In this article, we investigate energy efficient power control for the uplink of an OFDMA single-cell communication system. The user equipments decide freely their power level on the available subcarriers of the system in order to maximize their EE (Energy Efficiency) while respecting minimum normalized rate requirements. We use the non-cooperative Game theory to demonstrate that users will end by learning the equilibrium. The solution of the Game is given as a water-filling like power allocation. Furthermore, we implement a distributed power allocation scheme using two ways: a) Existing Algorithm: power allocation is done by using Fractional Programing techniques b) Proposed Algorithm: power allocation is done by using a closed form expression. Simulations show that even though the proposed algorithm has less EE than the reference algorithm, it performs better in terms of SE (Spectral Efficiency).

Cooperative Cognitive Radio Networks (CCRN) is a promising concept recently studied to enhance cellular networks. The basic idea is that a primary user (PU) transmits his traffic assisted by some selected secondary users (SUs), which transmit also their own traffics using the same channel. The existing works in the literature propose the use of the same channel by applying a time division approach, where a time slot is dedicated to secondary traffic transmission, which degrads system performance. To overcome this problem, the use of multiple antennas enables simultaneous primary and secondary transmissions. Furthermore, the integration of beam-forming techniques removes the interference generated by this simultaneous transmissions. However, for almost systems proposed so far, only the PU and one SU can transmit simultaneously. In this paper, we propose a new scheme of CCRN where SUs communicate with a fusion center (FC) over a TV White Space (TVWS) band and perform a modulation matrix that allows simultaneous transmissions of the PU and all SUs with no interferences. Finally, we prove by theoretical studies and simulations that the suggested model improves significantly the rate of secondary users yet retaining good performances for the primary link.

Sensing with equal gain combining (SEGC), a novel cooperative spectrum sensing technique for cognitive radio networks, is proposed. Cognitive radios simultaneously transmit their sensing results to the fusion center (FC) over multipath fading reporting channels. The cognitive radios estimate the phases of the reporting channels and use those estimates for coherent combining of the sensing results at the FC. A global decision is made at the FC by comparing the received signal with a threshold. We obtain the global detection probabilities and secondary throughput exactly through a moment generating function approach. We verify our solution via system simulation and demonstrate that the Chernoff bound and central limit theory approximation are not tight. The cases of hard sensing and soft sensing are considered and we provide examples in which hard sensing is advantageous to soft sensing. We contrast the performance of SEGC with maximum ratio combining of the sensors' results and provide examples where the former is superior. Furthermore, we evaluate the performance of SEGC against existing orthogonal reporting techniques such as time division multiple access (TDMA). SEGC performance always dominates that of TDMA in terms of secondary throughput. We also study the impact of phase and synchronization errors and demonstrate the robustness of the SEGC technique against such imperfections.

This paper presents an optimal adaptive modulation (AM) algorithm designed using a cross-layer approach which combines truncated automatic repeat request (ARQ) protocol and packet combining. Transmissions are performed over multiple-input multiple-output (MIMO) Nakagami fading channels, and retransmitted packets are not necessarily modulated using the same modulation format as in the initial transmission. Compared to traditional approach, cross-layer design based on the coupling across the physical and link layers, has proven to yield better performance in wireless communications. However, there is a lack for the performance analysis and evaluation of such design when the ARQ protocol is used in conjunction with packet combining. Indeed, previous works addressed the link layer performance of AM with truncated ARQ but without packet combining. In addition, previously proposed AM algorithms are not optimal and can provide poor performance when packet combining is implemented. Herein, we first show that the packet loss rate (PLR) resulting from the combining of packets modulated with different constellations can be well approximated by an exponential function. This model is then used in the design of an optimal AM algorithm for systems employing packet combining, truncated ARQ and MIMO antenna configurations, considering transmission over Nakagami fading channels. Numerical results are provided for operation with or without packet combining, and show the enhanced performance and efficiency of the proposed algorithm in comparison with existing ones.

We analyze the bit error rate (BER) performance of M-ary quadrature amplitude modulation (M-QAM) when using space-time block coding (STBC) along with packet combining triggered by automatic repeat request (ARQ) retransmission over multiple-input multiple-output (MIMO) fading channels. Specifically, adopting a log-likelihood ratio (LLR) based approach and considering the 16-QAM case of study, we provide an exact formulation for the aggregate LLR distribution in the case the STBC codeword can be transmitted twice, and derive the resulting BER. For higher number of retransmissions, an approximation of the error function is used to derive the LLR distributions and the system's ensuing BER. Considering different values of combined transmissions and M-QAM with possible constellation rearrangement (CoRe), validation of the proposed BER analytical model through simulations and assessment of the advantages of packet combining are provided for transmissions over additive white Gaussian noise (AWGN) channel and orthogonalized MIMO Rayleigh fading channels with different STBC mappings.

In this paper, we consider the scheduling problem in multiple-input multiple-output (MIMO) wireless networks. The main important characteristic of an optimal scheduler is to maximize throughput while servicing users in a fair manner. Herein, we formulate MIMO scheduling as a generalized assignment problem (GAP) and propose a general solution for the GAP, namely, a cross-layer MIMO scheduler (CMS), which uses a novel adaptive proportional fairness (APF) mapping approach in conjunction with a new fast transmit antenna selection (FTAS) technique, to determine the set of users to transmit to and the antenna over which the data associated to each user should be transmitted. The proposed scheduler is applied for packet transmission in high-speed downlink packet access (HSDPA), taking advantage of the use of adaptive modulation and coding while coping with the constraints on the maximum number of simultaneous codes a user equipment can support, the limited uplink signalling, and the absence of fast power control. Numerical results show that the proposed CMS provides up to 70% increase in total throughput compared to other scheduling schemes

Adopting a log-likelihood ratio (LLR) based approach, we analyze the bit error rate (BER) performance of orthogonal space-time block coding (STBC) using M-ary quadrature amplitude modulation (M-QAM) along with packet combining triggered by automatic repeat request (ARQ) retransmission over multiple-input multiple-output (MIMO) Rayleigh fading channels. Specifically, considering the 16-QAM case of study, we provide an exact formula for the aggregate LLR distribution in the case the STBC codeword can be transmitted twice, and derive an exact expression for the BER. For higher number of retransmissions, an approximation of the error function, erf(.), is used to derive the LLR distributions and the system's ensuing BER. The proposed BER analytical model is validated through simulations considering transmission over additive white Gaussian noise (AWGN) and MIMO Rayleigh fading channels, for different STBC mappings, different values of combined transmissions, and possible constellation rearrangement (CoRe).

In this paper we consider the problem of maximizing the multi-user capacity of Gaussian multiple-input multiple-output (MIMO) broadcast channels (BC). This problem consists in finding the optimal users' covariance matrices that maximize the multiuser capacity. These covariances represent, in the same time, the selection of users to transmit to, and their corresponding allocated power. To deal with this problem, many papers use iterative algorithms to provide the optimal solution. However, when the number of active users is high, these algorithms introduce a high order of complexity and suffer from memory drawback. Herein, we show that in a multi-user multi-antenna system, there exists a subset of active users that achieves a capacity close to the maximum, and that such iterative algorithms can be utilized considering a group of users instead of all active users. In addition, we present a new algorithm which makes a suboptimal selection of such group, referred to as the Best Group (BG). The proposed algorithm can be used jointly with any optimal power allocation algorithm in order to provide the covariances which maximize the multiuser capacity. Numerical results are provided and show that the BG selection is at least 5 times faster than other algorithms with a negligible reduction in the BC capacity.

This paper formulates the scheduling problem in MIMO networks as a generalized assignment problem (GAP), and advances a new cross-layer design for the scheduling of users and the assignment of their corresponding data to the available transmit antennas. The proposed scheduling and antenna sharing method, referred to as fast transmit antenna selection (FTAS), uses adaptive proportional fairness (APF) mapping as a means to determine the user-antenna assignment that maximizes the network performance both in terms of throughput and fairness. The proposed scheduler is applied in a high speed downlink packet access (HSDPA) network, taking advantage of an inherent HSDPA characteristic, namely, the use of adaptive modulation and coding, while coping with the imposed maximum number of simultaneously supported codes and the absence of fast power control. Numerical results show that our scheduler provides up to 70% increase in total throughput compared to other scheduling schemes applied to HSDPA

This paper considers packet scheduling in high speed downlink packet access (HSDPA) networks. One of the main features of HSDPA is the capability of tracking fast channel variations and the use of a large set of discrete rate values, which should be used to conduct fast scheduling of packets while ensuring fairness between users. We consider the operating environment where the scheduling is performed in heterogeneous channels. In this case, proportional fairness (PF) scheduling fails to achieve the goal of providing fair throughput to the users. We propose, in this paper, an approach that resolves this shortcoming. The proposed scheduling algorithm, called adaptive proportional fairness (APF) is shown to ensure proportional fairness even under different QoS requirements for users experiencing different channel conditions. Taking into consideration the system's constraints on the available rates, simulation results and comparisons show the high efficiency of our approach compared to PF scheduling.

Satellites are expected to have an important role in providing the Internet protocol (IP) multicast service to complementing next-generation terrestrial networks. In this paper, we focus on the deployment of IP multicast over the next generation of digital video broadcasting-based geosynchronous earth orbit satellites supporting multiple spot beams and on-board switching technologies. We propose a new encapsulation scheme optimized for IP multicast, which has two distinct modes enabling two alternative on-board switching approaches: the self-switching and the label-switching. We also detail a set of mechanisms and protocols for ground stations, as well as for the on-board processor to allow an efficient multicast forwarding in this type of environment, while reducing the load of control and data messages in the satellite segment, and building efficient multicast delivery trees reaching only the spot beams containing at least one member of the corresponding multicast session. To integrate satellite links in the terrestrial Internet, we present satellite multicast adaptation protocol (SMAP), a protocol which is implemented in satellite stations to process incoming protocol independent multicast-sparse mode (PIM-SM) messages sent by terrestrial nodes to the satellite system. SMAP helps to update the tables required for the mapping between IP packets and MPEG-2 data segments, their switching on board the satellite, and their filtering at the satellite receivers.