Cognitive Radio: An Information-Theoretic Perspective

In this paper, we consider a communication scenario in which the primary and the cognitive radios wish to communicate to different receivers, subject to mutual interference. In the model that we use, the cognitive radio has noncausal knowledge of the primary radio's codeword. We characterize the largest rate at which the cognitive radio can reliably communicate under the constraint that 1) no rate degradation is created for the primary user, and 2) the primary receiver uses a single-user decoder just as it would in the absence of the cognitive radio. The result holds in a “low-interference” regime in which the cognitive radio is closer to its receiver than to the primary receiver. In this regime, our results are subsumed by the results derived in a concurrent and independent work (Wu , 2007). We also demonstrate that, in a “high-interference” regime, multiuser decoding at the primary receiver is optimal from the standpoint of maximal jointly achievable rates for the primary and cognitive users.      

Outage capacities and optimal power allocation for fading multiple-access channels

We derive the outage capacity region of an M-user fading multiple-access channel (MAC) under the assumption that both the transmitters and the receiver have perfect channel side information (CSI). The outage capacity region is implicitly obtained by deriving the outage probability region for a given rate vector. Given a required rate and average power constraint for each user, we find a successive decoding strategy and a power allocation policy that achieves points on the boundary of the outage probability region. We discuss the scenario where an outage must be declared simultaneously for all users (common outage) and when outages can be declared individually (individual outage) for each user.     

Optimal Successive Group Decoders for MIMO Multiple-Access Channels

We consider a slow-fading narrowband multiple-input multiple-output (MIMO) multiple-access channel (MAC) in which multiple users, each equipped with multiple transmit antennas, communicate to a receiver equipped with multiple receive antennas. The users are unaware of the channel state information (CSI) whereas the receiver has perfect CSI and employs a successive group decoder (SGD). We obtain achievable outage probabilities for the case where an outage must be declared simultaneously for all users (common outage) as well as the case where outages can be declared individually for each user (individual outage). We then derive the optimum successive group decoder (OSGD) that simultaneously minimizes the common outage probability and the individual outage probability of each user, over all SGDs of permissible decoding complexity. For each channel realization, the OSGD is also shown to maximize the error exponent of the decodable set of users. An adaptive SGD is derived which not only retains the outage optimality of the OSGD but also minimizes the expected decoding complexity. Asymptotically tight (in the limit of high signal-to-noise ratio (SNR)) affine approximations are then obtained for the weighted sum common and individual outage capacities and the symmetric outage capacitiy yielded by the OSGD. Limiting expressions for the relevant capacities as the number of users and the number of receive antennas approach infinity are also obtained and it is shown that the OSGD yields symmetric capacity gains commensurate with the decoding complexity allowed. Simulation results with practical low-density parity-check (LDPC) outer codes show that the OSGD offers significantly improved performance at low decoding complexity.      

Antenna and User Subset Selection in Downlink Multiuser Orthogonal Space-Division Multiplexing

Block diagonalization (BD) and successive optimization (SO) are two suboptimal but more practical (compared to dirty paper coding (DPC)) orthogonal linear precoding techniques for the downlink of multiuser MIMO systems. Since the numbers of users supported by BD or SO for a given number of transmit antennas are limited, BD or SO should be combined with scheduling so that a subset of users is selected at a given time slot while meeting the dimensionality requirements of these techniques. On the other hand, receive antenna selection (RAS) is a promising hardware complexity reduction technique. In this paper, we consider user scheduling in conjunction with receive antenna selection. Since exhaustive search is computationally prohibitive, we propose simplified and suboptimal user scheduling algorithms for both BD and SO. For BD, we propose capacity and Frobenius-norm based suboptimal algorithms with the objective of sum rate maximization. Starting from an empty set, each step of proposed algorithms adds the best user from the set of users not selected yet until the desired number of users have been selected. Proposed receive antenna selection works in conjunction with user scheduling to further enhance the sum rate of BD. For SO, a Frobenius-norm based low complexity algorithm is proposed, which maximizes the ratio of the squared Frobenius norm of the equivalent channel (projected to the joint null space of the previously selected users) to the sum of the squared Frobenius norms of the previously selected users’ preprocessed channels. Simulation results demonstrate that the proposed algorithms achieve sum rates close to exhaustive search algorithms with much reduced complexity. We also show that in addition to reduced hardware complexity at the receiver, antenna selection enhances multiuser diversity gain that is achieved with user scheduling.     

非理想SIC下SWIPT-CR-NOMA网络中断性能分析

针对采用无线携能通信的多中继底层协作认知非正交多址接入网络,提出一种两阶段中继选择策略。认知中继执行功率划分的无线携能通信协议为次级用户提供解码转发服务,其能量开销源于所采集到的能量。考虑了实际的非正交多址接入网络中,中继节点与次级用户均无法完全消除多址干扰,即无法实现理想连续干扰消除。在干扰阈值约束下,推导了非理想连续干扰消除下两次级用户端中断概率的精确表达式,并通过蒙特卡洛仿真验证其正确性。此外,定量分析了各系统相关参数（最大发射功率、干扰阈值、功率分配系数等）的选取对次级用户中断性能的具体影响。结果表明,在相同的系统参数设置下,所提方案次级用户中断性能远优于现有部分中继选择方案。      

On the Performance of Energy-Division Multiple Access with Regular Constellations

In this paper we describe a multiple-access protocol in which different users are assumed to share the same bandwidth and the same pulse. Users employ the same modulation (binary-phase shift keying, quadrature-phase shift keying, and rectangular-phase shift keying are considered) with different transmitted magnitude, and are discriminated on the basis of the corresponding magnitude at receiver location. Conditions for user discrimination are analyzed. The proposed receiver uses successive decoding in order to avoid exponential complexity of maximum-likelihood decoding. Such a scheme, compared to orthogonal multiaccess schemes (e.g. time- or frequency-division multiple access) allows to achieve larger normalized throughput for systems operating in large signal-to-noise ratio range, and may be jointly applied with classical protocols in personal-area networks. Analytical and numerical results, in terms of bit error rate and normalized throughput, are derived for performance evaluation on additive white Gaussian noise channels.     

Resource allocation in underlay cognitive radio networks with full‐duplex cognitive base station

This paper considers an underlay cognitive radio network with a full‐duplex cognitive base station and sets of half‐duplex downlink and uplink secondary users, sharing multiple channels with the primary user. The resource allocation problem to maximize the sum rate of all the secondary users is investigated subject to the transmit power constraints and the interference power constraint. The optimization problem is highly nonconvex, and we jointly use the dual optimization method and the successive convex approximation method to derive resource allocation algorithms to solve the problem. Extensive simulations are shown to verify the performance of the resource allocation algorithms. It is shown that the proposed algorithms achieve much higher sum rate than that of the optimal half‐duplex algorithms and the reference full‐duplex algorithms.     

Proportional fair scheduling with superposition coding in a cellular cooperative relay system

Many works have tackled on the problem of throughput and fairness optimization in cellular cooperative relaying systems. Considering firstly a two-user relay broadcast channel, we design a scheme based on superposition coding (SC) which maximizes the achievable sum-rate under a proportional fairness constraint. Unlike most relaying schemes where users are allocated orthogonally, our scheme serves the two users simultaneously on the same time-frequency resource unit by superposing their messages into three SC layers. The optimal power allocation parameters of each SC layer are derived by analysis. Next, we consider the general multi-user case in a cellular relay system, for which we design resource allocation algorithms based on proportional fair scheduling exploiting the proposed SC-based scheme. Numerical results show that the proposed algorithms allowing simultaneous user allocation outperform conventional schedulers based on orthogonal user allocation, both in terms of throughput and proportional fairness. These results indicate promising new directions for the design of future radio resource allocation and scheduling algorithms.     

Dynamic Allocation of Subcarriers and Transmit Powers in an OFDMA Cellular Network

This paper considers the problem of minimizing outage probabilities in the downlink of a multiuser, multicell orthogonal frequency division multiple access (OFDMA) cellular network with frequency selective fading, imperfect channel state information, and frequency hopping. The task is to determine the allocation of powers and subcarriers for users to ensure that the user outage probabilities are as low as possible. We formulate a min–max outage probability problem and solve it under the constraint that the transmit power spectrum at each base station is flat. In particular, we obtain a subchannel allocation algorithm that has complexity $O(L log L)$ in $L$ , the number of users in the cell. We also consider suboptimal but implementable approaches with and without the flat transmit power spectrum constraint. We conclude that the flat transmit spectrum approach has merit, and warrants further study.      

Interference Suppression Receivers for the Cellular Downlink Channel

We consider the multi-input multi-output (MIMO) downlink channel in the next-generation cellular networks and propose two improved interference suppression receivers for combating out-of-cell interference. The proposed receivers exploit the fact that the co-channel interference seen on the downlink channel (especially the downlink control channel) has a particular structure, in order to obtain significantly improved performance while ensuring low decoding complexity. The first receiver does not require the user to decode the interference or be aware of the particular inner codes employed by the interfering transmitters. The second receiver decodes and subtracts a subset of interferers in a channel-dependent order before processing the desired signal. Each interferer is decoded at most once and the choice of the ordered subset mitigates error propagation. Simulation results are presented to demonstrate the significant gains obtained by the proposed low-complexity receivers over their conventional counterparts.     

A decision feedback decorrelator for a dual rate synchronous DS/CDMA system

A dual rate synchronous DS/CDMA system provides service to low bit rate and high bit rate users. In a fixed duration interval, a low rate user transmits one bit while a high rate user transmits M bits. The differences in the bit transmission rates result in different processing gains for each class of user. In this paper, we propose a decision feedback decorrelator for the dual rate synchronous DS/CDMA system which uses modified correlators and initiates the bit decision process at the end of the high rate bit interval. Each step of the decision process is executed by utilizing the decisions of all previously decoded users. This dual rate decision feedback receiver (evaluated by simulation) is found to outperform two types of decorrelators for dual rate CDMA systems. It is also observed that as the interferers grow stronger relative to the desired user, the performance of the decision feedback receiver for decoding the desired user approaches the single user bound. This revised version was published online in July 2006 with corrections to the Cover Date.     

Asymptotically Optimal Multiple-Access Communication Via Distributed Rate Splitting

We consider the multiple-access communication problem in a distributed setting for both the additive white Gaussian noise channel and the discrete memoryless channel. We propose a scheme called Distributed Rate Splitting to achieve the optimal rates allowed by information theory in a distributed manner. In this scheme, each real user creates a number of virtual users via a power/rate splitting mechanism in the M-user Gaussian channel or via a random switching mechanism in the M-user discrete memoryless channel. At the receiver, all virtual users are successively decoded. Compared with other multiple-access techniques, Distributed Rate Splitting (DRS) can be implemented with lower complexity and less coordination. Furthermore, in a symmetric setting, we show that the rate tuple achieved by this scheme converges to the maximum equal rate point allowed by the information-theoretic bound as the number of virtual users per real user tends to infinity. When the capacity regions are asymmetric, we show that a point on the dominant face can be achieved asymptotically. Finally, when there is an unequal number of virtual users per real user, we show that differential user rate requirements can be accommodated in a distributed fashion     

Coding for a Multiple-Access Frequency-Hopping System

A multiuser system employing on-off FSK modulation in conjunction with frequency hopping is examined for digital transmission. The receiver consists of a bank of bandpass noncoherent detectors followed by a message decoder. An analysis is presented for a transmission channel characterized by Rayleigh fading and additive Gaussian noise. The main source of impairment is interference between users. An upper limit on the number of simultaneous system users for acceptable transmission quality is derived. An example of a system with (one-way) bandwidth of 20 MHz and transmission rate of 32 kbits/s per user shows a maximum of 169 users at an average SNR on the channel of 25 dB and a bit error probability not exceeding 10^-3. The effect of applying error correcting codes to the system is evaluated. It is shown how Reed-Solomon codes can be used to generate both user identification and message coding. Such coding increases the number of users the system can accommodate in the example above to 212. Convolutional codes are shown to be even more effective. Such a code of constraint length 2 results in 285 simultaneous users in the example, which is an increase of 70 percent over an uncoded system. The drawback of coding is an increased complexity of the receiver. The amount of computation needed for the decoding of block and convolutional codes is estimated.     

基于MIMO系统的差分解码算法及性能分析

针对两用户MIMO系统,首先提出了一种基于正交空时分组码的部分差分解码算法,接收端获得一个用户的信道状态信息即可实现对两个用户的解码;然后给出了一种针对两用户MIMO系统的完全差分解码算法,可以在没有任何一个用户的信道状态信息情况下进行解码;最后针对该算法进行了复杂度分析和旋转预编码优化,并通过仿真给出了最优旋转角度。计算机仿真证明该完全差分解码算法有效地降低了解码复杂度。     

Beamforming and power allocation in the downlink of MIMO cognitive radio systems based on multiobjective optimization

In this paper, power allocation and beamforming are considered in a multiple input multiple output (MIMO) downlink cognitive radio (CR) communication system, which a base station (BS) serves one primary user (PU) and one secondary user (SU). In order to design the CR system, a constrained multiobjective optimization problem is presented. Two objectives are the signal to noise plus interference ratios (SINRs) of PU and SU. Since PU has a spectrum license for data communication, a constraint in the optimization problem is that the SINR of PU must be greater than a predefined threshold based on the PU demand requirement. Another constraint is a limitation on power in BS. By considering the mentioned model, three iterative algorithms are proposed. At each iteration of all algorithms, the receiver beamforming vectors are derived based on the maximization of PU and SU SINRs, by assuming that the allocated powers and BS beamforming vectors are known. Also, power is assigned to users such that the constraint of power limitation is satisfied. The difference between the algorithms is in the obtaining of transmitter beamforming parameters. We evaluate the performance of the proposed algorithms in terms of bit error rate (BER) in simulations. Also, the computational complexity of the proposed algorithms is obtained.     

OFDM-UWB系统基于用户速率的多用户动态资源分配算法

在原有动态资源分配算法基础上,提出了一种基于用户速率需求的动态资源分配算法。该算法在满足用户数据速率需求和服务质量要求(QoS)的前提下,以用户公平性为原则,分步执行子载波和比特分配来降低系统总的发射功率。首先,通过比较不同子载波对用户速率的影响,引入速率影响因子,对子载波进行分配;然后为每个用户子载波分配比特,并根据用户速率需求进行比特调整。为了进一步降低系统的复杂度,提出了一种通过子载波分组来完成子载波比特分配的方法。仿真结果表明,该算法能够降低系统功耗、误码率和系统复杂度。     

Downlink user selection and resource allocation for semi-elastic flows in an OFDM cell

We are concerned with user selection and resource allocation in wireless networks for semi-elastic applications such as video conferencing. While many packet scheduling algorithms have been proposed for elastic applications, and many user selection algorithms have been proposed for inelastic applications, little is known about optimal user selection and resource allocation for semi-elastic applications in wireless networks. We consider user selection and allocation of downlink transmission power and subcarriers in an orthogonal frequency division multiplexing cellular system. We pose a utility maximization problem, but find that direct solution is computationally intractable. We first propose a method that makes joint decisions about user selection and resource allocation by transforming the utility function into a concave function so that convex optimization techniques can be used, resulting in a complexity polynomial in the number of users with a bounded duality gap. This method can be implemented if the network communicates a shadow price for power to power allocation modules, which in turn communicate shadow prices for rate to individual users. We then propose a method that makes separate decisions about user selection and resource allocation, resulting in a complexity linear in the number of users.     

Adaptive Max SNR Packet Scheduling for OFDM Wireless Systems

In this paper, we consider scheduling and resource allocation for a downlink in a wireless OFDM system. If each broadcast sub channel is allocated to a user according to max SNR selection, optimal system throughput is obtained for the cost of a significant loss in fairness among users. As a solution to resolve this issue and in an attempt at reaching a compromise between fairness and throughput, we propose to add to the max SNR scheme a weak control based on user QoS requirements. In this work, user latency between two successive channel accesses is considered as a parameter for the control. The feedback of quantized channel state information (CSI) is proposed to reduce the feedback burden. Performance analysis of the proposed scheme has been presented to illustrate the capacity-fairness-feedback trade-off of the considered scheme compared to max SNR and proportional fair algorithms used as benchmark.

Approaching MIMO-OFDM Capacity with Per-Antenna Power and Rate Feedback

This paper presents power-efficient transmission schemes for the multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) block-fading channel under the assumption that the channel during each fading block is known perfectly at the receiver, but is unavailable at the transmitter. Based on the well-known vertical Bell Labs layered space-time (V-BLAST) architecture that employs independent encoding for each transmit antenna and successive decoding at the receiver, this paper presents a per-antenna-based power and rate feedback scheme, termed the "closed-loop" V- BLAST, for which the receiver jointly optimizes the power and rate assignments for all transmit antennas, and then returns them to the transmitter via a low-rate feedback channel. The power and rate optimization minimizes the total transmit power for support of an aggregate transmission rate during each fading block. Convex optimization techniques are used to design efficient algorithms for optimal power and rate allocation. The proposed algorithms are also modified to incorporate practical system constraints on feedback complexity and on modulation and coding. Furthermore, this paper shows that the per-antenna-based power and rate control can be readily modified to combine with the conventional linear MIMO transmit preceding technique as an efficient and capacity-approaching partial-channel-feedback scheme. Simulation results show that the closed-loop V-BLAST is able to approach closely the MIMO-OFDM channel capacity assuming availability of perfect channel knowledge at both the transmitter and the receiver.     

Optimum Power Allocation for Single-User MIMO and Multi-User MIMO-MAC with Partial CSI

We consider both the single-user and the multi-user power allocation problems in MIMO systems, where the receiver side has the perfect channel state information (CSI), and the transmitter side has partial CSI, which is in the form of covariance feedback. In a single-user MIMO system, we consider an iterative algorithm that solves for the eigenvalues of the optimum transmit covariance matrix that maximizes the rate. The algorithm is based on enforcing the Karush-Kuhn-Tucker (KKT) optimality conditions of the optimization problem at each iteration. We prove that this algorithm converges to the unique global optimum power allocation when initiated at an arbitrary point. We, then, consider the multi-user generalization of the problem, which is to find the eigenvalues of the optimum transmit covariance matrices of all users that maximize the sum rate of the MIMO multiple access channel (MIMO-MAC). For this problem, we propose an algorithm that finds the unique optimum power allocation policies of all users. At a given iteration, the multi-user algorithm updates the power allocation of one user, given the power allocations of the rest of the users, and iterates over all users in a round-robin fashion. Finally, we make several suggestions that significantly improve the convergence rate of the proposed algorithms.