Binary-exponential sleep mode (BE-SM) operation is an energy-saving solution of mobile stations for best-effort or non-realtime services. In general, there is a trade-off between energy consumption and delay. Especially, in the conventional BE-SM operations, the standard scheme achieves the lower bound of delay, while the threshold scheme achieves the upper bound of delay. Since the threshold scheme yields the highest energy efficiency at the expense of delay, it does not guarantee given quality-of-service (QoS) requirements. From the viewpoint of various QoS requirements, we propose a relaxed QoS (RQ) scheme with relaxed QoS requirements and a stringent QoS (SQ) scheme with stringent QoS requirements in which we have two policies: additional sleep cycles and buffer-threshold. The results show that the proposed RQ scheme has a trade-off between energy efficiency and user satisfaction ratio at low arrival rate, while the proposed SQ scheme is close to the upper bound of energy efficiency while satisfying the stringent QoS requirements.

We propose a new contention resolution scheme designed for large scale autonomous wireless systems and fully distributed D2D (device-to-device) communications networks. The proposed contention resolution scheme is designed for scalability, efficiency, and fairness. Unlike traditional contention resolution schemes, the proposed contention resolution scheme uses idle time of channel as a measure of the channel condition. Idle time of channel is not only a much more reliable and versatile measure of channel condition than the traditional way of collision detection using ACK, it also makes it possible to use the proposed contention resolution scheme in situations where ACK is not expected such as with broadcast and multicast messages or in fully distributed synchronization procedures. The simulation study confirms that the proposed scheme exhibits high degree of scalability, efficiency, and fairness.

A multi-user MIMO (MU-MIMO) system configures orthogonal MIMO channels for active mobile users by use of multiple antennas of the base station (BS). Because different grouping of users can introduce different channel properties in MU-MIMO, user groupinging can minimize BS transmit power in order to satisfy an essential requirement for BS energy savings. In this paper, we discuss how such user groupinging can vary transmit power consumption in a hybrid spatial and time diversity access (SDMA/TDMA) downstream. Then, we proposed an energy efficient user grouping algorithm for applications in MU-MIMO systems which finds a solution close to optimal by swapping users between different groups and comparing the transmit powers. The proposed greedy-swapping algorithm achieves 37% transmit power saving, which is close to the optimal for the exhaustive search, compared to the traditional capacity optimal scheduling algorithm PU2RC with 6% of the computational time for the optimal exhaustive search.

This paper proposes a Markov decision process (MDP) based base station management scheme that dynamically and collectively manages activation of a group of base stations depending on the time-varying traffic demand for power conservation in self-organization networks. Our MDP model is unique in a sense that it accurately captures the dynamics of handover traffic among neighboring cells, and it formulates infeasible actions as constraints in a constrained optimization problem. Simulation results confirm that the proposed scheme can significantly reduce power consumption: 55% of daily power savings, upto 73% of power savings during low traffic periods, and the minimum 23% of power savings even during high traffic periods. Our MDP algorithms find desired optimal policies to deactivate unnecessary base stations without sacrificing network performances.

In order to alleviate a mobile data explosion problem, WiFi offloading has been proposed. The key issue is how many access points (APs) are needed to accommodate a proper number of users per WiFi AP without severe performance degradation. Although WiFi networks can provide higher throughput as more and more APs are deployed, it may not be a reasonable solution if we consider an increase in the corresponding capital and operational expenditure (CAPEX/OPEX). Therefore, it is important to investigate the minimum required number of WiFi APs which achieve a certain level of performance improvement. In this paper, we focus on the minimum required number of WiFi APs for efficient WiFi offloading. We first set the target average per-user throughput when a WiFi network can play a role as an offloading network of a given cellular network. Based on this criterion, we find the minimum required number of WiFi APs in an overlay network through mathematical analysis.

Orthogonal frequency division multiple access (OFDMA) systems, such as IEEE 802.16e/m and 3GPP Long Term Evolution (LTE), require significantly large signaling overhead for delivering small-sized delay-sensitive traffic such as voice over IP (VoIP) service. It may result in a significant decrease in the spectral efficiency. In order to overcome this drawback, recently, a persistent scheduling scheme has been standardized in standard bodies. In order to reduce the signaling overhead, the modulation and coding scheme (MCS) is set to be fixed during a burst period for the persistent scheduling procedure and an incomplete transmission, if it occurs, is recovered by a hybrid automatic repeat request (HARQ) scheme. In this paper, considering the HARQ retransmissions, we propose a rate selection scheme for the persistent scheduling satisfying given quality of service (QoS) requirements. In our proposed rate selection scheme, we consider two important factors which were not considered in previous HARQ-related work: time-correlations of the wireless channel in the HARQ retransmissions and the resource usage of signaling overhead. Numerical results show that the proposed rate selection scheme can efficiently enhance the utilization of radio resources compared to the conventional schemes.

In IEEE 802.16e OFDMA system, the system capacity for accommodating VoIP traffic with small-sized PDUs is severely reduced due to a large amount of signalling overhead. In order to mitigate this problem, the IEEE 802.16 maintenance group has recently proposed a persistent allocation scheme to increase the voice over IP (VoIP) system capacity. However, it is difficult to use the conventional modulation and coding scheme (MCS) selection algorithms, which are based on instantaneous SINR, for the persistent allocation scheme. In this paper, we propose MCS selection algorithms which are effective for using radio resources considering a hybrid ARQ retransmission mechanisms while satisfying given QoS requirements for the persistent allocation scheme. Numerical results show that the proposed algorithms are effective for utilizing radio resources efficiently while satisfying given QoS requirements.

In this paper, we introduce a new modulation scheme called Spiral QAM, which is optimized for phase noise, and thus robust in the presence of phase noise. Symbol mapping rules for 16 and 64 Spiral QAM are also presented. SER and BER performance of 64 Spiral QAM was compared with the conventional 64 QAM to show the superior performance of Spiral QAM in the presence of phase noise.

IEEE 802.16e uses EAP-based authentication and key management for link layer security. Due to the lack of ability to support mobility, however, EAP-based key management becomes a principal impediment to the achievement of an efficient and secure handover in IEEE 802.16e mobile WiMAX networks. In this paper, an overview of the EAP-based handover procedures of the latest IEEE 802.16e standard is given and their security flaws are analyzed. Possible solutions for secure handover in IEEE 802.16e networks are also proposed in this paper. The proposed handover protocol guarantees a backward/forward secrecy while gives little burden over the previous handover protocols.

A new accurate analysis model of the IEEE 802.11 DCF is presented. The analysis model is based on a close observation of the IEEE 802.11 DCF behavior. We observe that an infinite number of probabilities of collision need to be defined to accurately represent the behavior of the IEEE 802.11 DCF. Simulation results are included to verify the analytical results.

EIED backoff algorithm was proposed in Song et al., (2003) to enhance the performance of the IEEE 802.11 DCF. EIED provides significant performance improvement without additional complexity. In this paper, we applied EIED to the periodic ranging process of IEEE 802.16, where BEB was originally used. As a performance metric, the average number of tries per periodic ranging attempt was used. The performance was shown analytically, which was verified by computer simulation. The performance results of EIED in the periodic ranging process of IEEE 802.16 are compared to those of BEB. The performance results show that EIED provides a significant performance gain over BEB. Using EIED, we can achieve comparable performance as BEB with significantly smaller set of ranging CDMA codes.

In the event of PNC failure, the event of PNC leaving a piconet without a proper handover procedure, it is critical to have a scheme that allows one of the PNC capable DEVs to take over the role of PNC to minimize the interruption of services. A new proactive coordinator appropriation (PCA) scheme is proposed to prevent piconets from collapsing in the event of PNC failure. PCA is an efficient and reliable scheme that detects PNC failure in a timely manner, while minimizing the probability of false detection. An analytical comparison of PCA with the existing schemes of similar functionality is provided.

New analytical results are given for the performance of the exponential backoff (EB) algorithm. Most available studies on EB focus on the stability of the algorithm and little attention has been paid to the performance analysis of EB. In this paper, we analyze EB and obtain saturation throughput and medium access delay of a packet for a given number of nodes N. The analysis considers the general case of EB with backoff factor r; binary exponential backoff (BEB) algorithm is the special case with r=2. We also derive the analytical performance of EB with maximum retry limit M (EB-M), a practical version of EB. The accuracy of the analysis is checked against simulation results.

We investigate the inherent scalability problem of ad hoc networks that originated from the nature of multi-hop networks. First, the expected packet traffic at the center of a network is analyzed. The result shows that the expected packet traffic at the center of a network is linearly related with the network size, that is, the expected packet traffic at the center of a network is O(k), where k is the radius of a network. From the result, the upper bound of the diameter of a network D = 2k, that guarantees the network is scalable, is obtained. The upper hound is given by C/r - 1, where C is the channel capacity available to each node and r is the packet arrival rate at each node.

A multisector antenna based access point (AP) network architecture with omni-directional mobile nodes (MNs) is proposed. We investigate the effect of hidden nodes and power control on the system performance, and compare the performance of the proposed network architecture with that of an omni-directional AP/MNs network architecture in terms of throughput, delay, probability of collision, and power consumption per throughput. The data throughput in the multisector antenna based AP network architecture with power control (PC) is approximately 5.65 and 6.59 times higher than for the conventional omni-directional AP network architecture with PC and without PC, respectively, at an aggregate offered load of 1.0 (2.0 Mbps). The peak data throughput of the proposed network architecture with PC is approximately 1.9 (3.8 Mbps) for an aggregate offered load of about 2.1 (4.2 Mbps). Furthermore, the power consumption of MNs per throughput in the proposed network architecture with PC is only 1.02% and 2.25% of those of the omni-directional AP network architecture without PC and with PC, respectively, at an aggregate offered load of 1.0 (2.0 Mbps). The proposed network architecture with PC yields a significant improvement in system throughput and power saving in comparison with the conventional omni-directional AP/MNs network architecture.

New analytic results are given for the stability and performance of the exponential backoff (EB) algorithm. Previous studies on the stability of the (binary) EB have produced contradictory results instead of a consensus: some proved instability, others showed stability under certain conditions. In these studies, simplified and/or modified models of the backoff algorithm were often used to make analysis more tractable. In this paper, care is taken to use a model for backoff that reflects the actual behavior of backoff algorithms. We show that EB is stable under a throughput definition of stability; the throughput of the network converges to a non-zero constant as the offered load N goes to infinity. We also obtain the analytical expressions for the saturation throughput and the medium access delay of a packet for a given number of nodes, N. The analysis considers the general case of EB with backoff factor r, where BEB is the special case with r = 2. The accuracy of the analysis is checked against simulation results.

In this report, wireless application protocol (WAP) traffic is experimentally modeled with wireless markup language (WML ) files collected on legacy WAP servers. This experimental WAP traffic modeling is completed by finding the following values: (i) the average sizes of a WML file (WML deck) and its encoded file; (ii) the distributions of a WML file and WMLC file; (iii) the average number of packets in a WML file; and (iv) the average packet and frame sizes.

The convergence speed of the steepest descent (SD) adaptive algorithm is determined by the eigenvalue spread of the correlation matrix. When the correlation matrix is singular, the algorithm will take a long time to converge. The problem can be regularized by adding a small constant to the diagonal, but this comes at the price of introducing bias. This paper introduces a new adaptive algorithm that uses a family of steepest descent iterations which converge quickly while making the bias arbitrarily small. A numerical example discusses in some detail the operation of the new algorithm.

We investigate a conjecture stated by Coffman, Flatto, and Wright within the context of a stochastic machine minimization problem with a hard deadline. We prove that the conjecture is true.