Marwan Hammouda

Effective capacity in cognitive radio broadcast channels

In this paper, we investigate effective capacity by modeling a cognitive radio broadcast channel with one secondary transmitter (ST) and two secondary receivers (SRs) under quality-of-service constraints and interference power limitations. We initially describe three different cooperative channel sensing strategies with different hard-decision combining algorithms at the ST, namely OR, Majority, and AND rules. Since the channel sensing occurs with possible errors, we consider a combined interference power constraint by which the transmission power of the secondary users (SUs) is bounded when the channel is sensed as both busy and idle. Furthermore, regarding the channel sensing decision and its correctness, there exist possibly four different transmission scenarios. We provide the instantaneous ergodic capacities of the channel between the ST and each SR in all of these scenarios. Granting that transmission outage arises when the instantaneous transmission rate is greater than the instantaneous ergodic capacity, we establish two different transmission rate policies for the SUs when the channel is sensed as idle. One of these policies features a greedy approach disregarding a possible transmission outage, and the other favors a precautious manner to prevent this outage. Subsequently, we determine the effective capacity region of this channel model, and we attain the power allocation policies that maximize this region. Finally, we present the numerical results. We first show the superiority of Majority rule when the channel sensing results are good. Then, we illustrate that a greedy transmission rate approach is more beneficial for the SUs under strict interference power constraints, whereas sending with lower rates will be more advantageous under loose interference constraints. Finally, we note that the methodology and the approach we consider in this study can be easily applied into a more general cognitive radio broadcast channel model with more than two SRs.

Effective Capacity in MIMO Channels With Arbitrary Inputs

Recently, communication systems that are both spectrum and energy efficient have attracted significant attention. Different from the existing research, we investigate the throughput and energy efficiency of a general class of multiple-input and multiple-output systems with arbitrary inputs when they are subject to statistical quality-of-service (QoS) constraints, which are imposed as limits on the delay violation and buffer overflow probabilities. We employ the effective capacity as the performance metric, which is the maximum constant data arrival rate at a buffer that can be sustained by the channel service process under specified QoS constraints. We obtain the optimal input covariance matrix that maximizes the effective capacity under a short-term average power constraint. Following that, we perform an asymptotic analysis of the effective capacity in the low signal-to-noise ratio and large-scale antenna regimes. In the low signal-to-noise ratio regime analysis, in order to determine the minimum energy-per-bit and also the slope of the effective capacity versus energy-per-bit curve at the minimum energy-per-bit, we utilize the first and second derivatives of the effective capacity when the signal-to-noise ratio approaches zero. We observe that the minimum energy-per-bit is independent of the input distribution, whereas the slope depends on the input distribution. In the large-scale antenna analysis, we show that the effective capacity approaches the average transmission rate in the channel with the increasing number of transmit and/or receive antennas. Particularly, the gap between the effective capacity and the average transmission rate in the channel, which is caused by the QoS constraints, is minimized with the number of antennas. In addition, we put forward the nonasymptotic backlog and delay violation bounds by utilizing the effective capacity. Finally, we substantiate our analytical results through numerical illustrations.

Performance analysis of energy-detection-based massive SIMO

Recently, communications systems that are both energy efficient and reliable are under investigation. In this paper, we concentrate on an energy-detection-based transmission scheme where a communication scenario between a transmitter with one antenna and a receiver with significantly many antennas is considered. We assume that the receiver initially calculates the average energy across all antennas, and then decodes the transmitted data by exploiting the average energy level. Then, we calculate the average symbol error probability by means of a maximum a-posteriori probability detector at the receiver. Following that, we provide the optimal decision regions. Furthermore, we develop an iterative algorithm that reaches the optimal constellation diagram under a given average transmit power constraint. Through numerical analysis, we explore the system performance.

Resource allocation and interference management in OFDMA-based VLC networks

Resource allocation and interference management are two main issues that need to be carefully addressed in visible light communication (VLC) systems. In this paper, we propose a resource allocation scheme that can also handle the inter-cell interference in a multi-user VLC system that employs orthogonal frequency division multiple access (OFDMA). Particularly, we suggest dividing the cell coverage into two non-overlapping zones and performing a two-step resource allocation process, in which each step corresponds to a different level of allocating resources, i.e., zone and user levels. We initially define both zones in terms of the physical area and the amount of allocated resources and we investigate the impact of illumination requirements on defining both zones. Through simulations, we evaluate the performance of the proposed scheme in terms of the area spectral efficiency and the fairness level between the two zones. We show that both performance measures can be potentially enhanced by carefully setting a certain design parameter that reflects the priority level of the users located in the region around the cell center, denoted as Zone 0, in terms of the achievable rate. We further eventuate the system performance in a realistic transmission scenario using a simulation tool.

Link Selection in Hybrid RF/VLC Systems Under Statistical Queueing Constraints

The co-deployment of radio frequency (RF) and visible light communication (VLC) technologies has been investigated in indoor environments to enhance network performances and to address specific quality-of-service (QoS) constraints. In this paper, we explore the benefits of employing both technologies when the QoS requirements are imposed as limits on the buffer overflow and delay violation probabilities, which are important metrics in designing low latency wireless networks. Particularly, we consider a multi-mechanism scenario that utilizes RF and VLC links for data transmission in an indoor environment, and then propose a link selection process through which the transmitter sends data over the link that sustains the desired QoS guarantees the most. Considering an ON–OFF data source, we employ the maximum average data arrival rate at the transmitter buffer and the non-asymptotic bounds on data buffering delay as the main performance measures. We formulate the performance measures under the assumption that both links are subject to average and peak power constraints. Furthermore, we investigate the performance levels when either one of the two links is used for data transmission, or when both are used simultaneously. Finally, we show the impacts of different physical layer parameters on the system performance through numerical analysis.

QoS analysis of cognitive radios employing HARQ

Recently, the demand for faster and more reliable data transmission has brought up complex communications systems. As a result, it has become more difficult to carry out closed-form solutions that can provide insight about performance levels. In this paper, different from the existing research, we study a cognitive radio system that employs hybrid-automatic-repeat-request (HARQ) protocols under quality-of-service (QoS) constraints. We assume that the secondary users access the spectrum by utilizing a strategy that is a combination of underlay and interweave access techniques. Considering that the secondary users imperfectly perform channel sensing in order to detect the active primary users and that there is a transmission deadline for each data packet at the secondary transmitter buffer, we formulate the state-transition model of the system. Then, we obtain the state-transition probabilities when HARQ-chase combining is adopted. Subsequently, we provide the packet-loss rate in the channel and achieve the effective capacity. Finally, we substantiate our analytical derivations with numerical results.

Design of a cognitive VLC network with illumination and handover requirements

In this paper, we consider a cognitive indoor visible light communications (VLC) system, comprised of multiple access points serving primary and secondary users through the orthogonal frequency division multiple access method. A cognitive lighting cell is divided into two non-overlapping regions that distinguish the primary and secondary users based on the region they are located in. Under the assumption of equal-power allocation among subcarriers, each region is defined in terms of its physical area and the number of allocated subcarriers within that region. In this paper, we provide the lighting cell design with cognitive constraints that guarantee fulfilling certain illumination, user mobility, and handover requirements in each cell. We further argue that, under some conditions, a careful assignment of the subcarriers in each region can mitigate the co-channel interference in the overlapping areas of adjacent cells. Numerical results depict the influence of different system parameters, such as user density, on defining both regions. Finally, a realistic example is implemented to assess the performance of the proposed scheme via Monte Carlo simulations.

Effective Capacity in Broadcast Channels with Arbitrary Inputs

We consider a broadcast scenario where one transmitter communicates with two receivers under quality-of-service constraints. The transmitter initially employs superposition coding strategies with arbitrarily distributed signals and sends data to both receivers. Regarding the channel state conditions, the receivers perform successive interference cancellation to decode their own data. We express the effective capacity region that provides the maximum allowable sustainable data arrival rate region at the transmitter buffer or buffers. Given an average transmission power limit, we provide a two-step approach to obtain the optimal power allocation policies that maximize the effective capacity region. Then, we characterize the optimal decoding regions at the receivers in the space spanned by the channel fading power values. We finally substantiate our results with numerical presentations.