Interference alignment (IA) is a joint-transmission technique that achieves the capacity of the interference channel for high signal-to-noise ratios (SNRs). However, most prior works on IA are based on the impractical assumption that perfect and global channel-state information(CSI) is available at all transmitters, resulting in overwhelming feedback overhead. To substantially suppress the feedback overhead, this paper proposes an efficient design of the feedback framework for IA in the K-user multiple-input multiple-output (MIMO) interference channel. The proposed feedback topology supports sequential CSI exchange (feedback and feedforward) between transmitters and receivers and reduces the feedback overhead from a cubic function of K to a linear one, compared to conventional feedback approaches. Given the proposed feedback topology, we consider the limited feedback channel from the receivers to corresponding interferers and analyze the effect of quantization error which generates the residual interference. Also, an efficient feedback-bit allocation algorithm that minimizes the upper-bound of sum residual interference is proposed.

In this letter we propose per antenna superposition coding (PASC) by which partial information can be relayed instead of full information, to exploit the higher capacity of source-relay-destination link. Here, the PASC is designed across antennas, producing basic layer and superposed layer for each data stream per antenna. It is shown that an overall data rate of partial information relaying with PASC can be increased beyond that offered by full information relaying by virtue of fast forwarding of partial information over relatively better link.

In this paper, a new subcarrier allocation algorithm is proposed for an uplink multiuser OFDM relay network. To achieve fairness for a source and relay, we consider the minimum rate requirement for a source and the power constraint on a relay, respectively. An optimization problem with fairness constraints is formulated and the subcarrier allocation criterion is obtained by using convex optimization. In the proposed algorithm, if all sources meet the minimum rate requirement, a subcarrier is allocated to a source-relay pair which has the largest instantaneous rate to maximize the sum of the achievable rate of a source. Otherwise, a subcarrier is allocated to a source-relay pair which has the smallest achievable rate to improve fairness for a source. Simulation results show that the proposed algorithm improves fairness and spectral efficiency for a source.

In this paper, we investigate the capacity region of a multiuser shared channel with time-varying transmission power, whose typical examples are the forward packet data channel (F-PDCH) of IS-2000 1xEV-DV system and the high speed downlink shared channel (HS-DSCH) in 3GPP high speed downlink packet access (HSDPA) system. The concavity of the throughput yields the property that additional power contributes more to a weaker user having a lower channel gain than to a stronger user. Noting this property, we consider a power-balanced policy which tries to balance the received SNR of each user by serving a weaker user with higher transmission power. Then, we establish the equivalence of the power-balanced policy and the Pareto optimal policy which yields a throughput vector at the boundary of the capacity region. This enables to characterize the capacity region explicitly, and also renders an easy means to maximize the total throughput while meeting each user's requirement.

In this paper, we introduce a new retransmission and combining scheme named estimation-based retransmission mode selection (E-RMS) that reinforces the error recovery capability of HARQ for MIMO systems in fast fading channels and present a framework for MIMO system equipped with HARQ capability. The E-RMS scheme is designed to select the more desirable retransmission mode between spatial multiplexing (SM) and space time code (STC) based on estimating the error recovery capability of the two retransmission modes. If the SM mode is selected, the E-RMS transmits all the erroneous streams using the SM mode and otherwise it transmits a part of the erroneous streams using the STC mode. For the E-RMS, we present a decision criterion that selects the more desirable retransmission mode using the channel realization of the previous transmission. Numerical results reveal that the proposed E-RMS achieves significant performance gain over the fixed SM or STC retransmission schemes, performing comparable to the optimal mode selection scheme.

In this paper, we present a multi-channel carrier sense multiple access with collision avoidance (CSMA/CA) protocol for orthogonal frequency division multiple access (OFDMA) systems. The CSMA/CA system in conventional single-channel operation has the advantage of not requiring the signaling for bandwidth request and allocation over the scheduled access system but it sacrifices system efficiency significantly. We overcome the system efficiency limitation by exploiting the OFDMA system features that multiple stations can transmit simultaneously on different sub-channels, and the stations can obtain the channel information of all the sub-channels at each time instant. The OFDMA-based multi-channel CSMA/CA protocol is designed to enable the stations to contend with each other for channel access both in time and frequency domains through a two-dimensional backoff scheme. The protocol takes a generalized form of the conventional single-channel CSMA/CA protocol: It allows to segment the channel bandwidth into multiple narrow-band random access channels and adjust the transmission probability according to the multi-channel activity in a flexible manner. For throughput analysis, we devise a multi-channel p-persistent CSMA protocol that can emulate the multi-channel CSMA/CA protocol and then analyze its saturated throughput. The simulation and analysis results reveal that the proposed system performs far better than the single-channel CSMA/CA system while using the same total bandwidth and even close to the scheduled access system. Further, we examine how stringent time synchronization is required among the constituent stations in implementing of the OFDMA-based multi-channel CSMA/CA system.

In this paper, we present a multi-channel carrier sense multiple access with collision avoidance (CSMA/CA) protocol for orthogonal frequency division multiple access (OFDMA) systems. The protocol exploits the OFDMA system features that multiple stations can transmit simultaneously on different subchannels and the stations can obtain the channel information of all the sub-channels at each time instant. It is designed to enable the stations to contend with each other for channel access both in time and frequency domains through a two-dimensional backoff scheme. By adopting this two-dimensional backoff, the protocol takes a generalized form of the conventional single-channel CSMA/CA protocol: It allows to segment the channel bandwidth into multiple narrow-band random access channels and adjust the transmission probability according to the multichannel activity in a flexible manner. The simulation and analysis results reveal that the proposed system performs far better than the single-channel CSMA/CA system while using the same total bandwidth.

In this paper, we discuss how to find the optimal method for efficient integration of multicast and unicast service in wireless OFDM systems. The multicast capacity is limited by the user with the worst channel condition. In order to overcome this limitation, we propose channel structure for the multicast and unicast traffic. The multicast channel first encodes the multicast traffic and then demultiplexes it into the constituent subchannels, and the channel structure increases the multicast channel capacity with the help of the channel coding. Based on the channel structure, we develop the subchannel allocation that maximizes the total unicast throughput while guaranteeing the transmission rate requirement on the multicast traffic for all the multicast users. Since it is too complicated to solve the allocation problem directly, we devise a fitness metric that quantitatively measures how suitable the subchannel is for carrying the multicast traffic and present the fitness-based subchannel allocation (FSA) algorithm. Numerical results reveal that the FSA algorithm achieves almost the same performance as the performance upper bound in terms of average unicast throughput.

In this paper, we discuss how to achieve optimal subcarrier allocation for multicast services in wireless OFDM systems. The multicast capacity is limited by the user with the worst channel condition. To overcome this limitation, we exploit the fine granularity scalability (FGS) video coding which divides multicast data into base layer and enhancement layer data. Then we develop an optimal subcarrier allocation that maximizes the enhancement layer throughput while satisfying the requirement for the base layer by employing linear programming (LP). For a simple subcarrier allocation we present the suitability-based subcarrier allocation (SSA) algorithm which allocates the subcarriers having a higher metric value to the base layer. The SSA algorithm turns out to be equivalent to the optimal solution of LP problem and is easily modifiable for application to practical OFDM systems. In addition, we present the channel condition-based user selection (CCUS) algorithm which selects a proper set of users to serve when the requirement cannot be met. Numerical results reveal that the SSA algorithm achieves the optimal performance in terms of average spectral efficiency and the CCUS algorithm combined with the SSA algorithm significantly improves the performance over the original SSA algorithm.

In this paper, we rigorously investigate the energy minimization problem for wireless packet networks with automatic repeat request (ARQ) capability. We first formulate the problem for the single-hop case under constrained packet delay and reliability and derive the necessary and sufficient condition for the optimal transmission power at each ARQ stage. We formulate a global rule of optimal transmission power control that achieves optimality regardless of the delay and reliability constraints. Then we extend it to encompass the multi-hop case by dividing the overall problem into two subproblems-energy determination for each ARQ stage and energy distribution among the constituent nodes. We show that the optimality condition established for the single-hop case is also applicable to solve the energy determination problem in the multi-hop case, rendering an optimal solution to the energy distribution problem. Numerical examples reveal that a significant amount of energy is saved by adopting the optimal transmission power and the performance gain is strongly correlated with the decreasing property of the frame error rate

In this letter, we investigate the power minimization problem while supporting the required reliability in wireless multi-hop relay networks. The novelty of the formulation is that it assumes a generalized relation between the power consumed in the transmitter and the packet reception rate in the receiver and, in addition, it takes into consideration the error detection capability of each relay node that can prevent unnecessary error propagation. We derive the optimality condition and provide a method that determines the optimal transmission power of each relay node sequentially. Numerical examples reveal that the optimal power allocation renders notable power saving effect while supporting the required level of reliability.

In this paper, we investigate the energy minimization problem for wireless packet networks with automatic repeat request (ARQ) capability. We formulate the problem under constrained packet delay and reliability, and derive a necessary and sufficient condition for optimal transmission power that achieves optimality regardless of the delay and reliability constraints. Numerical examples reveal that a significant amount of energy is saved by adopting the optimal transmission power and the performance gain is strongly correlated with the decreasing property of the frame error rate.

In this paper we investigate adaptive resource allocation schemes in multiuser OFDM systems for fair share of resources and efficient operation. We employ the CDF-based scheduling (CS) algorithm for the subcarrier allocation, taking advantage of its distinctive feature of analyzability and multiuser diversity. Noting that conventional power allocation schemes do not exhibit efficient and fair operations in heterogeneous user channel environment, we present a new algorithm called proportional-fair power allocation (PFPA). This algorithm is designed to allocate transmission power in such a way that the resulting relative throughput-increment is identical for all subcarriers. The PFPA algorithm is shown to be equivalent to the power allocation of the asymptotically optimal algorithm, which exhibits the largest achievable region in the asymptotic case. Numerical results reveal that the combined CS-PFPA algorithm improves the overall system capacity in terms of time-average throughput and provides efficient estimation of user performances. Further, the CS-PFPA algorithm can meet each user's requirements using a minimum amount of resources, so it renders an efficient and fair means for resource allocation in multiuser OFDM systems.

In this paper, we investigate the capacity region of a multiuser shared channel with time-varying transmission power, whose typical example is the forward packet data channel (F-PDCH) of IS-2000 IxEV-DV system. The concavity of the throughput yields the property that additional power contributes more to a weaker user having a lower channel gain than to a stronger user. Noting this property, we consider a power-balanced policy which tries to balance the received SNR of each user by serving a weaker user with higher transmission power. Then, we establish the equivalence of the power-balanced policy and the Pareto optimal policy which yields a throughput vector at the boundary of the capacity region. This enables to characterize the capacity region explicitly, and also renders an easy means to maximize the total throughput while meeting each user's requirement.

In this paper, we present a new wireless scheduling algorithm based on the cumulative distribution function (cdf) and its simple modification that limits the maximum starving time. This cdf-based scheduling (CS) algorithm selects the user for transmission based on the cdf of user rates, in such a way that the user whose rate is high enough, but least probable to become higher, is selected first. We prove that the CS algorithm is equivalent to a scheduling algorithm that regards the user rates as independent and identically distributed, and the average throughput of a user is independent of the probability distribution of other users. So, we can evaluate the exact user throughput only if we know the user's own distribution, which is a distinctive feature of this proposed algorithm. In addition, we try a modification on the CS algorithm to limit the maximum starving time, and prove that the modification does not affect the average interservice time. This CS with starving-time limitation (CS-STL) algorithm turns out to limit the maximum starving time at the cost of a negligible throughput loss.

In this paper, we investigate how to maximize network lifetime, while meeting the constraints on data collecting time, or data convergence latency (DCL), in networks consisting of N energy-constrained sensor nodes and a central base station (BS). Noting the trade-off relation that a data packet delivered to the BS requires less transmission energy through multi-hop relays but more DCL, we first formulate an optimal routing algorithm that maximizes the network lifetime while satisfying the DCL constraint determined by latency-sensitivity of the application or network stability conditions. As this optimal solution is too complex to implement in practice, we modify it to a suboptimal latency-constrained cost minimization (LCCM) algorithm that is close to the optimal algorithm in performance but is; much lighter in complexity. The LCCM algorithm is designed to minimize the total link cost, while satisfying the DCL constraint. Simulation results show that the performance of the proposed LCCM algorithm is slightly marginal to that of the optimal algorithm in terms of the lifetime, in various network environments.

In this paper we investigate adaptive resource allocation schemes in multiuser OFDM systems for fair share of resources and efficient operation. We employ the CDF-based scheduling (CS) algorithm for the subcarrier allocation, taking advantage of its distinctive feature of analyzability and multiuser diversity. Noting that conventional power allocation schemes do not exhibit efficient and fair operations in heterogeneous user channel environments, we present a new algorithm called proportional-fair power allocation (PFPA). This algorithm is designed to allocate transmission power in such a way that the resulting relative throughput-increment is identical for all subcarriers. The PFPA algorithm is shown to be equivalent to the power allocation of the asymptotically optimal algorithm which exhibits the largest achievable region in the asymptotic case. Numerical results reveal that the combined CS-PFPA algorithm improves the overall system capacity in terms of time-average throughput and provides efficient estimation of user performance. Further, the CS-PFPA algorithm can meet each user's requirements using a minimum amount of resources, so it renders an efficient and fair means for resource allocation in multiuser OFDM systems.

We present a new wireless scheduling algorithm based on the cumulative distribution function (cdf) of user transmission rates and also present a simple modification of it to limit the maximum starving time. This cdf-based scheduling (CS) algorithm selects the user for transmission based on the cdf of user rates in such a way that the user whose rate is high enough but least probable to become higher is selected. It turns out that the cdf-based scheduling algorithm is equivalent to a scheduling algorithm that regards the user rates as independent identically distributed (i.i.d.) and the average throughput of a user is independent of other users' probability distribution. A distinctive feature of this proposed algorithm is that the exact user throughput can be evaluated if the user's own distribution is known. The cdf-based scheduling with starving-time limitation (CS-STL) algorithm turns out not to affect the average inter-service time but to limit the maximum starving time at the cost of a negligible throughput loss.