Showing papers in "IEEE Transactions on Wireless Communications in 2008"

Sensing-Throughput Tradeoff for Cognitive Radio Networks

Abstract: In a cognitive radio network, the secondary users are allowed to utilize the frequency bands of primary users when these bands are not currently being used. To support this spectrum reuse functionality, the secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance in cognitive radio networks. There are two parameters associated with spectrum sensing: probability of detection and probability of false alarm. The higher the probability of detection, the better the primary users are protected. However, from the secondary users' perspective, the lower the probability of false alarm, the more chances the channel can be reused when it is available, thus the higher the achievable throughput for the secondary network. In this paper, we study the problem of designing the sensing duration to maximize the achievable throughput for the secondary network under the constraint that the primary users are sufficiently protected. We formulate the sensing-throughput tradeoff problem mathematically, and use energy detection sensing scheme to prove that the formulated problem indeed has one optimal sensing time which yields the highest throughput for the secondary network. Cooperative sensing using multiple mini-slots or multiple secondary users are also studied using the methodology proposed in this paper. Computer simulations have shown that for a 6 MHz channel, when the frame duration is 100 ms, and the signal-to-noise ratio of primary user at the secondary receiver is -20 dB, the optimal sensing time achieving the highest throughput while maintaining 90% detection probability is 14.2 ms. This optimal sensing time decreases when distributed spectrum sensing is applied.

Guaranteeing Secrecy using Artificial Noise

Abstract: The broadcast nature of the wireless medium makes the communication over this medium vulnerable to eavesdropping. This paper considers the problem of secret communication between two nodes, over a fading wireless medium, in the presence of a passive eavesdropper. The assumption used is that the transmitter and its helpers (amplifying relays) have more antennas than the eavesdropper. The transmitter ensures secrecy of communication by utilizing some of the available power to produce 'artificial noise', such that only the eavesdropper's channel is degraded. Two scenarios are considered, one where the transmitter has multiple transmit antennas, and the other where amplifying relays simulate the effect of multiple antennas. The channel state information (CSI) is assumed to be publicly known, and hence, the secrecy of communication is independent of the secrecy of CSI.

Soft Combination and Detection for Cooperative Spectrum Sensing in Cognitive Radio Networks

Abstract: In this letter, we consider cooperative spectrum sensing based on energy detection in cognitive radio networks. Soft combination of the observed energies from different cognitive radio users is investigated. Based on the Neyman-Pearson criterion, we obtain an optimal soft combination scheme that maximizes the detection probability for a given false alarm probability. Encouraged by the performance gain of soft combination, we further propose a new softened hard combination scheme with two-bit overhead for each user and achieve a good tradeoff between detection performance and complexity.

Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design

Abstract: This paper studies linear transmit filter design for Weighted Sum-Rate (WSR) maximization in the multiple input multiple output broadcast channel (MIMO-BC). The problem of finding the optimal transmit filter is non-convex and intractable to solve using low complexity methods. Motivated by recent results highlighting the relationship between mutual information and minimum mean square error (MMSE), this paper establishes a relationship between weighted sum-rate and weighted MMSE in the MIMO-BC. The relationship is used to propose two low complexity algorithms for finding a local weighted sum-rate optimum based on alternating optimization. Numerical results studying sum-rate show that the proposed algorithms achieve high performance with few iterations.

Optimal spectrum sensing framework for cognitive radio networks

Abstract: Spectrum sensing is the key enabling technology for cognitive radio networks. The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive radio users without interfering with the operations of the licensed network. Hence, recent research has been focused on the interference avoidance problem. Moreover, current radio frequency (RF) front-ends cannot perform sensing and transmission at the same time, which inevitably decreases their transmission opportunities, leading to the so-called sensing efficiency problem. In this paper, in order to solve both the interference avoidance and the spectrum efficiency problem, an optimal spectrum sensing framework is developed. More specifically, first a theoretical framework is developed to optimize the sensing parameters in such a way as to maximize the sensing efficiency subject to interference avoidance constraints. Second, in order to exploit multiple spectrum bands, spectrum selection and scheduling methods are proposed where the best spectrum bands for sensing are selected to maximize the sensing capacity. Finally, an adaptive and cooperative spectrum sensing method is proposed where the sensing parameters are optimized adaptively to the number of cooperating users. Simulation results show that the proposed sensing framework can achieve maximum sensing efficiency and opportunities in multi-user/multi-spectrum environments, satisfying interference constraints.

Cooperative communications with relay-selection: when to cooperate and whom to cooperate with?

Abstract: In this paper; we propose a new cooperative communication protocol, which achieves higher bandwidth efficiency while guaranteeing the same diversity order as that of the conventional cooperative schemes. The proposed scheme considers relay selection via the available partial channel state information (CSI) at the source and the relays. In particular, we discuss the multi-node decode-and-forward cooperative scenarios, where arbitrary N relays are available. The source determines when it needs to cooperate with one relay only, and which relay to cooperate with in case of cooperation, i.e., "When to cooperate?" and "Whom to cooperate with?". An optimal relay is the one which has the maximum instantaneous scaled harmonic mean functionof its source-relay and relay-destination channel gains. For the symmetric scenario, we derive an approximate expression of the bandwidth efficiency and obtain an upper bound on the symbol error rate (SER) performance. We show that full diversity is guaranteed and that a significant increase of the bandwidth efficiency is achieved. Moreover, we present the tradeoff between the achievable bandwidth efficiency and the corresponding SER. Finally, the obtained analytical results are verified through computer simulations.

Fixing the Complexity of the Sphere Decoder for MIMO Detection

Abstract: A new detection algorithm for uncoded multiple input-multiple output (MIMO) systems based on the complex version of the sphere decoder (SD) is presented in this paper. It performs a fixed number of operations during the detection process, overcoming the two main problems of the SD from an implementation point of view: its variable complexity and its sequential nature. The algorithm combines a novel channel matrix ordering with a search through a very small subset of the complete transmit constellation. A geometrically-based method is used to study the effect the proposed ordering has on the statistics of the MIMO channel. Using those results, a generalization is given for the structure this subset needs to follow in order to achieve quasi-maximum likelihood (ML) performance. Simulation results show that it has only a very small bit error rate (BER) degradation compared to the original SD while being suited for a fully-pipelined hardware implementation due to its low and fixed complexity.

Resource allocation for spectrum underlay in cognitive radio networks

Abstract: A resource allocation framework is presented for spectrum underlay in cognitive wireless networks. We consider both interference constraints for primary users and quality of service (QoS) constraints for secondary users. Specifically, interference from secondary users to primary users is constrained to be below a tolerable limit. Also, signal to interference plus noise ratio (SINR) of each secondary user is maintained higher than a desired level for QoS insurance. We propose admission control algorithms to be used during high network load conditions which are performed jointly with power control so that QoS requirements of all admitted secondary users are satisfied while keeping the interference to primary users below the tolerable limit. If all secondary users can be supported at minimum rates, we allow them to increase their transmission rates and share the spectrum in a fair manner. We formulate the joint power/rate allocation with proportional and max-min fairness criteria as optimization problems. We show how to transform these optimization problems into a convex form so that their globally optimal solutions can be obtained. Numerical results show that the proposed admission control algorithms achieve performance very close to that of the optimal solution. Also, impacts of different system and QoS parameters on the network performance are investigated for the admission control, and rate/power allocation algorithms under different fairness criteria.

Performance Analysis of Slotted Carrier Sense IEEE 802.15.4 Medium Access Layer

Abstract: Advances in low-power and low-cost sensor networks have led to solutions mature enough for use in a broad range of applications varying from health monitoring to building surveillance. The development of those applications has been stimulated by the finalization of the IEEE 802.15.4 standard, which defines the medium access control (MAC) and physical layer for sensor networks. One of the MAC schemes proposed is slotted carrier sense multiple access with collision avoidance (CSMA/CA), and this paper analyzes whether this scheme meets the design constraints of those low-power and low-cost sensor networks. The paper provides a detailed analytical evaluation of its performance in a star topology network, for uplink and acknowledged uplink traffic. Both saturated and unsaturated periodic traffic scenarios are considered. The form of the analysis is similar to that of Bianchi for IEEE 802.11 DCF only in the use of a per user Markov model to capture the state of each user at each moment in time. The key assumptions to enable this important simplification and the coupling of the per user Markov models are however different, as a result of the very different designs of the 802.15.4 and 802.11 carrier sensing mechanisms. The performance predicted by the analytical model is very close to that obtained by simulation. Throughput and energy consumption analysis is then performed by using the model for a range of scenarios. Some design guidelines are derived to set the 802.15.4 parameters as function of the network requirements.

On channel estimation and optimal training design for amplify and forward relay networks

Abstract: In this paper, we provide a complete study on the training based channel estimation issues for relay networks that employ the amplify-and-forward (AF) transmission scheme. We first point out that separately estimating the channel from source to relay and relay to destination suffers from many drawbacks. Then we provide a new estimation scheme that directly estimates the overall channels from the source to the destination. The proposed channel estimation well serves the AF based space time coding (STC) that was recently developed. There exists many differences between the proposed channel estimation and that in the traditional single input single out (SISO) and multiple input single output (MISO) systems. For example, a relay must linearly precode its received training sequence by a sophisticatedly designed matrix in order to minimize the channel estimation error. Besides, each relay node is individually constrained by a different power requirement because of the non-cooperation among all relay nodes. We study both the linear least-square (LS) estimator and the minimum mean-square-error (MMSE) estimator. The corresponding optimal training sequences, as well as the optimal preceding matrices are derived from an efficient convex optimization process.

Selection cooperation in multi-source cooperative networks

Abstract: In a cooperative network with multiple potential relays and multiple simultaneous transmissions, we present selection cooperation wherein each source pairs with a single "best" relay. We analyze the outage probability of a simple and completely distributed selection scheme, requiring some feedback but no centralization, and show that it outperforms distributed space-time codes for networks with more than three relaying nodes. These gains are due to the more efficient use of power in networks using selection. We suggest two other more complex selection schemes based on increasing system intelligence and centralization, and show that for smaller network sizes their performance improvement over the simple selection scheme is not significant.

Optimal and Suboptimal Power Allocation Schemes for OFDM-based Cognitive Radio Systems

Abstract: In this paper, we investigate an optimal power loading algorithm for an OFDM-based cognitive radio (CR) system. The downlink transmission capacity of the CR user is thereby maximized, while the interference introduced to the primary user (PU) remains within a tolerable range. We also propose two suboptimal loading algorithms that are less complex. We also study the effect of a subcarrier nulling mechanism on the performance of the different algorithms under consideration. The performance of the optimal and suboptimal schemes is compared with the performance of the classical power loading algorithms, e.g., water-filling and uniform power but variable rate loading schemes that are used for conventional OFDM-based systems. Presented numerical results show that for a given interference threshold, the proposed optimal scheme allows CR base station (BS) to transmit more power in order to achieve a higher transmission rate than the classical loading algorithms. These results also show that although the proposed suboptimal schemes have certain degradation in performance compared to the optimal scheme, they outperform the classical loading algorithms. We also present numerical results for nulling mechanism. Finally, we investigate the effect of imperfect channel gain information at the transmitter.

Energy-Efficient Cooperative Relaying over Fading Channels with Simple Relay Selection

Abstract: We consider a cooperative wireless network where a set of nodes cooperate to relay in parallel the information from a source to a destination using a decode-and-forward approach. The source broadcasts the data to the relays, some or all of which cooperatively beamform to forward the data to the destination. We generalize the standard approaches for cooperative communications in two key respects: (i) we explicitly model and factor in the cost of acquiring channel state information (CSI), and (ii) we consider more general selection rules for the relays and compute the optimal one among them. In particular, we consider simple relay selection and outage criteria that exploit the inherent diversity of relay networks and satisfy a mandated outage constraint. These criteria include as special cases several relay selection criteria proposed in the literature. We obtain expressions for the total energy consumption for general relay selection and outage criteria for the non-homogeneous case, in which different relay links have different mean channel power gains, and the homogeneous case, in which the relay links statistics are identical. We characterize the structure of the optimal transmission scheme. Numerical results show that the cost of training and feedback of CSI is significant. The optimal strategy is to use a varying subset (and number) of relay nodes to cooperatively beamform at any given time. Depending on the relative location of the relays, the source, and the destination, numerical computations show energy savings of about 16% when an optimal relay selection rule is used. We also study the impact of shadowing correlation on the energy consumption for a cooperative relay network.

Transmission capacity of ad hoc networks with spatial diversity

Abstract: This paper derives the outage probability and transmission capacity of ad hoc wireless networks with nodes employing multiple antenna diversity techniques, for a general class of signal distributions. This analysis allows system performance to be quantified for fading or non-fading environments. The transmission capacity is given for interference-limited uniformly random networks on the entire plane with path loss exponent alpha > 2 in which nodes use: (1) static beamforming through M sectorized antennas, for which the increase in transmission capacity is shown to be thetas(M2) if the antennas are without sidelobes, but less in the event of a nonzero sidelobe level; (2) dynamic eigenbeamforming (maximal ratio transmission/combining), in which the increase is shown to be thetas(M 2/alpha ); (3) various transmit antenna selection and receive antenna selection combining schemes, which give appreciable but rapidly diminishing gains; and (4) orthogonal space-time block coding, for which there is only a small gain due to channel hardening, equivalent to Nakagami-m fading for increasing m. It is concluded that in ad hoc networks, static and dynamic beamforming perform best, selection combining performs well but with rapidly diminishing returns with added antennas, and that space-time block coding offers only marginal gains.

On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance

Abstract: We consider a multi-channel opportunistic communication system where the states of these channels evolve as independent and statistically identical Markov chains (the Gilbert- Elliot channel model). A user chooses one channel to sense and access in each slot and collects a reward determined by the state of the chosen channel. The problem is to design a sensing policy for channel selection to maximize the average reward, which can be formulated as a multi-arm restless bandit process. In this paper, we study the structure, optimality, and performance of the myopic sensing policy. We show that the myopic sensing policy has a simple robust structure that reduces channel selection to a round-robin procedure and obviates the need for knowing the channel transition probabilities. The optimality of this simple policy is established for the two-channel case and conjectured for the general case based on numerical results. The performance of the myopic sensing policy is analyzed, which, based on the optimality of myopic sensing, characterizes the maximum throughput of a multi-channel opportunistic communication system and its scaling behavior with respect to the number of channels. These results apply to cognitive radio networks, opportunistic transmission in fading environments, downlink scheduling in centralized networks, and resource-constrained jamming and anti-jamming.

Using the physical layer for wireless authentication in time-variant channels

Abstract: The wireless medium contains domain-specific information that can be used to complement and enhance traditional security mechanisms. In this paper we propose ways to exploit the spatial variability of the radio channel response in a rich scattering environment, as is typical of indoor environments. Specifically, we describe a physical-layer authentication algorithm that utilizes channel probing and hypothesis testing to determine whether current and prior communication attempts are made by the same transmit terminal. In this way, legitimate users can be reliably authenticated and false users can be reliably detected. We analyze the ability of a receiver to discriminate between transmitters (users) according to their channel frequency responses. This work is based on a generalized channel response with both spatial and temporal variability, and considers correlations among the time, frequency and spatial domains. Simulation results, using the ray-tracing tool WiSE to generate the time-averaged response, verify the efficacy of the approach under realistic channel conditions, as well as its capability to work under unknown channel variations.

Cooperative spectrum sensing with transmit and relay diversity in cognitive radio networks - [transaction letters]

Abstract: In the letter the problem of cooperative spectrum sensing is investigated in cognitive radio (CR) networks over Rayleigh fading channels. By taking into account the error effect on the decision reporting, a general performance analysis of cooperative spectrum sensing is given. The analytical detection results show that the performance of cooperative spectrum sensing is limited by the probability of reporting errors. To deal with this limitation, we propose a transmit diversity based cooperative spectrum sensing method. By regarding multiple CRs as a virtual antenna array, space-time coding and space-frequency coding are applied into CR networks over flat-fading and frequency-selective fading channels, respectively. Moreover, we propose a relay diversity based cooperative spectrum sensing approach to increase the diversity of detection when some CRs are in heavy shadowing. It is then shown that, when combined with algebraic coding, relay diversity can further improve the cooperative spectrum sensing performance.

Competitive spectrum sharing in cognitive radio networks: a dynamic game approach

Abstract: "Cognitive radio" is an emerging technique to improve the utilization of radio frequency spectrum in wireless networks. In this paper, we consider the problem of spectrum sharing among a primary user and multiple secondary users. We formulate this problem as an oligopoly market competition and use a noncooperative game to obtain the spectrum allocation for secondary users. Nash equilibrium is considered as the solution of this game. We first present the formulation of a static game for the case where all secondary users have the current information of the adopted strategies and the payoff of each other. However, this assumption may not be realistic in some cognitive radio systems. Therefore, we consider the case of bounded rationality in which the secondary users gradually and iteratively adjust their strategies based on the observations on their previous strategies. The speed of adjustment of the strategies is controlled by the learning rate. The stability condition of the dynamic behavior for this spectrum sharing scheme is investigated. The numerical results reveal the dynamics of distributed dynamic adaptation of spectrum sharing strategies.

Binary Power Control for Sum Rate Maximization over Multiple Interfering Links

Abstract: We consider allocating the transmit powers for a wireless multi-link (N-link) system, in order to maximize the total system throughput under interference and noise impairments, and short term power constraints. Employing dynamic spectral reuse, we allow for centralized control. In the two-link case, the optimal power allocation then has a remarkably simple nature termed binary power control: depending on the noise and channel gains, assign full power to one link and minimum to the other, or full power on both. Binary power control (BPC) has the advantage of leading towards simpler or even distributed power control algorithms. For N>2 we propose a strategy based on checking the corners of the domain resulting from the power constraints to perform BPC. We identify scenarios in which binary power allocation can be proven optimal also for arbitrary N. Furthermore, in the general setting for N>2, simulations demonstrate that a throughput performance with negligible loss, compared to the best non-binary scheme found by geometric programming, can be obtained by BPC. Finally, to reduce the complexity of optimal binary power allocation for large networks, we provide simple algorithms achieving 99% of the capacity promised by exhaustive binary search.

Performance analysis of single relay selection in rayleigh fading

Abstract: We provide closed-form expressions for the outage and bit error probability (BEP) of uncoded, threshold-based opportunistic relaying (OR) and selection cooperation (SC), at arbitrary signal to noise ratios (SNRs) and number of available relays, assuming decode-and-forward relays and Rayleigh fading channels. Numerical results demonstrate that SC performs slightly better in terms of outage probability; in terms of BEP, both systems may outperform one another, depending on the SNR threshold that determines the set of relays that participate in the forwarding process.

Energy-Efficient Cooperative Communication Based on Power Control and Selective Single-Relay in Wireless Sensor Networks

Abstract: Cooperative communication with single relay selection is a simple but effective communication scheme for energy-constrained networks. In this paper, we propose a novel selective single-relay cooperative scheme, combining selective-relay cooperative communication with physical-layer power control. Based on the MAC-layer RTS-CTS signaling, a set of potential relays compute individually the required transmission power to participate in the cooperative communication, and compete within a window of fixed length. The "best" relay is selected in a distributed fashion with minimum signaling overhead. We derive power-control solutions corresponding to two policies on relay selection: one is to minimize the energy consumption per data packet, and the other is to maximize the network lifetime. Our numerical and simulation results confirm that the proposed scheme achieves significant energy savings and prolongs the network lifetime considerably.

Generalized Design of Multi-User MIMO Precoding Matrices

Abstract: In this paper we introduce a novel linear precoding technique. The approach used for the design of the precoding matrix is general and the resulting algorithm can address several optimization criteria with an arbitrary number of antennas at the user terminals. We have achieved this by designing the precoding matrices in two steps. In the first step we minimize the overlap of the row spaces spanned by the effective channel matrices of different users using a new cost function. In the next step, we optimize the system performance with respect to specific optimization criteria assuming a set of parallel single- user MIMO channels. By combining the closed form solution with Tomlinson-Harashima precoding we reach the maximum sum-rate capacity when the total number of antennas at the user terminals is less or equal to the number of antennas at the base station. By iterating the closed form solution with appropriate power loading we are able to extract the full diversity in the system and reach the maximum sum-rate capacity in case of high multi-user interference. Joint processing over a group of multi-user MIMO channels in different frequency and time slots yields maximum diversity regardless of the level of multi-user interference.

The industrial indoor channel: large-scale and temporal fading at 900, 2400, and 5200 MHz

Abstract: In this paper, large-scale fading and temporal fading characteristics of the industrial radio channel at 900, 2400, and 5200 MHz are determined. In contrast to measurements performed in houses and in office buildings, few attempts have been made until now to model propagation in industrial environments. In this paper, the industrial environment is categorized into different topographies. Industrial topographies are defined separately for large-scale and temporal fading, and their definition is based upon the specific physical characteristics of the local surroundings affecting both types of fading. Large-scale fading is well expressed by a one-slope path-loss model and excellent agreement with a lognormal distribution is obtained. Temporal fading is found to be Ricean and Ricean K-factors have been determined. Ricean K-factors are found to follow a lognormal distribution.

An Analytical Framework for Performance Evaluation of IPv6-Based mobility Management Protocols

Abstract: Mobility management with provision of seamless handover is crucial for an efficient support of global roaming of mobile nodes (MNs) in next-generation wireless networks (NGWN). Mobile IPv6 (MIPv6) and its extensions were proposed by IETF for IP layer mobility management. However, performance of IPv6-based mobility management schemes is highly dependent on traffic characteristics and user mobility models. Consequently, it is important to assess this performance in-depth through those two factors. The performance of IPv6-based mobility management schemes is usually evaluated through simulations. This paper proposes an analytical framework to evaluate the performance of IPv6-based mobility management protocols. This proposal does not aim to advocate which is better but rather to study the effects of various network parameters on the performance of these protocols to enlighten decision-making. The effect of system parameters, such as subnet residence time, packet arrival rate and wireless link delay, is investigated for performance evaluation with respect to various metrics like signaling overhead cost, handoff latency and packet loss. Numerical results show that there is a trade-off between performance metrics and network parameters.

Saturation throughput analysis of IEEE 802.11 in the presence of non ideal transmission channel and capture effects

Abstract: In this paper, we provide a saturation throughput analysis of the IEEE 802.11 protocol at the data link layer by including the impact of both transmission channel and capture effects in Rayleigh fading environment. Impacts of both non-ideal channel and capture effects, specially in an environment of high interference, become important in terms of the actual observed throughput. As far as the 4-way handshaking mechanism is concerned, we extend the multi-dimensional Markovian state transition model characterizing the behavior at the MAC layer by including transmission states that account for packet transmission failures due to errors caused by propagation through the channel. This way, any channel model characterizing the physical transmission medium can be accommodated, including AWGN and fading channels. We also extend the Markov model in order to consider the behavior of the contention window when employing the basic 2-way handshaking mechanism. Under the usual assumptions regarding the traffic generated per node and independence of packet collisions, we solve for the stationary probabilities of the Markov chain and develop expressions for the saturation throughput as a function of the number of terminals, packet sizes, raw channel error rates, capture probability, and other key system parameters. The theoretical derivations are then compared to simulation results confirming the effectiveness of the proposed models.

Joint rate and power allocation for cognitive radios in dynamic spectrum access environment

Abstract: We investigate the dynamic spectrum sharing problem among primary and secondary users in a cognitive radio network. We consider the scenario where primary users exhibit on-off behavior and secondary users are able to dynamically measure/estimate sum interference from primary users at their receiving ends. For such a scenario, we solve the problem of fair spectrum sharing among secondary users subject to their QoS constraints (in terms of minimum SINR and transmission rate) and interference constraints for primary users. Since tracking channel gains instantaneously for dynamic spectrum allocation may be very difficult in practice, we consider the case where only mean channel gains averaged over short-term fading are available. Under such scenarios, we derive outage probabilities for secondary users and interference constraint violation probabilities for primary users. Based on the analysis, we develop a complete framework to perform joint admission control and rate/power allocation for secondary users such that both QoS and interference constraints are only violated within desired limits. Throughput performance of primary and secondary networks is investigated via extensive numerical analysis considering different levels of implementation complexity due to channel estimation.

Novel Automatic Modulation Classification Using Cumulant Features for Communications via Multipath Channels

Abstract: Nowadays, automatic modulation classification (AMC) plays an important role in both cooperative and non-cooperative communication applications. Very often, multipath fading channels result in the severe AMC performance degradation or induce large classification errors. The negative impacts of multipath fading channels on AMC have been discussed in the existing literature but no solution has ever been proposed so far to the best of our knowledge. In this paper, we propose a new robust AMC algorithm, which applies higher-order statistics (HOS) in a generic framework for blind channel estimation and pattern recognition. We also derive the Cramer-Rao lower bound for the fourth-order cumulant estimator when the AMC candidates are BPSK and QPSK over the additive white Gaussian noise channel, and it is a nearly minimum-variance estimator leading to robust AMC features in a wide variety of signal-to-noise ratios. The advantage of our new algorithm is that, by carefully designing the essential features needed for AMC, we do not really have to acquire the complete channel information and therefore it can be feasible without any a priori information in practice. The Monte Carlo simulation results show that our new AMC algorithm can achieve the much better classification accuracy than the existing AMC techniques.

On cognitive radio networks with opportunistic power control strategies in fading channels

Abstract: In this paper, we consider a cognitive radio system in fading wireless channels and propose an opportunistic power control strategy for the cognitive users, which serves as an alternative way to protect the primary user's transmission and to realize spectrum sharing between the primary user and the cognitive users. The key feature of the proposed strategy is that, via opportunistically adapting its transmit power, the cognitive user can maximize its achievable transmission rate without degrading the outage probability of the primary user. If compared with the existing cognitive protocols, which usually try to keep the instantaneous rate of the primary user unchanged, our strategy relieves the cognitive users from the burden of detecting and relaying the message of the primary user and relaxes the system synchronization requirements. The achievable rate of a cognitive user under the proposed power control strategy is analyzed and simulated, taking into account the impact of imperfect channel estimation. A modified power control strategy is also proposed to reduce the sensitivity of our strategy to the estimation errors. Its effectiveness is verified by the simulations.

Performance evaluation of frequency planning schemes in OFDMA-based networks

Abstract: In this paper, we study the performance of frequency allocation schemes in forthcoming OFDMA-based systems. These systems include WiMAX and 3G long term evolution. We first develop an analytical model for the collisions for an arbitrary number of users in the different cells. We then calculate the capacity of the system using a Markov model and taking into account the inter-cell interference and its impact on the adaptive modulation. We apply this model to compare four frequency allocation schemes, namely reuse 1, reuse 3, and static and dynamic mixes of reuse 1 and 3. We also considered a fifth scheme, called partial isolation and proposed for 3G LTE systems, that uses different transmission powers in the different frequency bands, in order to reduce interference at cell edge. Our results show that the partial isolation scheme outperforms all the others, especially in the downlink, as it combines the advantage of the reuse 1 scheme (large overall throughput) with that of the mix of reuses 1 and 3 (good cell-edge performance).

Resource Allocation for Delay Differentiated Traffic in Multiuser OFDM Systems

Abstract: Most existing work on adaptive allocation of sub- carriers and power in multiuser orthogonal frequency division multiplexing (OFDM) systems has focused on homogeneous traffic consisting solely of either delay-constrained data (guaranteed service) or non-delay-constrained data (best-effort service). In this paper, we investigate the resource allocation problem in a heterogeneous multiuser OFDM system with both delay-constrained (DC) and non-delay-constrained (NDC) traffic. The objective is to maximize the sum-rate of all the users with NDC traffic while maintaining guaranteed rates for the users with DC traffic under a total transmit power constraint. Through our analysis we show that the optimal power allocation over subcarriers follows a multi-level water-filling principle; moreover, the valid candidates competing for each subcarrier include only one NDC user but all DC users. By converting this combinatorial problem with exponential complexity into a convex problem or showing that it can be solved in the dual domain, efficient iterative algorithms are proposed to find the optimal solutions. To further reduce the computational cost, a low-complexity suboptimal algorithm is also developed. Numerical studies are conducted to evaluate the performance of the proposed algorithms in terms of service outage probability, achievable transmission rate pairs for DC and NDC traffic, and multiuser diversity.