best relay selection over Rayleigh fading channels is presented. The authors obtain analytical expressions for the probability density function (PDF), cumulative density function (CDF) and the moment generating function (MGF) of end-to-end signal-to-noise ratio (SNR) of the system under study for independent and non-identically distributed (i.ni.d.) fading links. Using these expressions the authors derive lower bound closed-form expressions for the average symbol error rate (SER), the outage probability, and an upper bound closed-form expression for the average channel capacity. Using numerical evaluation of the mathematical expressions, system performances of different cases are evaluated and compared for both non-identically and identically distributed links showing the impact of the relay selection in cooperative communication systems.

Joint transmit antenna selection and user scheduling for Massive MIMO systems

It is largely accepted that the innovative technology of large-scale multiantenna systems (named Massive multiple input multiple output (MIMO) systems) will very probably be deployed in the fifth generation of mobile cellular networks. In order to render this technology feasible and efficient, many challenges have to be investigated before. In this paper, we consider the problem of antenna selection and user scheduling in Massive MIMO systems. Our objective is to maximize the sum of broadcasting data rates achieved by all the mobile users in one cell served by a massive MIMO transmitter. The optimal solution of this problem can be obtained through a highly complex exhaustive brute force search (BFS) over all possible combinations of antennas and users. This BFS solution cannot be implemented in practice even for small size systems because of its high computational complexity. Therefore, in this paper, we propose an algorithm that efficiently solves the problem of joint antenna selection and user scheduling. The proposed algorithm aims to maximize the achievable sum-rate and to benefit from both the spatial selectivity gain and multi-user diversity gain offered by the antenna selection and user scheduling, respectively. Compared with the optimal solution obtained by the highly complex BFS, the conducted performance evaluation and complexity analysis show that the proposed algorithm is able to achieve near-optimal performance with low computational complexity.

Packet Scheduling and Fairness for Multiuser MIMO Systems

This paper investigates the network resource allocation in multiuser downlink wireless systems where the base station and the mobile stations are equipped with multiple antennas to provide fair and efficient transmission services to the mobile users. We focus on packet scheduling, given that it has a significant impact on the overall performance of a multiple-input-multiple-output (MIMO) system. Most previous schedulers designed at the packet level do not take into account the traffic characteristics (different packet lengths and the arrival process parameters); consequently, they fall short of simultaneously providing fairness and a low average packet transmission delay. We are making use of a flexible packet transmission algorithm at the medium access control (MAC) layer to develop and propose a novel scheduler, which is referred to as MIMO packet-based proportional fairness (MP-PF). The new scheduler is designed with the goal of providing high performance in terms of a low average packet transmission delay and time and service fairness among the users based on the concept of proportional fairness. The scheduler also conserves work and takes into consideration the packet length, the user queue length, the user transmission rate (related to its channel quality), and the service guarantees for heterogeneous users. The well-known ideal service fair scheduler called max-min can also significantly be improved using our framework by taking into consideration the traffic characteristics. We also provide an analysis for the fairness of the new scheduler in terms of time and service allocation, which is the key contribution of this paper. Simulations that consider the traffic characteristics and the mobility of users show the relatively low average packet transmission delay and demonstrate the time and service fairness capabilities of MP-PF, compared with other well-known MIMO schedulers.

Performance Analysis of Scheduling Schemes for Rate-Adaptive MIMO OSFBC-OFDM Systems

Dynamic channel-aware user-selection and resource-allocation schemes are attractive for providing high system performance for multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. In this paper, we investigate the combination of different techniques, resulting in user scheduling schemes for multiuser MIMO-OFDM systems employing orthogonal space-frequency block coding (OSFBC) over multipath frequency-selective fading channels. Our contribution is a performance analysis framework that evaluates the advantages of employing user scheduling in MIMO-OFDM systems employing OSFBC in conjunction with adaptive modulation schemes. We derive analytical expressions for the average spectral efficiency (ASE), the average bit error rate (BER), the outage probability, and the average channel capacity for different scheduling and adaptive modulation schemes. Discrete-rate and continuous-rate adaptive modulation schemes are employed to increase the spectral efficiency of the system. We assume a signal-to-noise-ratio (SNR)-based user-selection scheme and the well-known proportional fair scheduling (PFS) scheme. Both full- and limited-feedback channel information scenarios are considered. Using the results obtained from both mathematical expressions and numerical simulations, we compare the presented schemes and show their significant advantages. Finally, the impact of spatial correlation on the performance of the system under study is analyzed and evaluated.

A Novel Relay-Aided Transmission Scheme in Cognitive Radio Networks

In underlay cognitive radio networks, unlicensed secondary users are allowed to share the spectrum with licensed primary users when the interference induced on the primary transmission is limited. In this paper, we propose a new cooperative transmission scheme for cognitive radio networks where a relay node is able to help both the primary and secondary transmissions. We derive exact closed-form and upper bound expressions of the conditional primary and secondary outage probabilities over Rayleigh fading channels. Furthermore, we proposed a simple power allocation algorithm. Finally, using numerical evaluation and simulation results we show the potential of our cooperative transmission scheme in improving the secondary outage probability without harming the primary one.

Downlink Scheduling and Resource Allocation for Cognitive Radio MIMO Networks

Cognitive radio is regarded as the ideal candidate for enhancing the efficiency of spectrum usage for next-generation wireless systems. In fact, this emerging technology allows unlicensed cognitive users to transmit over frequency bands that are initially owned by license holders through the use of dynamic spectrum sharing. In this paper, we propose a novel algorithm that efficiently solves the problem of spectrum sharing and user scheduling in a cognitive downlink multi-input-multi-output system (MIMO). We study the scenario where primary receivers do not allow any interference from a multiantenna cognitive base station, which serves cognitive users. Using graph theory, we model, formulate, and develop an algorithm that finds near-optimal spectrum sharing with the objective of approaching the maximum achievable secondary sum rate. Since the formulated graph-coloring problem is shown to be NP-hard, we design a low-complexity greedy algorithm. Following, we add the well-known proportional fairness to the proposed algorithm to ensure time-based fairness and to efficiently resolve the fairness/sum rate tradeoff. The problem is also formulated as a binary integer programming problem to find the optimal coloring solution. Computer simulations show that the proposed algorithm is able to achieve near-optimal performances with low computational complexity.

An on-demand routing protocol for multi-hop multi-radio multi-channel cognitive radio networks

Cognitive radio networks are composed of spectrum-agile devices capable of changing their configurations and transmission parameters on the fly based on their spectral environment. This capability opens up the possibility of designing flexible and dynamic spectrum access strategies with the purpose of opportunistically reusing portions of the spectrum temporarily vacated by licensed primary users. However, this flexibility in the spectrum access brings a new complexity in the design of communication protocols at different layers. In this paper, we consider the problem of routing in multi-hop cognitive radio networks. We propose a multi-radio multi-channel on-demand solution that is able to effectively manage the transmission activities of cognitive and primary users. The routing metric should be carefully developed in order to provide a tradeoff between the channel diversity of the routing path and the end-to-end delay. Through simulations, we highlight the performance of our proposed solution and compare it to multi-radio multichannel on-demand distance vector protocol.

Efficient Scheduling Algorithms for Multiantenna CDMA Systems

In multiple-input-multiple-output (MIMO) multiuser systems, simultaneously serving multiple users achieves high data rates. However, high-performance transmit beamforming requires an adequately designed user-selection scheme. Optimal scheduling can be only obtained through a high computationally complex exhaustive search, and hence, low-complexity heuristic algorithms are required. In addition, employing a multiple-access scheme such as code division (CDMA) largely increases the complexity of optimal scheduling, and it becomes unemployable even for a moderate number of users and antennas. In this context, this paper proposes three heuristic scheduling algorithms for MIMO CDMA systems using zero-forcing beamforming (ZFBF). We use a graph-theoretical approach to model the system as a weighted undirected graph. The problem of user selection is then formulated as a graph coloring problem, namely, the maximum weight N-colorable subgraph problem. Then, we design two heuristics to solve this graph problem. The first algorithm is a low-complexity greedy algorithm. The second algorithm is based on a tabu search approach to resolve efficiently the complexity/performance tradeoff. Numerical and simulation results show the sub-optimal performances and robustness of the proposed low-complexity algorithms.

Overlay cognitive radio systems with adaptive two-way relaying

In this paper, we propose a spectrum sharing mechanism with a two-phase two-way relaying protocol for an overlay cognitive network. The system comprises two primary users (PUs) and two secondary users (SUs). One of the SUs acts as a relay for the PUs and gains spectrum sharing as long as he respects outage probability constraints of the primary system. Moreover, we consider that the relaying node performs an optimal power allocation scheme that minimizes the outage performance of the secondary receiver. Closed form expressions for the outage probability are derived for the cases of Decode-and-Forward (DF), Amplify-and-Forward (AF), and adaptive relaying. Numerical simulations are presented to illustrate and compare the obtained results.